CN104937856A - Method and apparatus for estimating angle of arrival, and electronic device - Google Patents

Method and apparatus for estimating angle of arrival, and electronic device Download PDF

Info

Publication number
CN104937856A
CN104937856A CN201380002828.4A CN201380002828A CN104937856A CN 104937856 A CN104937856 A CN 104937856A CN 201380002828 A CN201380002828 A CN 201380002828A CN 104937856 A CN104937856 A CN 104937856A
Authority
CN
China
Prior art keywords
matrix
measurement result
aerial array
angle
redundant dictionary
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201380002828.4A
Other languages
Chinese (zh)
Other versions
CN104937856B (en
Inventor
刘劲楠
王悦
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huawei Technologies Co Ltd
Original Assignee
Huawei Technologies Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huawei Technologies Co Ltd filed Critical Huawei Technologies Co Ltd
Publication of CN104937856A publication Critical patent/CN104937856A/en
Application granted granted Critical
Publication of CN104937856B publication Critical patent/CN104937856B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Variable-Direction Aerials And Aerial Arrays (AREA)
  • Radio Transmission System (AREA)

Abstract

The present invention provides a method and an apparatus for estimating an angle of arrival and an electronic device, which are used for solving the technical problem existing in the prior art that larger storage space is needed to store a redundant dictionary. The electronic device, used in an orthogonal frequency division multiplexing communications system, comprises a processor, used for obtaining antenna array measurement results of M array elements, and estimating angles of arrival of K radio signals according to the antenna array measurement results and a redundant dictionary, the redundant dictionary being a partially-discrete Fourier transform matrix, M and K being positive integers.

