CN108614240B - Adaptive space-time transmission weighting generator applied to centralized MIMO radar - Google Patents

Adaptive space-time transmission weighting generator applied to centralized MIMO radar Download PDF

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CN108614240B
CN108614240B CN201810317581.XA CN201810317581A CN108614240B CN 108614240 B CN108614240 B CN 108614240B CN 201810317581 A CN201810317581 A CN 201810317581A CN 108614240 B CN108614240 B CN 108614240B
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于泽
王树森
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Beihang University
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    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

The invention discloses a self-adaptive space-time emission weighting generator applied to a centralized MIMO radar, which is arranged between a waveform generator and an emission component of a space-time self-adaptive processing radar. The space-time emission weight value generated by the adaptive space-time emission weight generator is acted on the adaptive weight generator of the space-time adaptive processing radar. The adaptive space-time transmitting weight generator takes a space-time transmitting weight and a space-time receiving weight as decision variables, takes output noise power as an objective function, takes constant output signal power as a constraint condition I and constant input signal power as a constraint condition II, and models a minimized objective function under the constraint condition as a constraint optimization problem. The space-time transmit-receive weight combining method provided by the invention brings the space-time transmit weight into a decision variable of an optimization problem, can adjust the space-time transmit weight according to a dynamic environment, enables a centralized MIMO radar to be in a working state with higher performance, improves clutter suppression performance, has strong universality and has the capacity of updating the space-time weight on line in real time.

Description

Adaptive space-time transmission weighting generator applied to centralized MIMO radar
Technical Field
The present invention relates to the field of radar signal processing technology, and more particularly, to an adaptive space-time transmit weight generator for a centralized MIMO radar. And the adaptive space-time transmitting weight generator is used for adaptively generating space-time transmitting weights of the centralized MIMO radar.
Background
The paper "MIMO radar detection performance and system configuration research" published by jun et al in 2009 indicates that Multiple-Input Multiple-Output (MIMO) radar is a new concept radar, and its basic idea is: a plurality of radar transmitters and a plurality of receivers are adopted in the system, each transmitter transmits different waveforms, each receiver simultaneously receives a plurality of waveforms, and then fusion processing is carried out on the received signals, so that the detection and parameter estimation performance of the system is improved. MIMO radars can be classified into two types according to the antenna structure: centralized MIMO radar and distributed MIMO radar, the present invention is directed to centralized MIMO radar.
Compared with the traditional phased array radar, the superior system performance of the centralized MIMO radar benefits from the fact that each transmitter can transmit different waveforms. In order to improve the detection performance of the target of the centralized MIMO radar in different working environments, researchers in the field have conducted intensive research work on the design of a transmitted waveform, and the existing documents can be divided into two categories: orthogonal waveform design and beamforming-based transmit waveform design. The waveform designed based on the beam forming improves the detection performance of the system to a certain extent, but the waveforms transmitted by the transmitters are partially coherent, and the transmission dimensional space degree of freedom of the centralized MIMO radar is not fully utilized. The conventional orthogonal waveform design method only considers the orthogonality among different transmitting signals, but the space-time weight of the transmitting signals is constant, and the method cannot be optimally adapted to the dynamic environment faced by the radar. By designing a reasonable shape, applying wave-absorbing materials and other methods, Radar Cross Section (RCS) (hereinafter collectively referred to as weak targets) of strategic tactical targets can be greatly reduced, such as stealth airplanes, Radar moving target detection faces a relatively strong background clutter environment, and particularly for Radar systems with small system freedom, the performance of the two algorithms is limited. An article, "cognitive radar MIMO-STAP based on joint transmit-receive weight optimization", published by zhanxin et al in 2012 preliminarily explores an optimization design method of space-time transmit-receive weights, but does not consider the influence of the transmit weights on received signals, and limits practical application occasions.
To date, no space-time transmit-receive weight value joint design method universally applied to the centralized MIMO radar has been proposed at home and abroad.
