CN114609605B - Subarray echo data matching angle measurement method based on maximum likelihood - Google Patents

Subarray echo data matching angle measurement method based on maximum likelihood Download PDF

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CN114609605B
CN114609605B CN202210503914.4A CN202210503914A CN114609605B CN 114609605 B CN114609605 B CN 114609605B CN 202210503914 A CN202210503914 A CN 202210503914A CN 114609605 B CN114609605 B CN 114609605B
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马亮
周伟光
袁暾
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Nanjing Tianlang Defense Technology Co ltd
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    • G—PHYSICS
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Abstract

The invention discloses a subarray echo data matching angle measurement method based on maximum likelihood, which utilizes radar subarray echo sampling data to obtain a covariance inverse matrix between channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted echo data; and finally, matching the target information with the guide vector to finally obtain the angle information of the target. In order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.

Description

Subarray echo data matching angle measurement method based on maximum likelihood
Technical Field
The invention relates to the technical field of wireless communication, in particular to a subarray echo data matching angle measuring method based on maximum likelihood.
Background
The array signal processing means that a group of sensors capable of sensing spatial propagation signals and transmitting in a certain form are distributed on different positions in space according to a certain sequence to form a sensor array, and the sensor array receives the spatial propagation signals, so that discrete data of spatial incident signals are obtained.
The purpose of array signal processing is to make the beam former enhance the interesting or needed useful signal and simultaneously suppress the undesired interference and noise components by performing specific processing on the incident signal received by the antenna array, so as to effectively obtain the characteristic information of the needed signal and perform performance analysis.
The adaptive beam forming is one of important contents for array signal processing, can automatically measure clutter and interference characteristics of a working environment, analyze the action mode of main interference, automatically adopt a corresponding anti-interference scheme, and can adaptively adjust working parameters along with the change of the environment to achieve certain optimal performance.
However, in phased array radars, particularly multi-function phased array radars, the array typically contains hundreds to thousands of array elements. If array element-level digital beam forming is carried out on the large array, each receiving channel comprises an amplifying device, a mixing device and an analog-to-digital conversion device, so that the system overhead is greatly increased, and meanwhile, the consistency among the channels is poor due to the excessive number of the channels. Thus, for large arrays, a subarray structure is often used, which reduces hardware cost and complexity of engineering implementation. The subarray level self-adaptive processing has the advantages of small calculated amount, high convergence speed, less hardware equipment of a receiving system and the like. Therefore, the adaptive digital beamforming research at the sub-array level is one of the key technologies of the phased array radar.
The angle measurement is a basic task of a radar system, and the radar system undertakes a guidance or precise tracking task, and the angle measurement and tracking of a target are required to be realized with higher precision. At present, the relevant literature of the angle measurement function aiming at the subarray echo data is few, and the research in the field is still in a weak link. Therefore, it is necessary to pay attention to and enhance the goniometric study on the subarray echo data.
Disclosure of Invention
In view of the problems in the prior art, the present invention aims to provide a subarray echo data matching angle measurement method based on maximum likelihood, which is implemented by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.
The technical scheme adopted by the invention is as follows:
a subarray echo data matching angle measurement method based on maximum likelihood is disclosed, wherein radar subarray echo sampling data is utilized to obtain covariance inverse matrix between channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted echo data; and finally, traversing the target information and the guide vector to obtain a correlation coefficient, and taking an angle corresponding to the maximum value of the correlation coefficient as an angle measurement result of the target.
Further, the method takes the following subarray echo data as a calculation basis:
setting the subarray echo data as
Figure 324071DEST_PATH_IMAGE001
Dimension of
Figure 155760DEST_PATH_IMAGE002
I.e. the square number of the sub-array level is
Figure 660691DEST_PATH_IMAGE003
The number of pitches is
Figure 411478DEST_PATH_IMAGE004
。
Further, the method comprises:
calculating covariance matrix of subarray echo data
Figure 1859DEST_PATH_IMAGE005
And inverse matrix
Figure 902819DEST_PATH_IMAGE006
：
Figure 685093DEST_PATH_IMAGE007
Figure 685410DEST_PATH_IMAGE008
；
Wherein,
Figure 825404DEST_PATH_IMAGE009
in order to select the sub-array echo data samples,
Figure 389110DEST_PATH_IMAGE010
which represents the transpose of the conjugate,Iis a unit array.