Description

Method and apparatus for estimating angle of arrival, and electronic device
A kind of method, device and technical field of electronic equipment for estimating angle of arrival
The present invention relates to the communications field, more particularly to a kind of method, device and electronic equipment for estimating angle of arrival.Background technology
Utilize the angle of arrival in aerial array measurement signal source（DOA, Direction of Arrival) all played an important role in radar, communication, sonar, voice etc. very numerous areas.Wherein in wireless communications, base station can pass through measuring terminals signal（That is upward signal）DOA, realize positioning to terminal, can also be just blunt according to DO A, carry out Inferior obliqued overaction（Downlink Beam Forming) weight selection.Likewise, terminal can also be by measuring base station signal（That is downstream signal）DOA, carry out uplink beam shaping (Uplink Beam Forming) weight selection.
In the existing estimation DOA based on compressed sensing algorithm method, after generation redundant dictionary, to store redundant dictionary and be accomplished by larger memory space.The content of the invention
The present invention provides a kind of method, device and electronic equipment for estimating angle of arrival, and the technical problem of larger memory space is needed to solve storage redundant dictionary present in prior art.
In a first aspect, the present invention provides a kind of electronic equipment, applied in orthogonal FDM communication system, including：Processor, the aerial array measurement result for obtaining M array element；Based on the aerial array measurement result and redundant dictionary, the angle of arrival of K wireless signal is estimated, wherein, the redundant dictionary is some discrete Fourier transform matrix, wherein, M and K are positive integer.
With reference in a first aspect, in the first possible embodiment, when the M array element includes the array element with least two dimensions, the processor, specifically for：The aerial array measurement result of the array element of each dimension in the M array element is obtained respectively；For the array element of each dimension, based on the aerial array measurement result and the redundant dictionary, K angle of arrival is estimated；Based on described each K angle of arrival of the array element of individual dimension, estimates the K angle of arrival of the M array element.
With reference to first aspect or the first possible implementation, in second of possible embodiment, the redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and the redundant dictionary is constituted by N number of direction vector.
With reference to second of possible embodiment, in the third possible embodiment, the direction vector is determined according to below equation：
2i 0) = [1 ej^(!-2i/N) e(M- 1) (1- 2i/N)] T wherein, be the angle of grid described in i-th ,=arccos (l-2i/ N), i=0 ..., N-l, M N, N for 2 integer time Power.
With reference to any one of first aspect and the first possible implementation to the third possible implementation, in the 4th kind of possible implementation, the processor, specifically for：Based on the aerial array measurement result and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the first matrix described in the computing of the second matrix and second matrix for the matrix related to the aerial array measurement result；Based on the sparse signal matrix, the angle of arrival is estimated.
With reference to the 4th kind of possible embodiment, in the 5th kind of possible embodiment, the processor is specifically additionally operable to：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
With reference to the 5th kind of possible embodiment, in the 6th kind of possible embodiment, the element of the first derivative matrix is determined according to below equation：
B( jj π) = j 2;r(jj ~^cj^(jj-D(i-2ii N)
, N
Wherein, jj is the line number of the first derivative matrix, is the first derivative matrix column number, jj=0, l ..., M-l ,=0,1, Ν -1. With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 7th kind of possible implementation, the processor, specifically for：First matrix-expand is tieed up into matrix into N；Inverse fast Fourier transform is carried out to the N-dimensional matrix, and carries out fast Fourier displacement.
With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 8th kind of possible implementation, the processor, specifically for：Inverse fast Fourier transform is carried out to second matrix, the 3rd matrix is obtained；By the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding M in the 3rd matrix, it is defined as the odd term of the operation result.
With reference to any one of first aspect and the first possible implementation to the 8th kind of possible implementation, in the 9th kind of possible implementation, the electronic equipment also includes：Aerial array, for being carried out receiving the signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
With reference to any one of first aspect and the first possible implementation to the 8th kind of possible implementation, in the tenth kind of possible implementation, the electronic equipment, in addition to：Receiver, processor is sent to for receiving the aerial array measurement result, and by the aerial array measurement result.
With reference to any one of first aspect and the first possible implementation to the tenth kind of possible implementation, in a kind of the tenth possible implementation, the electronic equipment is specially terminal or base station.
Second aspect, the present invention provides a kind of device for estimating angle of arrival, applied in orthogonal FDM communication system, including：Aerial array measurement result receiving unit, the aerial array measurement result for obtaining M array element；Angle-of- arrival estimation unit, for based on the aerial array measurement result and redundant dictionary, estimating the angle of arrival of K wireless signal, wherein, the redundant dictionary is some discrete Fourier transform matrix, and M and K are positive integer.
With reference to second aspect, in the first possible embodiment, when the M array element includes the array element with least two dimensions, the angle-of- arrival estimation unit is specifically included：Aerial array measurement result inputs subelement, the aerial array measurement result for obtaining the array element of each dimension in the M array element respectively；Single dimension angle of arrival computation subunit, for the array element for each dimension, based on the aerial array measurement result and the redundant dictionary, estimates K angle of arrival；Various dimensions are reached Angle computation subunit, for K angle of arrival of the array element based on each dimension, calculates the K angle of arrival of the M array element.
With reference to second aspect or the first possible implementation, in second of possible embodiment, the redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and the redundant dictionary is constituted by N number of direction vector.
With reference to second of possible embodiment, in the third possible embodiment, the direction vector is determined according to below equation：
2i 0) e (M- 1)(1- 2i/N)]T
Wherein, it is the angle of grid described in i-th ,=arccos (l-2i/ N), i=0 ..., N-l, M N,
N is 2 integral number power.
With reference to any one of second aspect and the first possible implementation to the third possible implementation, in the 4th kind of possible implementation, the angle-of- arrival estimation unit is specifically included：Sparse signal matrix computations subelement, for based on the aerial array measurement result and the redundant dictionary, sparse signal matrix to be obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the first matrix described in the computing of the second matrix and second matrix for the matrix related to the aerial array measurement result；Subelement is estimated, for based on the sparse signal matrix, estimating the angle of arrival.
With reference to the 4th kind of possible embodiment, in the 5th kind of possible embodiment, the sparse signal matrix computations subelement, specifically for：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
With reference to the 5th kind of possible embodiment, in the 6th kind of possible embodiment, determine that element is in the first derivative matrix according to below equation： B( jj ii) ： j2;r(jj ~ ^ cj^( jj -i)d-2ii N)
, N
Wherein, jj is the row subscript of the first derivative matrix, and ii is the first derivative matrix column subscript, jj=0, l ..., M-l ,=0,1, Ν -1.
With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 7th kind of possible implementation, the sparse signal matrix computations subelement is specifically included：Subelement is extended, for first matrix-expand to be tieed up into matrix into Ν；Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to Ν dimension matrixes, and carries out Fast Fourier Transform (FFT) displacement.
With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 8th kind of possible implementation, the sparse signal matrix computations subelement is specifically included：Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to second matrix, obtains the 3rd matrix；Determination subelement, for by the even item in preceding Μ in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding Μ in the 3rd matrix, it is defined as the odd term of the operation result.
With reference to any one of second aspect and the first possible implementation to the 8th kind of possible implementation, in the 9th kind of possible implementation, the aerial array measurement result receiving unit, specifically for：Carried out receiving the signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