Disclosure of Invention
The invention relates to a self-adaptive space-time transmitting weight generator applied to a centralized MIMO radar, which solves the optimal joint design problem of a space-time transmitting weight and a space-time receiving weight by utilizing an optimization theory and a method, takes the space-time transmitting weight and the space-time receiving weight as decision variables, takes output noise power as a target function, takes constant output signal power as a constraint condition I and constant input signal power as a constraint condition II, and models a minimized target function under the constraint condition as a constraint optimization problem. And under the constraint that the power of the input signal is kept constant and the power of the output signal is kept constant, minimizing the power of the output noise shows that the radar clutter suppression performance is strongest. And the space-time transmitting weight and the space-time receiving weight are simultaneously used as decision variables to be limited to a first constraint condition, so that the influence of the space-time transmitting weight on a received signal is fully considered. Considering whether the information of the actual detection observation scene of the radar is received or not, the optimization problem is decomposed into two sub-optimization problems: and solving the optimal space-time receiving weight when the space-time transmitting weight is known, and solving the optimal space-time transmitting weight when the space-time receiving weight is known. And respectively solving the optimal solutions of the two sub-optimization problems, namely the optimal space-time receiving weight and the optimal space-time transmitting weight by utilizing a Lagrange multiplier method. The invention applies self-adapting to generate space-time transmitting or receiving weight, and adjusts the space-time transmitting weight and the space-time receiving weight in real time to continuously self-adapt to the target and the dynamic environment (including clutter and noise), thereby improving the clutter suppression performance. The centralized MIMO radar weighted by the space-time transmitting weight and the space-time receiving weight designed by the invention can effectively inhibit strong clutter and improve the output signal-to-noise ratio.
The invention designs an adaptive space-time transmitting weight generator applied to a centralized MIMO radar, which is arranged between a waveform generator and a transmitting component of a space-time adaptive processing radar. The space-time emission weight value generated by the adaptive space-time emission weight generator is acted on the adaptive weight generator of the space-time adaptive processing radar. The adaptive space-time transmit weight generator receives target information output by the automatic detector.
The invention relates to a method for adaptively generating space-time transmitting weight by using a centralized MIMO radar with an adaptive space-time transmitting weight generator, which is characterized by comprising the following steps:
the method comprises the following steps: constructing a covariance matrix of noise characteristics for the radar working in the passive mode;
step two: constructing a space-time emission weight value for the radar working in the active mode;
step three: training by adopting a maximum likelihood estimation method to obtain clutter characteristics, namely a clutter covariance matrix;
step four: solving a sub-optimization problem of the optimal space-time receiving weight when the space-time transmitting weight is known by utilizing a Lagrange multiplier method;
step five: processing azimuth-Doppler data of the unit to be detected by utilizing a space-time receiving weight to obtain target information;
if the target is detected in the fifth step of the invention, the distance-direction-Doppler information of the target is obtained, and the output space-time transmitting weight is obtained through the sixth step by utilizing the covariance matrix of the clutter characteristics represented in the third step, the space-time receiving weight in the fourth step and the distance-direction-Doppler information of the target in the fifth step.
And if the target is not detected in the fifth step, assigning the space-time transmission weight of the previous frame of radar to the space-time transmission weight of the current frame, and then returning to the fourth step.
Step six: and solving the sub-optimization problem of the optimal space-time transmission weight when the space-time receiving weight is known by utilizing a Lagrange multiplier method.
The centralized MIMO radar with the self-adaptive space-time transmitting weighting generator has the advantages that:
(1) the space-time transmitting weight is brought into a decision variable of an optimization problem, and can be adjusted according to a dynamic environment, so that the centralized MIMO radar is in a working state with higher performance, and clutter suppression performance is improved.
(2) The centralized MIMO radar of the invention sets two constraint conditions, so as to comprehensively consider the influence of the space-time emission weight on the received signal, and is closer to the actual working state of the radar and has strong universality.
(3) The space-time transmitting weight and the space-time receiving weight adopted by the centralized MIMO radar are both analytic solutions, and the system complexity is low.
(4) The centralized MIMO radar adopts a closed-loop feedback optimization mode and has the potential of updating the space-time weight value on line in real time.
Drawings
Fig. 1 is a block diagram of a conventional space-time adaptive processing radar.
Fig. 2 is a block diagram of a centralized MIMO radar with an adaptive space-time transmit weight generator of the present invention.
Fig. 2A is a flow chart of the steps performed by the adaptive space-time transmit weight generator of the present invention.
Figure 3 is a graph of the improvement factor of the present invention as a function of normalized doppler frequency.