Further, the weighting the sub-array echo data by the inverse matrix is as follows:
Figure 603053DEST_PATH_IMAGE011
Figure 102168DEST_PATH_IMAGE012
the weighted echo data.
Further, the extracting target information of the weighted echo data is: set a target at
Figure 89978DEST_PATH_IMAGE013
A distance door, then
Figure 4844DEST_PATH_IMAGE014
Dimension of
Figure 401190DEST_PATH_IMAGE015
，
Figure 930261DEST_PATH_IMAGE016
And weighting the sub-array echo data for the matrix to extract target information.
Further, the method comprises:
roughly measuring the angle of the target;
1) setting a search range of the angle rough measurement,
direction dimension
Figure 716951DEST_PATH_IMAGE017
，
Figure 232246DEST_PATH_IMAGE018
For the azimuth dimension, the maximum value of the search range, the pitch dimension
Figure 171514DEST_PATH_IMAGE019
，
Figure 622218DEST_PATH_IMAGE020
Searching the maximum value of the range for the pitch dimension;
Figure 224101DEST_PATH_IMAGE021
searching step length for the angle rough measurement;
2) calculating a steering vector corresponding to the angle rough measurement search angle
Figure 730037DEST_PATH_IMAGE022
Wherein
Figure 710763DEST_PATH_IMAGE023
whereinjIs a unit of an imaginary number, and is,
Figure 722581DEST_PATH_IMAGE024
is the carrier frequency, and is,
Figure 980736DEST_PATH_IMAGE025
and
Figure 978779DEST_PATH_IMAGE026
search range for traversing rough measurement angle
Figure 204224DEST_PATH_IMAGE027
And
Figure 308315DEST_PATH_IMAGE028
the corresponding angle of the angle is set to be,
Figure 494577DEST_PATH_IMAGE029
and
Figure 420944DEST_PATH_IMAGE030
is an index of the distance between the two objects,
Figure 923732DEST_PATH_IMAGE031
is shown as
Figure 152719DEST_PATH_IMAGE032
Reference array elements of the individual sub-arrays are
Figure 872283DEST_PATH_IMAGE033
The distance in the axial direction relative to the reference array elements of the original array,
Figure 602341DEST_PATH_IMAGE030
is relative to
Figure 146586DEST_PATH_IMAGE034
The distance in the axial direction, d is the distance between the azimuth dimension and the pitch dimension array element;
3) calculating the correlation coefficient between the guide vector of the angle rough measurement and the target information, and defining the correlation coefficient as
Figure 359524DEST_PATH_IMAGE035
Figure 645012DEST_PATH_IMAGE036
Wherein,
Figure 522969DEST_PATH_IMAGE037
weighting the subarray echo data for the inverse matrix and extracting target information;
4) taking the angle corresponding to the maximum value of the correlation coefficient of the angle rough measurement as a rough measurement angle result
Figure 498884DEST_PATH_IMAGE038
，
Wherein,
Figure 459887DEST_PATH_IMAGE039
is the angle rough measurement result, namely the angle rough measurement result
Figure 576879DEST_PATH_IMAGE035
The angle corresponding to the medium maximum value.
Further enter oneThe method comprises the following steps: carrying out fine measurement on the angle of the target; the result of the rough measurement is used as the basis of the azimuth dimension searching range and the pitch dimension searching range, and the angle is used for accurately measuring the searching step length
Figure 648740DEST_PATH_IMAGE040
And performing traversal calculation as a search step length, and taking an angle corresponding to the maximum value of the angle precision measurement correlation coefficient as a precision angle measurement result.