With reference to any one of second aspect and the first possible implementation to the 8th kind of possible implementation, in the tenth kind of possible implementation, the aerial array measurement result receiving unit, specifically for：Receive the aerial array measurement result sent by opposite equip..
The third aspect, the present invention provides a kind of method for estimating angle of arrival, applied in orthogonal FDM communication system, including：Obtain the aerial array measurement result of Μ array element；Based on the aerial array measurement result and redundant dictionary, the angle of arrival of Κ wireless signal is estimated, wherein, the redundant dictionary is some discrete Fourier transform matrix, and Μ and Κ are positive integer. With reference to the third aspect, in the first possible embodiment, when the M array element includes the array element with least two dimensions, the aerial array measurement result of described M array element of acquisition is specially：The aerial array measurement result of the array element of each dimension in the M array element is obtained respectively；It is described to be based on the aerial array measurement result and redundant dictionary, estimate the angle of arrival of K wireless signal, specifically include：For the array element of each dimension, based on the aerial array measurement result and the redundant dictionary, K angle of arrival is estimated；K angle of arrival of the array element based on each dimension, calculates the K angle of arrival of the M array element.
With reference to the third aspect or the first possible implementation, in second of possible embodiment, the redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and the redundant dictionary is constituted by N number of direction vector.
With reference to second of possible embodiment, in the third possible embodiment, the direction vector is determined according to below equation：
^ 0. ) = [1 e j (1- 2i / N) e(M-1) (1-2i/N)] T wherein, be the angle of grid described in i-th, ^=arccos (l-2i/N), i=0 ..., N-l, M N, N are 2 integral number power.
With reference to any one of the third aspect and the first possible implementation to the third possible implementation, in the 4th kind of possible implementation, it is described to be based on the aerial array measurement result and redundant dictionary, estimate the angle of arrival of K wireless signal, specifically include：Based on the aerial array measurement result and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the first matrix described in the computing of the second matrix and second matrix for the matrix related to the aerial array measurement result；Based on the sparse signal matrix, the angle of arrival is estimated.
It is described to be based on the aerial array measurement result and the redundant dictionary in the 5th kind of possible embodiment with reference to the 4th kind of possible embodiment, sparse letter is obtained using the compressed sensing algorithm Number matrix, be specially：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
With reference to the 5th kind of possible embodiment, in the 6th kind of possible embodiment, the element of the first derivative matrix is determined according to below equation：
B( jj ϋ) = j 2;γ 」 ~ ^ cj^( jj-D(i-2ii/N)
, N
Wherein, jj is the line number of the first derivative matrix, and ii is the first derivative matrix column number, jj=0, l ..., M-l ,=0,1, Ν -1.
With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 7th kind of possible implementation, the first matrix is multiplied using the transposed matrix right side of fast Fourier algorithm redundant dictionary, specifically included：First matrix-expand is tieed up into matrix into Ν；Inverse fast Fourier transform is carried out to Ν dimension matrixes, and carries out fast Fourier displacement.
With reference to any one of the 4th kind of possible implementation to the 6th kind of possible implementation, in the 8th kind of possible implementation, the computing of the second matrix is multiplied using the fast Fourier algorithm redundant dictionary right side, is specifically included：Inverse fast Fourier transform is carried out to second matrix, the 3rd matrix is obtained；By the even item in preceding Μ in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding Μ in the 3rd matrix, it is defined as the odd term of the operation result.
With reference to any one of the third aspect and the first possible implementation to the 8th kind of possible implementation, in the 9th kind of possible implementation, before the acquisition array measurement knot is bright, methods described also includes：Carried out receiving the signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
With reference to any one of the third aspect and the first possible implementation to the 8th kind of possible implementation, in the tenth kind of possible implementation, the acquisition array measurement result is specially：Receive the aerial array measurement result sent by opposite equip.. Beneficial effects of the present invention：
The present invention provides a kind of electronic equipment, and applied in orthogonal FDM communication system, the electronic equipment includes：Processor, for obtaining the aerial array measurement result of M array element and tying bright and redundant dictionary based on aerial array measurement, estimate the angle of arrival of K wireless signal, wherein, the redundant dictionary used herein is some discrete Fourier transform matrix, that is there is the discrete Fourier transform factor in the redundant dictionary, so, just can be with a part for the complete Discrete Fourier transform in multiplexed quadrature frequency division multiplexing communication system, extra memory space need not be consumed to store redundant dictionary, so, efficiently solve the technical problem that the larger memory space of redundant dictionary needs is stored present in prior art, save system resource.Brief description of the drawings
Fig. 1 be one embodiment of the invention in electronic equipment functional block diagram；
Fig. 2A-Fig. 2 B be another embodiment of the present invention in electronic equipment functional block diagram；
Fig. 3 be one embodiment of the invention in uniform linear array structural representation；
Fig. 4 be one embodiment of the invention in L-shaped array structural representation；
Fig. 5 is the space angle and the relation schematic diagram of deflection in one embodiment of the invention；
Fig. 6 be one embodiment of the invention in estimation angle of arrival device functional block diagram；
Fig. 7 be one embodiment of the invention in estimation angle of arrival method flow chart.Embodiment
The embodiment of the present application solves the technical problem that the larger memory space of redundant dictionary needs is stored present in prior art by providing a kind of method, device and electronic equipment for estimating angle of arrival.
Technical scheme in the embodiment of the present application is solves the problem of above-mentioned storage redundant dictionary needs larger memory space, and general thought is as follows：
The present invention provides a kind of device for estimating angle of arrival, and applied in orthogonal FDM communication system, the device includes：Angle-of- arrival estimation unit, the unit is used for the aerial array measurement result for obtaining M array element and based on aerial array measurement result and redundant dictionary, estimates the angle of arrival of K wireless signal, its In, the redundant dictionary used herein is some discrete Fourier transform matrix, that is there is the discrete Fourier transform factor in the redundant dictionary, so, just can be with a part for the complete Discrete Fourier transform in multiplexed quadrature frequency division multiplexing communication system, without consuming, extra memory space stores redundant dictionary, so, the technical problem that the larger memory space of redundant dictionary needs is stored present in prior art is efficiently solved, memory space is saved.
Technical solution of the present invention is described in detail below by accompanying drawing and specific embodiment, it should be understood that the specific features in the embodiment of the present invention and embodiment are the detailed description to technical solution of the present invention, rather than the restriction to technical solution of the present invention, in the case where not conflicting, the technical characteristic in the embodiment of the present invention and embodiment can be mutually combined.
The present invention provides a kind of electronic equipment, and the electronic equipment can be OFDM（OFDM, Orthogonal Frequency Division Multiplexing) any node in communication system, such as, terminal, base station can also be other Wireless Telecom Equipments certainly, and the application is not specifically limited.
It refer to Fig. 1, Fig. 1 is the functional block diagram of the electronic equipment of the estimation angle of arrival in one embodiment of the invention.The electronic equipment, including：Processor 10, the aerial array measurement result for obtaining M array element；Based on aerial array measurement result and redundant dictionary, the angle of arrival of K wireless signal is estimated, wherein, redundant dictionary is some discrete Fourier transform matrix, wherein, M and K are positive integer.
Optionally, above-mentioned electronic equipment can also include transceiver 20, memory 30, if the bright electronic equipment is terminal, can also include display unit, WIFI module, I/O interfaces etc..