Fig. 4 is a graph of the output signal-to-noise ratio of the present invention as a function of frame number.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Fig. 1 is a block diagram of a conventional space-time adaptive processing radar, which is derived from page 126 of a radar manual (third edition) published by electronic industry press 2010, and the conventional radar processing method has no space-time transmission weight adaptive generator and is weak in radar clutter suppression capability. Fig. 2 is a structural block diagram of a space-time adaptive processing radar to which the adaptive space-time transmit weighting generator designed by the present invention is added, and a link of feeding back sensing information of a transmission system by a receiving system is added, so that adaptive generation of a space-time transmit weight is realized, and clutter suppression capability of the MIMO radar is improved. The transmitter and receiver of fig. 2 illustrate duplex operation, and in practice, a split transceiver mode of operation may be used. Fig. 2A is a flowchart of the execution steps of the adaptive space-time transmit weighting generator of the present invention, which estimates a covariance matrix representing noise and clutter characteristics in a dynamic environment by using range-azimuth-doppler data received by a radar, adaptively generates a space-time receive weight, estimates range-azimuth-doppler information of a target by using the filtered range-azimuth-doppler data, and adaptively generates a space-time transmit weight by combining the space-time receive weight, so that the radar operates in a closed-loop optimized operating state to achieve more excellent clutter suppression performance.
In the present invention, fig. 2 is a diagram of an adaptive space-time transmit weight generator installed between a waveform generator and a transmit component of a conventional space-time adaptive processing radar.
Referring to fig. 2 and fig. 2A, the process of adaptively generating the space-time transmit weight by the adaptive space-time transmit weight generator applied to the centralized MIMO radar according to the present invention includes the following steps:
the method comprises the following steps: constructing a covariance matrix of noise characteristics for the radar working in the passive mode;
the radar is set to work in a passive mode, and the acquired distance-direction-Doppler data is only noise information and is recorded as a data matrix N. The dimension of the data matrix N is ghk × L, where g denotes the number of transmitters, h denotes the number of receivers, k denotes the number of time samples, and L denotes the number of range cells. In the present invention, the covariance matrix representing the noise characteristics is estimated using range-azimuth-Doppler data, denoted
Figure GDA0003014917660000041
Wherein N isHRepresenting the conjugate transpose of the data matrix N.
In the present invention, noise information is used to construct
Figure GDA0003014917660000042
The clutter characteristic involved in the space-time transmission weight is satisfied.
Step two: constructing a space-time emission weight value for the radar working in the active mode;
setting a radar working in an active mode, wherein the radar irradiates any observation area, and setting a space-time emission weight of a transmission signal emitted by a transmitter, which is marked as Wt, if so;
Figure GDA0003014917660000043
A1representing the weight of the first space-time transmitting channel; a. the2Representing the weight of the second space-time transmitting channel; a. thegkRepresenting the weight of the final space-time transmitting channel; g represents the number of transmitters; k represents the number of time samples.
In the invention, when the radar works in the active mode to irradiate any observation area for the first time, the space-time emission weight of the emission signal is recorded as Wt0(ii) a Since the irradiation of the observation region is performed for the first time, Wt0The middle space-time transmission weight is assigned as 1, and then the weight is present;
Figure GDA0003014917660000051
step three: training by adopting a maximum likelihood estimation method to obtain clutter characteristics, namely a clutter covariance matrix;
when a transmitting signal emitted by a transmitter is reflected by a ground scene, the transmitting signal of the normally working radar is collected by a radar digital receiver as distance-azimuth-Doppler data which is recorded as a data matrix Z. For convenience of explanation, the range-azimuth-doppler data is expressed as a vector combination matrix form of different range cell azimuth-doppler data, and is denoted as Zghk×L；
Zghk×L＝[z1,z2,…,zL]ghk×L (3)
z1Azimuth-doppler data representing the 1 st range cell; z is a radical of2Azimuth-doppler data representing the 2 nd range cell; z is a radical ofLAzimuth-doppler data indicating that the number of range cells is equal to the number L of range cells; g represents the number of transmitters; h represents the number of receivers; k represents the number of time samples; l represents the number of distance units.