Further, setting the angle precision measurement search range as
Angle fine measurement to obtain coarse measurement result
Figure 246206DEST_PATH_IMAGE041
On the basis of the search range of the orientation dimension
Figure 722317DEST_PATH_IMAGE042
Pitch dimension search range:
Figure 982397DEST_PATH_IMAGE043
；
Figure 513742DEST_PATH_IMAGE040
and searching step length for angle precision measurement.
The beneficial results are that:
the invention provides a subarray echo data matching angle measurement method based on maximum likelihood, which provides technical support for the subarray echo data angle measurement field and improves the weak current situation of the current adaptive beam forming angle measurement field; meanwhile, in order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement.
Drawings
FIG. 1 is a schematic diagram of subarray division;
FIG. 2 is a screenshot of an interference sample selection interface;
FIG. 3 is a screenshot of a result interface after weighting of the subarray echo data by the inverse matrix;
FIG. 4 is a schematic diagram of the result of coarse angle measurement of the subarray echo data;
FIG. 5 is a schematic diagram of the accurate angle measurement result of the subarray echo data;
FIG. 6 is a graph showing the variation of the sub-array SNR with the angle measurement result of the sub-array echo data in the embodiment;
fig. 7 shows antenna patterns after the sub-array echo data are synthesized into beams.
Detailed Description
The technical solution of the present invention will be explained with reference to the accompanying drawings. The described embodiments and their description are intended to be illustrative of the invention and should not be construed as restrictive.
The embodiment discloses a subarray echo data matching angle measurement method based on maximum likelihood, radar subarray level echo sampling data are utilized, covariance inverse matrixes among channels are obtained, information of a target is extracted from weighted echo data and matched with a guide vector, and finally target angle information is obtained. In order to avoid the problem of large calculation amount of engineering realization, the method is realized by two steps of rough angle measurement and fine angle measurement. And a foundation is laid for subsequent trace point processing and target tracking through accurate angle measurement. The method specifically comprises the following steps:
suppose the subarray echo data is
Figure 152665DEST_PATH_IMAGE001
Dimension of
Figure 189891DEST_PATH_IMAGE002
I.e. the square number of the sub-array level is
Figure 360103DEST_PATH_IMAGE003
The number of pitches is
Figure 383554DEST_PATH_IMAGE004
；
Step 1: selecting a subarray echo data sample with the length of the sample beingL
Figure 188568DEST_PATH_IMAGE044
Wherein
Figure 396695DEST_PATH_IMAGE045
dimension of
Figure 241154DEST_PATH_IMAGE046
。
Step 2: calculating covariance matrix of subarray echo data
Figure 615766DEST_PATH_IMAGE005
And inverse matrix
Figure 353915DEST_PATH_IMAGE047
Figure 405048DEST_PATH_IMAGE048
Figure 986071DEST_PATH_IMAGE049
And 3, step 3: weighting the subarray echo data with an inverse matrix
Figure 475958DEST_PATH_IMAGE050
And 4, step 4: extracting target information
Suppose the target is at
Figure 6296DEST_PATH_IMAGE013
A distance gate.