In actual applications, above-mentioned aerial array measurement result is to measure acquisition to the wireless signal that it is received by aerial array, then, there are following two situations.
The first situation, aerial array measurement result is measured by electronic equipment oneself and obtained, and now, as shown in Figure 2 A, electronic equipment also includes：Aerial array 11a, for being carried out receiving signal measurement acquisition aerial array measurement result according to measurement configuration.
Specifically, aerial array 11a is arranged in same equipment with processor 10, so, aerial array 11a is measured after the wireless signal of signal source transmitting is received according to measurement configuration to the signal, and generate aerial array measurement result, then the result is sent to processor 10, certainly, aerial array 11a can only have the function of receiving signal, after aerial array 11a receives wireless signal, sent out The measurement processor in electronic equipment is given, aerial array measurement result is generated by it, and the result is sent to processor 10.
In the present embodiment, aerial array 11a can be one-dimensional aerial array, such as hook linear array, or multi-dimensional antenna array, and such as two-dimentional L-shaped array, the application is not specifically limited.Above-mentioned measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
Further, if aerial array 11a is arranged in same electronic equipment with processor 10, then, above-mentioned measurement configuration can voluntarily be determined by electronic equipment, without being issued by other equipment.
Second of situation, what aerial array measurement result was measured by opposite equip. and sent, now, as shown in Figure 2 B, electronic equipment also includes：Receiver lib, processor is sent to for receiving antenna array measurement result, and by aerial array measurement result.
Specifically, aerial array is arranged on from processor 10 in different equipment, namely aerial array is provided with opposite equip., so, after aerial array is measured the wireless signal that it is received and obtains aerial array measurement result, the measurement result is sent to electronic equipment, and received by receiver lib, and then is sent to processor 10.
Further, if aerial array and processor 10 are separately positioned in terminal and base station, so, above-mentioned measurement configuration is handed down to terminal by base station or consults what is determined with base station, terminal is after completion measurement generation aerial array measurement knot is bright, base station is just sent it to, the receiver lib on base station is received and is sent to processor 10.If aerial array is arranged on base station, and processor 10 is when being arranged in terminal, the measurement configuration that base station can be issued with terminal or consult to determine with terminal is measured, and aerial array measurement result is sent to the receiver lib in terminal, and processor 10 is transmitted to by receiver lib.
First such scheme is illustrated so that aerial array is uniform linear array as an example below.
Fig. 3 is refer to, Fig. 3 is the structural representation of uniform linear array.It is d that the aerial array, which has between M array element, two array elements distance, the angle of wireless signal to each array element be (9, wherein<It is the angle in direction of arrival of signal and aerial array direction.
It should be noted that, above-mentioned redundant dictionary is some discrete Fourier transform matrix, the discrete Fourier transform factor therein is the Fourier transformation factor in OFDM in multiplexing electronic equipment, so, electronic equipment can construct redundant dictionary offline, without Fourier's factor in special storage redundant dictionary Only need to call the OFDM stored Fourier's factor when in use, save system resource.
First, above-mentioned redundant dictionary is constructed offline.
The first step, N number of grid is evenly dividing into by the scope of trigonometric function value.
For example, by functional value interval [- 1 of the cosine function on 0 ° ~ 180 °, 1] uniformly it is divided into N part, that is, forms N number of grid, then, the corresponding cosine value of i-th grid is just 1- 2i/N, i=0,1 ..., N-l, the corresponding angle of i-th of grid is exactly=arccos (l -2/N).
In actual applications, if angle of arrival to be defined as to the angle of normal direction of direction of arrival of signal and aerial array, above-mentioned redundant dictionary can be represented with the SIN function of the angle.Likewise, by sine function -90. ~90.On functional value interval [- 1,1] be uniformly divided into N number of part, that is, form N grid.So, the corresponding sine value of i-th grid is just-l+2i/N, i=0,1 ..., N-l, and the corresponding angle of i-th grid is exactly θ ,=arcsin (- l+2i/N).
When specific implementation, those skilled in the art can sets itself be that redundant dictionary is constructed with cosine function, or redundant dictionary is constructed with SIN function, the application is not especially limited.In the present embodiment, by taking cosine function construction redundant dictionary as an example.
Second step, calculates the direction vector of each grid in N number of grid, and constitutes redundant dictionary by N number of direction vector.
Specifically, its direction vector first is asked to the corresponding angle of each grid in above-mentioned N number of grid, wherein, the direction vector such as formula of i-th of grid（1) shown in.
2i 0.) = [1 e (1- 2i/N) eJ (M-1) (1-2i/N)] T is in above formula, and the angle of i-th of grid is=£^∞8(1-21/1^), i=0, l ..., N-l,
M«N。
Then, the N number of direction vector composition redundant dictionary obtained, such as formula will be calculated（2) shown in.
A = [a(6()),a(6i),...,a(¾.1)] (2)In the present embodiment, N is 2 integral number power, now, and the discrete Fourier transform factor just becomes for FFT (Fast Fourier Transformation, fast Fourier 4 an ancient type of spoons of change）The factor. So, just processor 10 is used for carrying out the redundant dictionary of angle-of- arrival estimation constructed, now, memory 20 stores the Fourier transformation factor and above-mentioned redundant dictionary in OFDM.
Next, processor 10 begins to carry out angle-of- arrival estimation.
The first step, processor 10 can be based on aerial array measurement result and redundant dictionary, and sparse signal matrix is obtained using compressed sensing algorithm.
For example, using the compressed sensing algorithm based on greedy algorithm, input above-mentioned redundant dictionary A, array measurement result Y, i.e. receipt signal matrix, also degree of rarefication K, that is, need the angle number of estimation, by calculating, the sparse signal matrix X recovered is exported, wherein, the collection of the position of the nonzero element in X is combined into T.
Here with SOMP (Simultaneous orthogonal Match Pursuit, synchronous orthogonal matching pursuit) exemplified by, pass through continuous iteration obtain it is sparse recover：
Step 1:Initialization.Make residual error r=Y, T=0.
Step 2:Iterative calculation, obtains the X for the condition that meets.
A, matching are related, i.e., multiply the residual error r in step 1 with the redundant dictionary A transposed matrix right side, as shown in formula (3).
U=A'.r (3) b, location tracking, return to the subscript of a line of maximum absolute value in U, i.e.,： t = argmax |ui|.C, renewal location sets T, that is to say, that take Τ and t union, and replaced originally with result
T。
D, corresponding T row in Α matrixes are taken, obtain Ak, i.e. Ak=AIT。
E, estimate update, that is, seek AkPseudo inverse matrix, and the right side multiplies Y, obtains estimate X.
F, residual error update, i.e., with the above-mentioned estimate X tried to achieve, according to formula（4) residual error ^ is updated
R=Y- AX (4) are tried to achieve by above-mentioned Bu Sudden a ~ f after the residual error r after updating, and the r after renewal is substituted into step a, are then followed by performing step 1~ iteration successively, wherein, iterations have to be larger than equal to K, so, until iterations reaches that this black norm of the not Luo Beini of maximum iteration and r matrixes is less than a threshold value, such as lx 10-5, stop iteration, now, the estimate X obtained by step e just recovers for sparse signal Matrix.
It should be noted that, in above-mentioned calculating process, the transposed matrix right side such as the A occurred in step a multiplies r, that is the first matrix, and the A right sides occurred in step f multiply X, that is the second matrix, in the case of integral number powers of the N for 2, can use fast Fourier algorithm to calculate.
For example, the A transposed matrix right side multiplies r, it is possible to r first is extended into N-dimensional matrix, then carries out FFT inverse transformations, a FFT displacement is finally carried out, the U in step a has just been obtained.For another example, the A right sides multiply X, just FFT inverse transformations first can be carried out to the matrix X of the mat woven of fine bamboo strips two, obtain the 3rd matrix, that is, X FFT inverse-transform matrixs, then, by the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary A right sides multiply the second matrix X operation result, by the inverse value of the odd term in preceding M in the 3rd matrix, is defined as the odd term of operation result.
Second step, processor 10 is obtained after sparse signal matrix, can be based on the sparse signal matrix, be estimated angle of arrival.