Suppose the distance unit set to be detected is BlTo be detectedAny distance unit to be detected is marked as l0Zl0 denotes the l-th0Azimuth-doppler data for each range cell; distance units trained as maximum likelihood estimation are called training units, and a plurality of training units form a training set and are marked as BlTraining(ii) a Any training unit is marked as l; l is in the range of {1,2, …, L }, L0E {1,2, …, L } and
Figure GDA0003014917660000052
zlthe azimuth-doppler data of the l-th range cell is shown. In the invention, a covariance matrix of the unit to be detected representing the clutter characteristics is estimated by using the data of the training unit and is marked as Cc;
Figure GDA0003014917660000053
Figure GDA0003014917660000054
denotes zlThe conjugate transpose of (1); cn represents the covariance matrix of the noise features.
Step four: solving a sub-optimization problem of the optimal space-time receiving weight when the space-time transmitting weight is known by utilizing a Lagrange multiplier method;
in the invention, in order to obtain the relative azimuth information between the target and the transmitter related to the digital beam former of fig. 2, a space transmission guide vector is constructed and is marked as Sst;
Figure GDA0003014917660000061
Figure GDA0003014917660000062
represents an imaginary unit; f. ofstRepresenting normalized spatial transmit frequencies; g represents the number of transmitters;
Figure GDA0003014917660000063
representing base natural logarithm e, with j2 π fstIs a logarithmic function value of the variable;
Figure GDA0003014917660000064
representing base natural logarithm e, with j2 π fst(g-1) Is a logarithmic function value of the variable.
In the invention, in order to obtain the relative azimuth information between the target and the receiver related to the digital beam former of fig. 2, a space receiving guide vector is constructed and is marked as Ssr;
Figure GDA0003014917660000065
fsrrepresenting normalized spatial receive frequency(ii) a h represents the number of receivers;
Figure GDA0003014917660000066
representing base natural logarithm e, with j2 π fsrIs a logarithmic function value of the variable;
Figure GDA0003014917660000067
representing base natural logarithm e, with j2 π fsr (h-1)Is a logarithmic function value of the variable.
In the invention, in order to obtain the relative Doppler information between the target and the radar related to the Doppler filter bank in FIG. 2, a time-oriented vector is constructed and recorded as Sd;
Figure GDA0003014917660000068
fdrepresents a normalized doppler frequency; k represents the number of time samples;
Figure GDA0003014917660000069
representing base natural logarithm e, with j2 π fdIs a logarithmic function value of the variable;
Figure GDA00030149176600000610
representing base natural logarithm e, with j2 π fd (k-1)Is a logarithmic function value of the variable.
In the invention, in order to represent the transmitting signals which are not weighted by the space-time transmitting weight in the traditional space-time self-adaptive radar, a space-time transmitting guide vector is constructed and recorded as
Figure GDA00030149176600000611
Wherein
Figure GDA00030149176600000612
Representing the Kronecker product. In order to fully consider the influence of the space-time transmission weight value on a received signal, a space-time receiving guide vector weighted by the space-time transmission weight value is constructed and recorded as a space-time receiving guide vector
Figure GDA00030149176600000613
Wherein |, indicates a Hadamard product. In the invention, the covariance matrix of the distance unit to be detected representing the clutter and noise characteristics is estimated by using the data of the training unit and is marked as Cq.
Figure GDA00030149176600000614
In the present invention, the space-time receive weight generated by the adaptive weight generator in fig. 2 is denoted as Wr. Solving the sub-optimization problem of solving the optimal space-time receiving weight value when the space-time transmitting weight value is known by utilizing a Lagrange multiplier method, namely taking Wr as a decision variable and WrHCqWr is an objective function, WrHSr 1 is constraint one, and constraint two constructed by signal input power at first irradiation, namely WtHAnd St is p, and p represents the amplitude of the transmission signal in the target direction, wherein p is assigned by using the target information, so that a constraint condition two is met, and the optimal space-time receiving weight Wr is obtained by minimizing the output noise power.
Figure GDA0003014917660000071
Cq-1An inverse matrix, Wr, representing CqHDenotes the conjugate transpose of Wr, WtHDenotes the conjugated transpose of Wt, SrHRepresenting the conjugate transpose of Sr.