Figure 447904DEST_PATH_IMAGE014
Dimension of
Figure 126010DEST_PATH_IMAGE051
。
And 5: coarse angle measurement of subarray echo data
Setting angular rough measurement search range
Orientation dimension
Figure 91692DEST_PATH_IMAGE052
，
Figure 929067DEST_PATH_IMAGE053
For the azimuth dimension, the maximum value of the search range, the pitch dimension
Figure 649898DEST_PATH_IMAGE019
，
Figure 752984DEST_PATH_IMAGE054
Searching the maximum value of the range for the pitch dimension;
Figure 476351DEST_PATH_IMAGE021
step length is searched for angle rough measurement and can be set to be 0.2 degrees;
calculating a steering vector corresponding to the search angle
Figure 778020DEST_PATH_IMAGE055
Figure 607435DEST_PATH_IMAGE056
Wherein,
Figure 650347DEST_PATH_IMAGE024
is the carrier frequency, and is,
Figure 20148DEST_PATH_IMAGE025
and
Figure 379585DEST_PATH_IMAGE057
needs to traverse the angle rough measurement search range
Figure 56599DEST_PATH_IMAGE027
And
Figure 868697DEST_PATH_IMAGE058
the corresponding angle is set to be the same as the angle,
Figure 307769DEST_PATH_IMAGE059
and
Figure 770980DEST_PATH_IMAGE030
is a distance index, the former being expressed as
Figure 879882DEST_PATH_IMAGE032
Reference array elements of the individual sub-arrays are
Figure 507172DEST_PATH_IMAGE033
Distance in the axial direction with respect to the reference array element of the original array, the latter with respect to the reference array element
Figure 907192DEST_PATH_IMAGE034
And d is the distance between the azimuth dimension and the pitch dimension array element.
Calculating correlation coefficient between guide vector of angle coarse measurement and target information
Figure 444483DEST_PATH_IMAGE035
Figure 848920DEST_PATH_IMAGE060
Taking the angle corresponding to the maximum value of the phase relation number as the angle measurement result
Figure 884878DEST_PATH_IMAGE038
Step 6: accurate angle measurement of subarray echo data
Setting the search range of angle precision measurement
Azimuth dimension search range:
Figure 541118DEST_PATH_IMAGE061
pitch dimension search range:
Figure 791971DEST_PATH_IMAGE062
；
Figure 55724DEST_PATH_IMAGE040
the angle searching step length during accurate angle measurement can be set to be 0.01 degree;
calculating a steering vector corresponding to the search angle
Figure 267394DEST_PATH_IMAGE022
Figure 773330DEST_PATH_IMAGE063
WhereinjIs the unit of an imaginary number,
Figure 878690DEST_PATH_IMAGE025
and
Figure 562612DEST_PATH_IMAGE026
need to traverse the precision angle search range
Figure 746731DEST_PATH_IMAGE027
And
Figure 807091DEST_PATH_IMAGE028
roughly measuring other parameters of the corresponding angle at the same angle, wherein d is the spacing between the azimuth dimension and the pitch dimension array element;
calculating correlation coefficient between guide vector and target information
Figure 766957DEST_PATH_IMAGE064
Taking the angle corresponding to the maximum value of the phase relation number as the final angle measurement result
Figure 74310DEST_PATH_IMAGE065
。
The specific embodiment is as follows:
the azimuth is 32 array elements, the pitching is 64 array elements, and the azimuth pitching interval is half wavelength; the azimuth and elevation (8 × 16) array elements are combined into 1 sub-array, and as shown in fig. 1, the number of sub-arrays is 4 × 4= 16. 2 pressed disturbances, wherein the disturbance azimuth and the pitching angle are (2.2, -1.8) ° (2.5, 1.7) ° (1-2.8), and the disturbance ratio is 30-40 dB, as shown in Table 1; the target is at the 468 th range gate and the subarray is divided as shown in FIG. 1.
TABLE 12 interference parameter information
Number of interferences Azimuth (°) Angle of pitch (°)
1 2.2 -1.8
2 -2.5 1.7
The results of the sub-array echo data angle measurement embodiment are embodied according to the basic operation steps:
step 1: a subarray echo data sample is selected, with a sample length of 64, see fig. 2.
Step 2: computing an inverse matrix
Figure 322889DEST_PATH_IMAGE006
。
And step 3: the subarray echo data is weighted with an inverse matrix and the echo results are shown in figure 3.
And 4, step 4: echo data of 16 subarrays are extracted from the echoes and are marked as tar _ info. Specific values are shown in Table 2.