Specifically, if the position of nonzero element is located on grid, then, it is assumed that i is designated as under the sparse signal nonzeros row obtained by the first step, then its angle of arrival is just arCC0S(l- 2i / N)。
In another embodiment, in the first step, the position of some nonzero elements may not be on grid in the sparse signal matrix being resumed, so, in order to obtain the position of these non-grid elements, when being compressed perception algorithm, sparse Bayesian deduction-singular value decomposition algorithm can be used（SBI-SVD, Sparsity Bayesian Inference-Singular Value Decomposition, Off- Grid Direction of Arrival Estimation Using Sparse Bayesian Inferenc, IEEE Transaction on Signal) Processing, vol, 61, No. l, Janary, 2013), or synchronous orthogonal matching pursuit-least-squares algorithm (SOMP-LS, Simultaneous Orthogonal Match Pursuit- Least Squared, An alternating descent algorithm for the off-grid DOA estimation problem with sparsity constraints, EUSIPCO, 2012) sparse signal matrix is obtained, in these algorithms in addition to being related to aerial array measurement result with redundant dictionary, the first derivative matrix of redundant dictionary can also be used, to obtain sparse signal matrix.
For example, referring to formula（1) and likes（2), the element in the single order of redundant dictionary matrix reciprocal can be such as formula（5) shown in. (~ the ^ of B (jj jj) two j 2c j^( jj -i)d-2ii )
(5) wherein, jj is the line number of first derivative matrix, is first derivative matrix column number, jj=0,1 ..., Μ -1, ii=0, l ..., N-l.
Accordingly, in second step, due to passing through above-mentioned SBI-SVD or SOMP-LS algorithms, the position i and offset Δ of sparse signal nonzeros can be obtained, so, its angle of arrival is then arccos (l-2 (i+diag (A))/N).
Certainly, there are many algorithms for recovering sparse signal matrix in actual applications, the application is not specifically limited, wherein, as long as the transposition right side for redundant dictionary occur multiplies the first matrix or the redundant dictionary right side multiplies the second matrix, above-mentioned FFT fast algorithms can be just used, the processing speed of processor 10 is improved.
The estimation of the angle of arrival to one-dimensional aerial array is achieved that by above-mentioned steps, and in actual applications, M array element, which can include the array element with least two dimensions, i.e. aerial array, has at least two dimensions.Below using aerial array as two-dimensional array, illustrated exemplified by such as L-shaped aerial array.
Fig. 4 is refer to, Fig. 4 is the structural representation of L-shaped aerial array.Assuming that aerial array has M array element, processor 10, the aerial array measurement result for obtaining the array element of each dimension in M array element respectively；For the array element of each dimension, bright and redundant dictionary is tied based on aerial array measurement, K angle of arrival is estimated；K angle of arrival of the array element based on each dimension, estimates K angle of arrival of M array element.
Specifically, processor 10 obtains the first dimension, the aerial array measurement result of the array element of such as horizontal direction respectively, and second dimension, antenna measurement knot such as the array element of vertical direction is bright, wherein, the aerial array measurement result of each dimension is obtained by following process.
First, aerial array is divided into two independent one-dimensional hook linear arrays by the equipment with aerial array, and the space angle α and β of each uniform linear array are estimated respectively, as shown in figure 5, Fig. 5 is the relation schematic diagram of space angle and deflection.
Next, rarefaction representation antenna receives signal and space angle α, β.For example, the antenna reception signal of horizontal direction, i.e. X-axis is just： Υχ = ΑΧχ + Εχ, and the antenna in vertical direction, i.e. y-axis Receiving signal is just： Yy =AXy+Ey, wherein, A is redundant dictionary, Xx, XyIt is the rarefaction representation of signal signal on X axles, y-axis array element, that is, sparse signal matrix. YxIt is the receipt signal matrix for representing array element in X-axis, YyIt is the receipt signal matrix of array element in y-axis, Ex, EyRespectively noise matrix of the signal in X-axis, y-axis array element.
3rd step, it is just blunt according to Y respectivelyx, A, K, and Yy, A, K estimate cos a, cos β using the algorithm of compressed sensing.The method of angle of arrival is namely estimated the aerial array in two dimensions using one-dimensional aerial array respectively, i.e., using the method in said one or multiple embodiments, Χ is obtained respectivelyχAnd Xy, then, it is possible to according to XxIn non-zero position ix, obtain coso
=l-2ix/ N, likewise, according to XyIn non-zero position iy, obtain cos β=l-2iy/N.Certainly, ix, iyCan be vector.
In another embodiment, identical with the algorithm of one-dimensional aerial array, when nonzero element is not on grid, processor 10 is respectively according to Υχ, Α, Β, Κ, and Yy, A, B, K, wherein, Β is Α first derivative matrix, using the algorithm of compressed sensing, according to xxIn non-zero position ^ and ^, obtain cos=l -2 (ix+ diag (Ax))/N, likewise, according to XyIn non-zero position iyAnd Ay, obtainCOSy9 = l_2(iy+diag(Ay))/N.Certainly, ix, iyCan be vector.
Finally, in order to be matched to the element in cos α and cos β, antitrigonometric function is realized using angle automatching algorithm, such as fitting, to calculate angle of arrival.
For example, level angle/： / = arctan(cos β I cos a) .
Vertical angle 。
From the foregoing, due to the electronic equipment in said one or multiple embodiments, applied in orthogonal FDM communication system, the electronic equipment includes：Processor, for obtaining the aerial array measurement result of M array element and based on aerial array measurement result and redundant dictionary, estimating the angle of arrival of K wireless signal, wherein, the redundant dictionary used herein is some discrete Fourier transform matrix, that is to say, that There is the discrete Fourier transform factor in the redundant dictionary, so, just can be with a part for the complete Discrete Fourier transform in multiplexed quadrature frequency division multiplexing communication system, extra memory space need not be consumed to store redundant dictionary, so, the technical problem that the larger memory space of redundant dictionary needs is stored present in prior art is efficiently solved, system resource is saved.
Based on same inventive concept, the present invention also provides a kind of device for estimating angle of arrival, and the device is applied in ofdm communication system, and the device can be arranged in any node of this communication system, as shown in fig. 6, Fig. 6 is the functional block diagram of the device of estimation angle of arrival in the present embodiment.The device includes：Aerial array measurement result receiving unit 61, the aerial array measurement result for obtaining M array element；Angle-of- arrival estimation unit 62, for based on aerial array measurement result and redundant dictionary, estimating the angle of arrival of K wireless signal, wherein, redundant dictionary is some discrete Fourier transform matrix, and M and K are positive integer.
Further, the device measuring where aerial array measurement result has the device is obtained, then, aerial array measurement result receiving unit 61, specifically for：Carried out receiving signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, above-mentioned measurement configuration at least includes one or more of degree of rarefication, snapshot number and each snapshot bit number, naturally it is also possible to which, including other specification, the application is not specifically limited.
Further, the opposite equip. of equipment where aerial array measurement result has the device, which is measured, obtains, then, aerial array measurement result receiving unit 61, specifically for：Receive the aerial array measurement result sent by opposite equip..
In actual applications, aerial array can be one-dimensional aerial array, or multi-dimensional antenna array, wherein, when M array element includes the array element with least two dimensions, angle-of- arrival estimation unit 62 can include：Aerial array measurement result inputs subelement, and the aerial array measurement result of the array element of each dimension in M array element is obtained for Fen Do；Single dimension angle of arrival computation subunit, for the array element for each dimension, based on aerial array measurement result and redundant dictionary, estimates K angle of arrival；Various dimensions angle of arrival computation subunit, for K angle of arrival of the array element based on each dimension, calculates K angle of arrival of M array element.
Further, above-mentioned redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and redundant dictionary is constituted by N number of direction vector.Specifically, according to formula（1) direction vector is determined, then, redundant dictionary such as public affairs Formula（2) shown in.
Further, angle-of- arrival estimation unit 62, can include：Sparse signal matrix computations subelement, for based on aerial array measurement result and redundant dictionary, sparse signal matrix to be obtained using compressed sensing algorithm, wherein, at least include in compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the matrix of computing first and the second matrix of the second matrix for the matrix related to aerial array measurement result；Subelement is estimated, for based on sparse signal matrix, estimating angle of arrival.