Step five: processing azimuth-Doppler data of the unit to be detected by utilizing a space-time receiving weight to obtain target information;
in the invention, the space-time receiving weight is used for weighting and processing the azimuth-Doppler data of the unit to be detected, and the processing result is recorded as
Figure GDA0003014917660000072
Namely, traversing the normalized spatial transmit frequency and the normalized spatial receive frequency to construct the digital beamformer of FIG. 2, traversing the normalized Doppler frequency to construct the Doppler filter bank of FIG. 2, FIG. 2The auto detector will decide whether a target is detected and output target information. If the target is detected, target information is obtained, namely a space-time receiving guide vector of the target is obtained and is recorded as Tr, a corresponding space-time transmitting guide vector is recorded as Tt, a corresponding space receiving guide vector is recorded as Tsr, and the following development forms are provided:
Figure GDA0003014917660000073
τsr,11 st partition representing a spatially received director; tau issr,22 nd partitions of the space receiving director vector; tau issr,iAn ith partition representing a spatially received director vector; i represents a block identification number, and i belongs to 1,2, …, h; tau issr,hRepresenting the blocks with spatial receive steering vector index equal to the number of receivers h.
If the target is detected in the fifth step of the invention, the distance-direction-Doppler information of the target is obtained, and the output space-time transmitting weight is obtained through the sixth step by utilizing the covariance matrix of the clutter characteristics represented in the third step, the space-time receiving weight in the fourth step and the distance-direction-Doppler information of the target in the fifth step.
And if the target is not detected in the fifth step, assigning the space-time transmission weight of the previous frame of radar to the space-time transmission weight of the current frame, and then returning to the fourth step.
Step six: solving a sub-optimization problem of the optimal space-time transmitting weight when the space-time receiving weight is known by utilizing a Lagrange multiplier method;
and if the target is detected in the fifth step, updating the space-time transmission weight value according to the following mode when the radar of the current frame transmits signals.
In the present invention, the constraint-Wr is usedHSr is 1 and the objective function WrHThe CqWr displays a functional relation for expressing a decision variable space-time transmission weight Wt so as to simplify the complexity of solving the space-time transmission weight, and the space-time receiving weight Wr in the step four is expressed in a block vector form;
Figure GDA0003014917660000081
ωr1the filter coefficient representing the block number 1 is a gk × 1 dimensional matrix;
ωr2the filter coefficient representing the block number 2 is a gk × 1 dimensional matrix;
ωrithe filter coefficient representing the block number i is a gk × 1 dimensional matrix;
ωrhthe filter coefficients, which represent the number of blocks equal to the number of receivers h, are a gk x 1 dimensional matrix.
In the invention, in order to display and characterize the influence of the space-time emission weight on the clutter characteristic, a matrix is further constructed on the basis of a block vector form and is marked as F;
Figure GDA0003014917660000082
where g represents the number of transmitters, h represents the number of receivers, and k represents the number of time samples;
Figure GDA0003014917660000083
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure GDA0003014917660000084
An element of (1);
Figure GDA0003014917660000085
represents ω r1Conjugate, the superscript conjugate is a conjugate identification;
Figure GDA0003014917660000086
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure GDA0003014917660000087
An element of (1);
Figure GDA0003014917660000088
represents ω r2Conjugate, the superscript conjugate is a conjugate identification;
Figure GDA0003014917660000089
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure GDA00030149176600000810
An element of (1);
Figure GDA00030149176600000811
represents ω rhConjugate, the superscript conjugate is the conjugate identification.
In order to represent the influence of space-time transmission weight values on the clutter characteristics in a universal way, the number of any receiver is marked as i, i belongs to h, and then omega r existsi conjugateRepresents ω riConjugate, the superscript conjugate is the conjugate identification.
In the invention, an equivalent clutter covariance matrix which represents clutter characteristics and is weighted by a space-time receiving weight is constructed and is marked as C omega ═ FCcFH。
For the convenience of subsequent expression, the equivalent signal I is recorded as
Figure GDA0003014917660000091
The equivalent signal two is s2＝Ttconjugate，TtconjugateRepresenting the conjugation of Tt, converting the sub-optimization problem of solving the optimal space-time transmission weight when the space-time reception weight is known into the objective function Wr by taking Wt as a decision variableHCqWr shows that the expression is (Wt)conjugate)HCω(Wtconjugate) Will restrict the condition one WrHSr 1 indicates the expression
Figure GDA0003014917660000092
Constraint two WtHSt ═ p indicates an expression of
Figure GDA0003014917660000093
Assigning p to be
Figure GDA0003014917660000094
Figure GDA0003014917660000095
Represents OgkBy conjugation of (A) to (B), OgkRepresenting gk dimension column vector with elements equal to 1, and utilizing Lagrange multiplier method to minimize output noise power to obtain optimal space-time emission weight Wt of current frameCurrent frame。
Figure GDA0003014917660000096
Figure GDA0003014917660000097
Figure GDA0003014917660000098
D represents a linear equation set coefficient matrix for solving the Lagrange multiplier;
D11the (1,1) th element representing D;
D12the (1,2) th element representing D;
D21the (2,1) th element representing D;
D22the (2,2) th element representing D;
Figure GDA0003014917660000099
denotes s1The conjugate transpose of (1);
Figure GDA00030149176600000910
denotes s2The conjugate transpose of (c).