TABLE 2 tar _ info values
Subarray channel number echo data
1 7.57-0.08i 9 5.72-5.36i
2 9.04+3.32i 10 12.28-1.48i
3 5.62+7.36i 11 9.84+1.79i
4 4.73+9.27i 12 6.22+5.45i
5 8.78-1.50i 13 6.90-7.27i
6 10.95+2.53i 14 5.21-1.80i
7 8.50+5.93i 15 8.12+1.26i
8 6.59+6.22i 16 9.84+2.62i
And 5: setting the azimuth dimension (-2.5: 0.2: 2.5) DEG and the pitch dimension (-2: 0.2: 2) DEG of an angle search range by coarsely measuring the angle of the subarray echo data; calculating steering vectors corresponding to the search angles, e.g., -2.5, -2) DEG for the first azimuth and pitch angles
Figure 983677DEST_PATH_IMAGE066
The dimensions are shown in Table 3.
TABLE 3
Figure 486465DEST_PATH_IMAGE067
Numerical value
Figure 715452DEST_PATH_IMAGE067
Numerical value
Figure 435015DEST_PATH_IMAGE068
Numerical value
1 0.54+0.07i 9 -0.32-0.99i
2 -0.22-1.13i 10 -1.06+0.68i
3 -0.25+0.92i 11 1.24+0.08i
4 0.60+0.22i 12 -0.07-0.79i
5 0.26-0.96i 13 -0.58+0.20i
6 -1.25+0.06i 14 0.06+0.91i
7 0.81+0.85i 15 0.53-0.77i
8 0.57-0.72i 16 -0.45-0.12i
Calculating correlation coefficient between steering vector corresponding to azimuth and pitch angle (-2.5, -2) and target information
Figure 899495DEST_PATH_IMAGE035
Figure 709319DEST_PATH_IMAGE069
After traversing all the azimuth angles and the pitch angles in the rough angle measurement, carrying out normalization processing, and taking
Figure 922257DEST_PATH_IMAGE035
The angle corresponding to the maximum is the raw angle measurement result, see fig. 4.
The results of the rough angle measurement were (0.5, -0.6) °.
Step 6: accurate angle measurement of subarray echo data
Setting azimuth dimension (0.3:0.01:0.7) degree and pitch dimension (-0.8:0.01: minus 0.4) degree of an angle search range;
at the moment, the corresponding angle range of the guide vector is a precise angle measurement range, the other steps are the same as the rough angle measurement, and finally the angle is obtained
Figure 676586DEST_PATH_IMAGE070
The angle corresponding to the maximum value is the accurate angle measurement result, as shown in fig. 5, the accurate angle measurement result is (0.47, -0.55) °, and the angle measurement result is consistent with the target real result (0.48, -0.55).
Fig. 6 shows that the interference is 40dB, and the angle measurement result changes with the sub-array SNR. It can be seen that when the target SNR is low, the error of the angle measurement result is large, and as the SNR increases, the angle measurement result continuously tends to and finally converges to the true value.
The technical solution of the present invention is not limited to the limitations of the above-mentioned specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the scope of the present invention.