In another embodiment, for nonzero element not on grid, sparse signal matrix computations subelement, specifically for：First derivative matrix based on aerial array measurement result, redundant dictionary and redundant dictionary, sparse signal matrix is obtained using compressed sensing algorithm.Specifically, in first derivative matrix shown in element such as formula (5).
Further, sparse signal matrix computations subelement, is specifically included：Extend subelement, for by the first matrix-expand into N-dimensional matrix；Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to N-dimensional matrix, and carries out Fast Fourier Transform (FFT) displacement.
Further, sparse signal matrix computations subelement, is specifically included：Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to the second matrix, obtains the 3rd matrix；Determination subelement, for by the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of the second matrix, and by the inverse value of the odd term in preceding M in the 3rd matrix, is defined as the odd term of operation result.
Various change mode and instantiation in electronic equipment in previous embodiment are equally applicable to the device of the present embodiment, pass through the foregoing detailed description to electronic equipment, those skilled in the art are clear that the implementation of device in the present embodiment, so it is succinct for specification, it will not be described in detail herein.
Based on same inventive concept, the present invention provides a kind of method for estimating angle of arrival, applied to any node in orthogonal FDM communication system, can apply in terminal, can also apply on base station, the application is not especially limited.
Fig. 7 is refer to, this method includes：
S101 :The aerial array measurement knot for obtaining M array element is bright； S102:Based on aerial array measurement result and redundant dictionary, the angle of arrival of K wireless signal is estimated, wherein, redundant dictionary is some discrete Fourier transform matrix, and M and K are positive integer.
In the present embodiment, S101 can have two embodiments.The first, aerial array measurement result is to be obtained by the node by the aerial array measurement itself set, then, S101 can be：Carried out receiving signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.Second, aerial array measurement result is sent by the opposite equip. for being provided with aerial array, then, S101 can be：Receive the aerial array measurement result sent by opposite equip..
Optionally, when M array element includes the array element with least two dimensions, S101 can be：The aerial array measurement result of the array element of each dimension in M array element is obtained respectively；Based on aerial array measurement result and redundant dictionary, estimate the angle of arrival of K wireless signal, specifically include：For the array element of each dimension, based on aerial array measurement result and redundant dictionary, K angle of arrival is estimated；K angle of arrival of the array element based on each dimension, calculates K angle of arrival of M array element.
Further, the redundant dictionary in said one or multiple embodiments can be obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；Calculate the direction vector of each grid in N number of grid, and from N number of direction Xiang Liang Group into redundant dictionary.Specifically, direction vector such as formula（1) shown in, corresponding, redundant dictionary such as formula（2) shown in.
Further, S102 can include：Based on aerial array measurement result and redundant dictionary, sparse signal matrix is obtained using compressed sensing algorithm, wherein, at least include in compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the matrix of computing first and the second matrix of the second matrix for the matrix related to aerial array measurement result；Based on sparse signal matrix, angle of arrival is estimated.
In another embodiment, for estimative nonzero element not on grid, S102 can be：First derivative matrix based on aerial array measurement result, redundant dictionary and redundant dictionary, sparse signal matrix is obtained using compressed sensing algorithm.Specifically, the element of first derivative matrix such as formula（6) shown in.
Multiply the first matrix for the transposed matrix right side of the use fast Fourier algorithm redundant dictionary in said one or multiple embodiments, can be first by the first matrix-expand into N-dimensional matrix, then N-dimensional matrix is entered Row inverse fast Fourier transform, and carry out fast Fourier displacement.
And multiply the computing of the second matrix for the use fast Fourier algorithm redundant dictionary right side in said one or multiple embodiments, inverse fast Fourier transform first can be carried out to the second matrix, obtain the 3rd matrix, again by the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of the second matrix, and by the inverse value of the odd term in preceding M in the 3rd matrix, it is defined as the odd term of operation result.
Certainly, there are the blunt algorithms for recovering sparse signal matrix of ^ in actual applications more, the application is not specifically limited, wherein, as long as the transposition right side for redundant dictionary occur multiplies the first matrix or the redundant dictionary right side multiplies the second matrix, above-mentioned FFT fast algorithms can be just used, processing speed is improved.
The method that various change mode and instantiation in electronic equipment in previous embodiment are equally applicable to the estimation angle of arrival of the present embodiment, pass through the foregoing detailed description to electronic equipment, those skilled in the art are clear that the implementation for the method that angle of arrival is estimated in the present embodiment, so it is succinct for specification, it will not be described in detail herein.
Technical scheme in above-mentioned the embodiment of the present application, at least imitates bright or advantage with following technology：Due to the electronic equipment in said one or multiple embodiments, applied in orthogonal FDM communication system, the electronic equipment includes：Processor, for obtaining the aerial array measurement result of Μ array element and based on aerial array measurement result and redundant dictionary, estimate the angle of arrival of Κ wireless signal, wherein, the redundant dictionary used herein is some discrete Fourier transform matrix, that is there is the discrete Fourier transform factor in the redundant dictionary, so, just can be with a part for the complete Discrete Fourier transform in multiplexed quadrature frequency division multiplexing communication system, extra memory space need not be consumed to store redundant dictionary, so, efficiently solve the technical problem that the larger memory space of redundant dictionary needs is stored present in prior art, save system resource.
It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program product.Therefore, the form of the embodiment in terms of the present invention can use complete hardware embodiment, complete software embodiment or combine software and hardware.Moreover, the present invention can be used (includes but is not limited to magnetic disk storage, CD-ROM, optical memory etc. in one or more computer-usable storage mediums for wherein including computer usable program code）The form of the computer program product of upper implementation. The present invention is with reference to method according to embodiments of the present invention, equipment（System）And the flow chart and/or block diagram of computer program product are described.It should be understood that can by the flow in each flow and/or square frame and flow chart and/or block diagram in computer program instructions implementation process figure and/or block diagram and/or square frame combination.These computer program instructions can be provided to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices to produce a machine so that produce the device for being used for realizing the function of specifying in one flow of flow chart or multiple flows and/or one square frame of block diagram or multiple square frames by the instruction of the computing device of computer or other programmable data processing devices.
These computer program instructions may be alternatively stored in the computer-readable memory that computer or other programmable data processing devices can be guided to work in a specific way, so that the instruction being stored in the computer-readable memory, which is produced, includes the manufacture of command device, the command device realizes the function of being specified in one flow of flow chart or multiple flows and/or one square frame of block diagram or multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices, so that series of operation steps is performed on computer or other programmable devices to produce computer implemented processing, so that the instruction performed on computer or other programmable devices provides the step of being used to realize the function of specifying in one flow of flow chart or multiple flows and/or one square frame of block diagram or multiple square frames.
Obviously, those skilled in the art can carry out various changes and modification to the present invention without departing from the spirit and scope of the present invention.So, if these modifications and variations of the present invention belong within the scope of the claims in the present invention and its equivalent technologies, then the present invention is also intended to comprising including these changes and modification.