In the centralized MIMO radar with the adaptive space-time transmission weighting generator, which defines the first step and the second step, the space-time transmission weight value of each frame of transmission signals is executed according to the operation sequence from the third step to the sixth step. The centralized MIMO radar designed by the invention utilizes the target and dynamic environment information obtained from the previous frame to continuously adjust the space-time transmitting weight and the space-time receiving weight of the current frame so as to maximally inhibit clutter.
Example 1
Clutter suppression simulation of the centralized MIMO radar was performed under the simulation conditions of table 1.
TABLE 1 simulation parameters
Figure GDA0003014917660000101
In order to fully verify the present invention, simulation experiments were performed according to the simulation parameters listed in the above table, as shown in fig. 3 and 4.
Fig. 3 shows a simulation experiment in which the improvement factor varies with the normalized doppler frequency, the platform and the target are set to be in initial states (including distance, velocity, and the like), closed-loop updating of the space-time transmit weight and the space-time receive weight is performed according to the steps of the present invention, and the convergence speed of the present invention is analyzed. An improvement factor is introduced to characterize the performance of the centralized MIMO radar with the adaptive space-time transmission weight generator, and the improvement factor is defined as the ratio of the signal-to-noise power ratio of the output end to the input end. Comparing the difference between the results of different iteration times and the traditional processing in fig. 3, it can be easily found that the convergence speed of the invention is fast, and the processing result of the invention is obviously superior to the traditional processing result.
Fig. 4 shows a simulation experiment in which the output signal-to-noise ratio varies with the frame number, a platform and a target are set according to the simulation parameters listed in the above table, the platform and the target in the simulation move according to the simulation parameters, and the space-time transmit weight and the space-time receive weight are generated adaptively according to the steps of the invention to complete clutter suppression, as can be seen from the figure, the processing result of the method of the invention is obviously superior to the traditional processing result, when the algorithm converges, the output signal-to-noise ratio is improved by 14dB, and the convergence speed of the invention is very fast, and the invention converges into the optimal working state through 4 frames, and has the potential.

Claims (4)

1. A method for self-adaptive generation of space-time transmission weight by a self-adaptive space-time transmission weight generator applied to a centralized MIMO radar is characterized by comprising the following steps:
the method comprises the following steps: constructing a covariance matrix of noise characteristics for the radar working in the passive mode;
setting the radar to work in a passive mode, and recording the noise of the collected distance-azimuth-Doppler data as a data matrix N; the dimensionality of the data matrix N is ghk xL, wherein g represents the number of transmitters, h represents the number of receivers, k represents the number of time samples, and L represents the number of range cells; estimation of covariance matrices representing noise characteristics using range-azimuth-Doppler data, denoted
Figure FDA0003014917650000011
Wherein N isHRepresents a conjugate transpose of the data matrix N;
step two: constructing a space-time emission weight value for the radar working in the active mode;
setting a radar working in an active mode, wherein the radar irradiates any observation area, and setting a space-time emission weight of a transmission signal emitted by a transmitter, which is marked as Wt, if so;
Figure FDA0003014917650000012
A1representing the weight of the first space-time transmitting channel; a. the2Representing the weight of the second space-time transmitting channel; a. thegkRepresenting the weight of the final space-time transmitting channel; g represents the number of transmitters; k represents the number of time samples;
step three: training by adopting a maximum likelihood estimation method to obtain clutter characteristics, namely a clutter covariance matrix;
normal operationWhen a transmitting signal emitted by the transmitter is reflected by a ground scene, the transmitting signal is collected by the radar digital receiver into a data matrix of distance-azimuth-Doppler data, and the data matrix is recorded as Z; the range-azimuth-Doppler data is expressed in the form of vector combination matrix of different range unit azimuth-Doppler data, and is recorded as Zghk×L；
Zghk×L＝[z1,z2,…,zL]ghk×L (3)