Claims (3)

1. A subarray echo data matching angle measurement method based on maximum likelihood is characterized in that subarray echo sampling data are utilized to obtain covariance inverse matrixes among channels; weighting the subarray echo data by using an inverse matrix, and extracting target information from the weighted subarray echo data; finally, traversing the target information and the guide vector to obtain a correlation coefficient, and taking an angle corresponding to the maximum value of the correlation coefficient as a target angle measurement result;
the method takes the following subarray echo data as a calculation basis:
setting the subarray echo data as
Figure DEST_PATH_IMAGE001
Dimension of
Figure DEST_PATH_IMAGE002
I.e. the square number of the sub-array level is
Figure DEST_PATH_IMAGE003
The number of pitches is
Figure DEST_PATH_IMAGE004
；
The method comprises the following steps: calculating covariance matrix of subarray echo data
Figure DEST_PATH_IMAGE005
And inverse covariance matrix
Figure DEST_PATH_IMAGE006
：
Figure DEST_PATH_IMAGE007
Figure DEST_PATH_IMAGE008
；
Wherein,
Figure DEST_PATH_IMAGE009
in order to select a subarray echo data sample, the length of the sample is L,
Figure DEST_PATH_IMAGE010
which represents the transpose of the conjugate,Iis a unit array;
the weighting of the sub-array echo data by the inverse matrix is as follows:
Figure DEST_PATH_IMAGE011
Figure DEST_PATH_IMAGE012
weighted subarray echo data;
the extraction of target information from the weighted subarray echo data is as follows: set a target at
Figure DEST_PATH_IMAGE013
A distance door, then
Figure DEST_PATH_IMAGE014
Dimension of
Figure DEST_PATH_IMAGE015
，
Figure DEST_PATH_IMAGE016
Weighting the subarray echo data for the inverse matrix and extracting target information;
the method comprises the following steps:
roughly measuring the angle of the target;
setting a search range of the angle rough measurement,
direction dimension
Figure DEST_PATH_IMAGE017
，
Figure DEST_PATH_IMAGE018
For the azimuth dimension, the maximum value of the search range, the pitch dimension
Figure DEST_PATH_IMAGE019
，
Figure DEST_PATH_IMAGE020
Searching the maximum value of the range for the pitch dimension;
Figure DEST_PATH_IMAGE021
searching step length for the angle rough measurement;
calculating a steering vector corresponding to the angle rough measurement search angle
Figure DEST_PATH_IMAGE022
Wherein
Figure DEST_PATH_IMAGE023
wherein,jis the unit of an imaginary number,
Figure DEST_PATH_IMAGE024
is the carrier frequency, and is,
Figure DEST_PATH_IMAGE025
and
Figure DEST_PATH_IMAGE026
search range for traversing rough measurement angle
Figure DEST_PATH_IMAGE027
And
Figure DEST_PATH_IMAGE028
the corresponding angle of the angle is set to be,
Figure DEST_PATH_IMAGE029
and
Figure DEST_PATH_IMAGE030
is an index of the distance between the two objects,
Figure DEST_PATH_IMAGE031
is shown as
Figure DEST_PATH_IMAGE032
Reference array elements of the individual sub-arrays are
Figure DEST_PATH_IMAGE033
The distance in the axial direction relative to the reference array elements of the original array,
Figure DEST_PATH_IMAGE034
is relative to
Figure DEST_PATH_IMAGE035
The distance in the axial direction, d is the distance between the azimuth dimension and the pitch dimension array element;
calculating the correlation coefficient between the guiding vector of the angle rough measurement and the target information, and defining as
Figure DEST_PATH_IMAGE036
Figure DEST_PATH_IMAGE037
Wherein,
Figure DEST_PATH_IMAGE038
weighting the subarray echo data for the inverse matrix and extracting target information;
taking the angle corresponding to the maximum value of the correlation coefficient of the angle rough measurement as a rough measurement angle result
Figure DEST_PATH_IMAGE039
，
Wherein,
Figure DEST_PATH_IMAGE040
is the angle rough measurement result, namely the angle rough measurement result
Figure DEST_PATH_IMAGE041
The angle corresponding to the medium maximum value.
2. The maximum likelihood-based subarray echo data matching goniometry method of claim 1, wherein the method comprises: carrying out fine measurement on the angle of the target; the result of the rough measurement is used as the basis of the azimuth dimension searching range and the pitch dimension searching range, and the angle is used for accurately measuring the searching step length
Figure DEST_PATH_IMAGE042
And performing traversal calculation as a search step length, and taking an angle corresponding to the maximum value of the angle precision measurement correlation coefficient as a precision angle measurement result.
3. The maximum likelihood-based subarray echo data matching angle measurement method of claim 2, wherein the angle precision measurement search range is set to
Angle fine measurement to obtain coarse measurement result
Figure DEST_PATH_IMAGE043
On the basis of the search range of the orientation dimension
Figure DEST_PATH_IMAGE044
Pitch dimension search range:
Figure DEST_PATH_IMAGE045
；
Figure DEST_PATH_IMAGE046
and searching step length for angle precision measurement.
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