Claims (1)

  1. Claim
    1st, a kind of electronic equipment, applied in orthogonal FDM communication system, it is characterised in that including：Processor, the aerial array measurement result for obtaining M array element；Based on the aerial array measurement result and redundant dictionary, the angle of arrival of K wireless signal is estimated, wherein, the redundant dictionary is some discrete Fourier transform matrix, wherein, M and K are positive integer.
    2nd, electronic equipment as claimed in claim 1, it is characterised in that when the M array element includes the array element with least two dimensions, the processor, specifically for：The aerial array measurement result of the array element of each dimension in the M array element is obtained respectively；For the array element of each dimension, based on the aerial array measurement result and the redundant dictionary, K angle of arrival is estimated；K angle of arrival of the array element based on each dimension, estimates the K angle of arrival of the M array element.
    3rd, electronic equipment as claimed in claim 1 or 2, it is characterised in that the redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and the redundant dictionary is constituted by N number of direction vector.
    4th, electronic equipment as claimed in claim 3, it is characterised in that the direction vector is determined according to below equation：
    Ά θ ) = [1 ej "(1"2i ) e(M- 1) (1- 2i/N)] T wherein, be the angle of grid described in i-th, ^=arccos (l-2i/N), i=0 ..., N-l, M N, N are 2 integral number power.
    5th, the electronic equipment as described in any one of claim 1 ~ 4, it is characterised in that the processor, specifically for：Based on the aerial array measurement result and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the first matrix described in the computing of the second matrix and second matrix for the matrix related to the aerial array measurement result；Based on the sparse signal matrix, the angle of arrival is estimated.
    6th, electronic equipment as claimed in claim 5, it is characterised in that the processor, is specifically also used In：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
    7th, electronic equipment as claimed in claim 6, it is characterised in that the element of the first derivative matrix is determined according to below equation：
    Wherein, jj is the line number of the first derivative matrix, is the first derivative matrix column number, jj=0, l ..., M-l, ii=0, l ..., N-l
    8th, the electronic equipment as described in any one of claim 5 ~ 7, it is characterised in that the processor, specifically for：By first matrix-expand into N-dimensional matrix；Inverse fast Fourier transform is carried out to the N-dimensional matrix, and carries out fast Fourier displacement.
    9th, the electronic equipment as described in any one of claim 5 ~ 7, it is characterised in that the processor, specifically for：Inverse fast Fourier transform is carried out to second matrix, the 3rd matrix is obtained；By the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding M in the 3rd matrix, it is defined as the odd term of the operation result.
    10th, the electronic equipment as described in any one of claim 1 ~ 9, it is characterised in that the electronic equipment also includes：Aerial array, for being carried out receiving the signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number
    11st, the electronic equipment as described in any one of claim 1 ~ 9, it is characterised in that the electronic equipment, in addition to：Receiver, processor is sent to for receiving the aerial array measurement result, and by the aerial array measurement result.
    12nd, the electronic equipment as described in claim 1 ~ 11, it is characterised in that the electronic equipment is specially terminal or base station.
    13rd, a kind of device for estimating angle of arrival, applied in orthogonal FDM communication system, its feature exists In, including：
    Aerial array measurement result receiving unit, the aerial array measurement result for obtaining M array element；Angle-of- arrival estimation unit, for based on the aerial array measurement result and redundant dictionary, estimating the angle of arrival of K wireless signal, wherein, the redundant dictionary is some discrete Fourier transform matrix, M with
    K is positive integer.
    14th, device as claimed in claim 13, it is characterised in that when the M array element includes the array element with least two dimensions, the angle-of- arrival estimation unit is specifically included：
    Aerial array measurement result inputs subelement, the aerial array measurement result for obtaining the array element of each dimension in the M array element respectively；
    Single dimension angle of arrival computation subunit, for the array element for each dimension, based on the aerial array measurement result and the redundant dictionary, estimates K angle of arrival；
    Various dimensions angle of arrival computation subunit, for K angle of arrival of the array element based on each dimension, calculates the K angle of arrival of the M array element.
    15th, the device as described in claim 13 or 14, it is characterised in that the redundant dictionary is obtained in the following manner：The scope of trigonometric function value is evenly dividing into N number of grid；The direction vector of each grid in N number of grid is calculated, and the redundant dictionary is constituted by N number of direction vector.
    16th, device as claimed in claim 15, it is characterised in that the direction vector is determined according to below equation：
    ^ = [1 e i^(l-2i ) eJ^ (M-l) (l-2i/ N)-| T is the angle of grid described in i-th wherein, 6 i=arccos (l -2i/N), and i=0 ..., N -1, M N, N are 2 integral number power.
    17th, the device as described in any one of claim 13 ~ 16, it is characterised in that the angle-of- arrival estimation unit, is specifically included：
    Sparse signal matrix computations subelement, for based on the aerial array measurement result and the redundant dictionary, sparse signal matrix to be obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Using the transposition right side of fast Fourier algorithm computing redundancy dictionary multiply the first matrix computing and/ Or it is the matrix related to the aerial array measurement result that the redundant dictionary right side, which multiplies the first matrix described in the computing of the second matrix and second matrix,；
    Subelement is estimated, for based on the sparse signal matrix, estimating the angle of arrival.
    18th, device as claimed in claim 17, it is characterised in that the sparse signal matrix computations subelement, specifically for：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
    19th, device as claimed in claim 18, it is characterised in that determine that element is in the first derivative matrix according to below equation：
    B(jj jj) = j 2;Γ( ϋ — l) c(jj- ι χ ι -2/Ν) wherein, jj be the first derivative matrix row subscript, ii be the first derivative matrix column subscript, jj=0, l ..., M-l ,=0,1, Ν -1.
    20th, the device as described in any one of claim 17 ~ 19, it is characterised in that the sparse signal matrix computations subelement, is specifically included：
    Subelement is extended, for first matrix-expand to be tieed up into matrix into Ν；
    Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to Ν dimension matrixes, and carries out Fast Fourier Transform (FFT) displacement.
    21st, the device as described in any one of claim 17 ~ 19, it is characterised in that the sparse signal matrix computations subelement, is specifically included：
    Inverse fast Fourier transform subelement, for carrying out inverse fast Fourier transform to second matrix, obtains the 3rd matrix；
    Determination subelement, for by the even item in preceding Μ in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding Μ in the 3rd matrix, it is defined as the odd term of the operation result.
    22nd, the device as described in any one of claim 13 ~ 21, it is characterised in that the aerial array measurement result receiving unit, specifically for：Carried out receiving the signal measurement acquisition antenna array according to measurement configuration Row measurement result, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
    23rd, the device as described in any one of claim 13 ~ 21, it is characterised in that the bright receiving unit of the aerial array measurement knot, specifically for：Receive the aerial array measurement sent by opposite equip. and tie bright.
    24th, a kind of method for estimating angle of arrival, applied in orthogonal FDM communication system, it is characterised in that including：
    The aerial array measurement knot for obtaining M array element is bright；
    Based on the aerial array measurement result and redundant dictionary, the angle of arrival of K wireless signal is estimated, wherein, the redundant dictionary is some discrete Fourier transform matrix, and M and K are positive integer.
    25th, method as claimed in claim 24, it is characterised in that when the M array element includes the array element with least two dimensions, the aerial array measurement result of described M array element of acquisition is specially：The aerial array measurement result of the array element of each dimension in the M array element is obtained respectively；
    It is described to be based on the aerial array measurement result and redundant dictionary, estimate the angle of arrival of K wireless signal, specifically include：
    For the array element of each dimension, based on the aerial array measurement result and the redundant dictionary, K angle of arrival is estimated；
    K angle of arrival of the array element based on each dimension, calculates the K angle of arrival of the M array element.
    26th, the method as described in claim 24 or 25, it is characterised in that the redundant dictionary is obtained in the following manner：
    The scope of trigonometric function value is evenly dividing into N number of grid；
    Calculate the direction vector of each grid in N number of grid, and from N number of direction Xiang Liang Group into the redundant dictionary.
    27th, method as claimed in claim 26, it is characterised in that the direction vector is determined according to below equation：
    α Ί Λ _ Π XI— 2i / N) ^
    Wherein, it is the angle of grid described in i-th, ^=arccos (l-2i/N), i=0 ..., N-l, M N, N are 2 integral number power.
    28th, the method as described in any one of claim 24 ~ 29, it is characterised in that described to be based on the aerial array measurement result and redundant dictionary, estimates the angle of arrival of K wireless signal, specifically includes：
    Based on the aerial array measurement result and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm, wherein, at least include in the compressed sensing algorithm：Use that the transposition right side of fast Fourier algorithm computing redundancy dictionary multiplies the computing of the first matrix and/or the redundant dictionary right side multiplies the first matrix described in the computing of the second matrix and second matrix for the matrix related to the aerial array measurement result；
    Based on the sparse signal matrix, the angle of arrival is estimated.
    29th, method as claimed in claim 28, it is characterised in that described to be based on the aerial array measurement result and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm, is specially：Based on the first derivative matrix of the aerial array measurement result, the redundant dictionary and the redundant dictionary, sparse signal matrix is obtained using the compressed sensing algorithm.
    30th, method as claimed in claim 29, it is characterised in that the element of the first derivative matrix is determined according to below equation：
    Wherein, jj is the line number of the first derivative matrix, and ii is the first derivative matrix column number, jj=0, l ..., M-l, ii=0, l ..., N-l
    31st, the method as described in any one of claim 28 ~ 30, it is characterised in that the first matrix is multiplied using the transposed matrix right side of fast Fourier algorithm redundant dictionary, specifically included：
    By first matrix-expand into N-dimensional matrix；
    Inverse fast Fourier transform is carried out to the N-dimensional matrix, and carries out fast Fourier displacement.
    32nd, the method as described in any one of claim 28 ~ 30, it is characterised in that multiply the computing of the second matrix using the fast Fourier algorithm redundant dictionary right side, specifically include：
    Inverse fast Fourier transform is carried out to second matrix, the 3rd matrix is obtained； By the even item in preceding M in the 3rd matrix, it is defined as the even item that the redundant dictionary right side multiplies the operation result of second matrix, and by the inverse value of the odd term in preceding M in the 3rd matrix, it is defined as the odd term of the operation result.
    33rd, the method as described in any one of claim 24 ~ 32, it is characterised in that the acquisition array measurement result, be specially：Carried out receiving the signal measurement acquisition aerial array measurement result according to measurement configuration, wherein, the measurement configuration at least includes the combination of one or more of degree of rarefication, snapshot number and each snapshot bit number.
    34th, the method as described in any one of claim 24 ~ 32, it is characterised in that the acquisition array measurement result, be specially：Receive the aerial array measurement result sent by opposite equip..
CN201380002828.4A 2013-12-26 2013-12-26 A kind of method, apparatus and electronic equipment for estimating angle of arrival Expired - Fee Related CN104937856B (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2013/090581 WO2015096099A1 (en) 2013-12-26 2013-12-26 Method and apparatus for estimating angle of arrival, and electronic device