z1Azimuth-doppler data representing the 1 st range cell; z is a radical of2Azimuth-doppler data representing the 2 nd range cell; z is a radical ofLAzimuth-doppler data indicating that the number of range cells is equal to the number L of range cells; g represents the number of transmitters; h represents the number of receivers; k represents the number of time samples; l represents the number of range cells;
suppose the distance unit set to be detected is BlTo be detectedAny distance unit to be detected is marked as l0，
Figure FDA0003014917650000013
Denotes the l0Azimuth-doppler data for each range cell; distance units trained as maximum likelihood estimation are called training units, and a plurality of training units form a training set and are marked as BlTraining(ii) a Any training unit is marked as l; l is in the range of {1,2, …, L }, L0E {1,2, …, L } and
Figure FDA0003014917650000021
zlazimuth-doppler data representing the l-th range cell; estimating a covariance matrix of the unit to be detected representing the clutter characteristics by using the data of the training unit, and recording the covariance matrix as Cc;
Figure FDA0003014917650000022
Figure FDA0003014917650000023
denotes zlThe conjugate transpose of (1); cn represents a covariance matrix of noise features;
step four: solving a sub-optimization problem of the optimal space-time receiving weight when the space-time transmitting weight is known by utilizing a Lagrange multiplier method;
constructing a space transmitting guide vector which is recorded as Sst according to relative azimuth information between a target and a transmitter related to the digital beam former;
Figure FDA0003014917650000024
Figure FDA0003014917650000025
represents an imaginary unit; f. ofstRepresenting normalized spatial transmit frequencies; g represents the number of transmitters;
Figure FDA0003014917650000026
representing base natural logarithm e, with j2 π fstIs a logarithmic function value of the variable;
Figure FDA0003014917650000027
representing base natural logarithm e, with j2 π fst (g-1)Is a logarithmic function value of the variable;
constructing a space receiving guide vector which is recorded as Ssr according to the relative azimuth information between the target and the receiver related by the digital beam former;
Figure FDA0003014917650000028
fsrrepresenting a normalized spatial receive frequency; h represents the number of receivers;
Figure FDA0003014917650000029
represent by natural pairsBase by the number e, j2 π fsrIs a logarithmic function value of the variable;
Figure FDA00030149176500000210
representing base natural logarithm e, with j2 π fsr (h-1)Is a logarithmic function value of the variable;
constructing a time guide vector, which is marked as Sd, according to relative Doppler information between a target and a radar related to a Doppler filter bank;
Figure FDA0003014917650000031
fdrepresents a normalized doppler frequency; k represents the number of time samples;
Figure FDA0003014917650000032
representing base natural logarithm e, with j2 π fdIs a logarithmic function value of the variable;
Figure FDA0003014917650000033
representing base natural logarithm e, with j2 π fd (k-1)Is a logarithmic function value of the variable;
in order to represent the transmitted signals which are not weighted by the space-time transmission weight in the traditional space-time self-adaptive radar, a space-time transmission guide vector is constructed and recorded as
Figure FDA0003014917650000034
Wherein
Figure FDA0003014917650000035
Represents the Kronecker product; in order to fully consider the influence of the space-time transmission weight value on a received signal, a space-time receiving guide vector weighted by the space-time transmission weight value is constructed and recorded as a space-time receiving guide vector
Figure FDA0003014917650000036
Wherein [ ] indicates a Hadamard product; training is utilized in the present inventionThe training unit data estimates a covariance matrix of the clutter and noise characteristics represented by the distance unit to be detected, and the covariance matrix is marked as Cq;
Figure FDA0003014917650000037
recording the space-time receiving weight value generated by the self-adaptive weight generator as Wr; solving the sub-optimization problem of solving the optimal space-time receiving weight value when the space-time transmitting weight value is known by utilizing a Lagrange multiplier method, namely taking Wr as a decision variable and WrHCqWr is an objective function, WrHSr 1 is constraint one, and constraint two constructed by signal input power at first irradiation, namely WtHP represents the amplitude of the signal transmitted in the target direction, wherein p is assigned by using target information, so that a constraint condition two is met, and the optimal space-time receiving weight Wr is obtained by minimizing the output noise power;
Figure FDA0003014917650000038
Cq-1an inverse matrix representing Cq; wrHRepresents the conjugate transpose of Wr; wtHRepresents the conjugate transpose of Wt; srHRepresents the conjugate transpose of Sr;