Publications (2)

Publication Number Publication Date
CN104937856A true CN104937856A (en) 2015-09-23
CN104937856B CN104937856B (en) 2018-06-05

Family

ID=53477371

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201380002828.4A Expired - Fee Related CN104937856B (en) 2013-12-26 2013-12-26 A kind of method, apparatus and electronic equipment for estimating angle of arrival

Country Status (2)

Country Link
CN (1) CN104937856B (en)
WO (1) WO2015096099A1 (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111551902A (en) * 2020-06-02 2020-08-18 电子科技大学 Method for recovering acquired signals when FMCW radar antenna is defective based on compressed sensing technology
CN112740058A (en) * 2019-12-26 2021-04-30 华为技术有限公司 Method and device for measuring angle of arrival
CN113253194A (en) * 2021-04-21 2021-08-13 中国电子科技集团公司第二十九研究所 Broadband arrival angle and polarization combined measurement method based on sparse representation
CN116450993A (en) * 2023-04-24 2023-07-18 哈尔滨工业大学 Multi-measurement vector satellite data processing method, electronic equipment and storage medium

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
IL266212B2 (en) * 2016-10-28 2023-10-01 Univ Macquarie Direction of arrival estimation
US11630518B2 (en) * 2018-03-19 2023-04-18 King Abdullah University Of Science And Technology Ultrasound based air-writing system and method
CN108957390B (en) * 2018-07-09 2022-03-18 东南大学 Arrival angle estimation method based on sparse Bayesian theory in presence of mutual coupling
CN109039403B (en) * 2018-09-14 2020-08-18 中国人民解放军空军预警学院 Downlink channel estimation method based on redundant dictionary in large-scale MIMO system
CN111431575B (en) * 2020-03-04 2022-02-11 哈尔滨工程大学 Incoming wave direction sparse reconstruction method based on conventional beam forming

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101232316A (en) * 2008-01-17 2008-07-30 华南理工大学 Method for estimating wave arriving based on mobile WIMAX
CN101860387A (en) * 2009-04-09 2010-10-13 中兴通讯股份有限公司 DOA estimation method and system thereof
US20110181471A1 (en) * 2002-09-27 2011-07-28 Panasonic Corporation Adaptive antenna radio communication device
CN102608565A (en) * 2012-03-23 2012-07-25 哈尔滨工程大学 Direction-of-arrival estimation method on basis of uniform circular array

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100749451B1 (en) * 2005-12-02 2007-08-14 한국전자통신연구원 Method and apparatus for beam forming of smart antenna in mobile communication base station using OFDM
CN103454615A (en) * 2013-03-01 2013-12-18 西安电子科技大学 Steady blind signal parameter estimation method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110181471A1 (en) * 2002-09-27 2011-07-28 Panasonic Corporation Adaptive antenna radio communication device
CN101232316A (en) * 2008-01-17 2008-07-30 华南理工大学 Method for estimating wave arriving based on mobile WIMAX
CN101860387A (en) * 2009-04-09 2010-10-13 中兴通讯股份有限公司 DOA estimation method and system thereof
CN102608565A (en) * 2012-03-23 2012-07-25 哈尔滨工程大学 Direction-of-arrival estimation method on basis of uniform circular array

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112740058A (en) * 2019-12-26 2021-04-30 华为技术有限公司 Method and device for measuring angle of arrival
CN112740058B (en) * 2019-12-26 2022-04-22 华为技术有限公司 Method and device for measuring angle of arrival
CN111551902A (en) * 2020-06-02 2020-08-18 电子科技大学 Method for recovering acquired signals when FMCW radar antenna is defective based on compressed sensing technology
CN111551902B (en) * 2020-06-02 2022-11-01 电子科技大学 Method for recovering acquired signals when FMCW radar antenna is defective based on compressed sensing technology
CN113253194A (en) * 2021-04-21 2021-08-13 中国电子科技集团公司第二十九研究所 Broadband arrival angle and polarization combined measurement method based on sparse representation
CN113253194B (en) * 2021-04-21 2022-07-08 中国电子科技集团公司第二十九研究所 Broadband arrival angle and polarization combined measurement method based on sparse representation
CN116450993A (en) * 2023-04-24 2023-07-18 哈尔滨工业大学 Multi-measurement vector satellite data processing method, electronic equipment and storage medium
CN116450993B (en) * 2023-04-24 2023-12-12 哈尔滨工业大学 Multi-measurement vector satellite data processing method, electronic equipment and storage medium

Also Published As

Publication number Publication date
WO2015096099A1 (en) 2015-07-02
CN104937856B (en) 2018-06-05

Similar Documents

Publication Publication Date Title
CN104937856A (en) Method and apparatus for estimating angle of arrival, and electronic device
CN102419432B (en) Round array phase interferometer two-dimensional (2D) direction-finding method based on virtual base line
CN107589399B (en) Estimation method of direction of arrival of co-prime array based on singular value decomposition of multi-sampling virtual signal
CN108141256B (en) Phase adjustment method and device of antenna array
CN103475397A (en) Three-dimensional wave beam forming method, communication station and mobile station
CN102299775A (en) Method and device for selecting precoding matrix
CN110430147B (en) Channel tracking method for FDD system
CN107121662A (en) Single passive location method based on spatial domain rarefaction representation
CN113922848A (en) Signal sending method, channel estimation method, sending end equipment and receiving end equipment
CN104333407A (en) Acquiring method and device of channel information
CN114785391A (en) RIS and beam forming method and device based on RIS
CN109039403A (en) Downlink channel estimation method based on redundant dictionary in extensive mimo system
CN102394686B (en) Device and method for estimating angle of high-precision array antenna receiving system
CN102208930B (en) Rapid signal subspace estimation method
Chen et al. Low-complexity joint 2-D DOA and TOA estimation for multipath OFDM signals
US20120213115A1 (en) Channel estimation method and device in a multi-antenna system
CN108614234B (en) Direction-of-arrival estimation method based on multi-sampling snapshot co-prime array received signal fast Fourier inverse transformation
CA2948539C (en) Calibration device
CN103152093B (en) The acquisition methods and device of two dimensional arrival angles
CN101860387B (en) DOA estimation method and system thereof
CN114553649B (en) Signal frequency deviation calibration method, device, electronic equipment and storage medium
CN101499816A (en) Incoming wave arrival angle estimating method and apparatus
CN108282205B (en) Method and device for selecting space division user
CN106877979A (en) A kind of low complex degree detection method that single notation is modulated based on generalized space
EP3565199B1 (en) Channel estimation method and device

Legal Events

Date Code Title Description
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20180605

Termination date: 20181226

CF01 Termination of patent right due to non-payment of annual fee