step five: processing azimuth-Doppler data of the unit to be detected by utilizing a space-time receiving weight to obtain target information;
weighting and processing the azimuth-Doppler data of the unit to be detected by utilizing the space-time receiving weight, and recording the processing result as
Figure FDA0003014917650000039
Traversing the normalized space transmitting frequency and the normalized space receiving frequency to construct a digital beam former, traversing the normalized Doppler frequency to construct a Doppler filter bank, judging whether a target is detected by an automatic detector, and outputting target information; if the target is detected, target information is obtained, namely a space-time receiving guide vector of the target is obtained,denoted as Tr, the corresponding space-time transmit steering vector is denoted as Tt, the corresponding space-time receive steering vector is denoted as Tsr, and has the following developed form:
Figure FDA0003014917650000041
τsr,11 st partition representing a spatially received director; tau issr,22 nd partitions of the space receiving director vector; tau issr,iAn ith partition representing a spatially received director vector; i represents a block identification number, and i belongs to 1,2, …, h; tau issr,hBlocks with the sequence number of the space receiving guide vector equal to the number h of the receivers are represented;
step six: solving a sub-optimization problem of the optimal space-time transmitting weight when the space-time receiving weight is known by utilizing a Lagrange multiplier method;
if the target is detected in the fifth step, updating the space-time transmitting weight value according to the following mode when the radar of the current frame transmits signals;
with a constraint of one WrHSr is 1 and the objective function WrHThe CqWr displays a functional relation for expressing a decision variable space-time transmission weight Wt so as to simplify the complexity of solving the space-time transmission weight, and the space-time receiving weight Wr in the step four is expressed in a block vector form;
Figure FDA0003014917650000042
ωr1the filter coefficient representing the block number 1 is a gk × 1 dimensional matrix; r of2The filter coefficient representing the block number 2 is a gk × 1 dimensional matrix; r ofiThe filter coefficient representing the block number i is a gk × 1 dimensional matrix; r ofhThe filter coefficients representing the number of blocks equal to the number h of receivers are a gk x 1 dimensional matrix;
in order to display and characterize the influence of the space-time emission weight on the clutter characteristic, a matrix is further constructed on the basis of a block vector form and is marked as F;
Figure FDA0003014917650000043
where g represents the number of transmitters, h represents the number of receivers, and k represents the number of time samples;
Figure FDA00030149176500000519
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure FDA00030149176500000517
An element of (1);
Figure FDA00030149176500000518
represents ω r1Conjugate, the superscript conjugate is a conjugate identification;
Figure FDA0003014917650000051
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure FDA0003014917650000052
An element of (1);
Figure FDA0003014917650000053
represents ω r2Conjugate, the superscript conjugate is a conjugate identification;
Figure FDA0003014917650000054
representing a gk × gk diagonal matrix with diagonal elements as column vectors
Figure FDA0003014917650000055
An element of (1);
Figure FDA0003014917650000056
represents ω rhConjugate, the superscript conjugate is a conjugate identification;
constructing an equivalent clutter covariance matrix representing clutter characteristics and weighted by space-time receiving weight, and recording the equivalent clutter covariance matrix as C omega ═ FCcFH；
Records an equivalent signal of
Figure FDA0003014917650000057
The equivalent signal two is s2＝Ttconjugate，TtconjugateRepresenting the conjugation of Tt, converting the sub-optimization problem of solving the optimal space-time transmission weight when the space-time reception weight is known into the objective function Wr by taking Wt as a decision variableHCqWr shows that the expression is (Wt)conjugate)HCω(Wtconjugate) Will restrict the condition one WrHSr 1 indicates the expression
Figure FDA0003014917650000058
Constraint two WtHSt ═ p indicates an expression of
Figure FDA0003014917650000059
Assigning p to be
Figure FDA00030149176500000510
Figure FDA00030149176500000511
Represents OgkBy conjugation of (A) to (B), OgkRepresenting gk dimension column vector with elements equal to 1, and utilizing Lagrange multiplier method to minimize output noise power to obtain optimal space-time emission weight Wt of current frameCurrent frame；
Figure FDA00030149176500000512
Figure FDA00030149176500000513
Figure FDA00030149176500000514
D represents a linear equation set coefficient matrix for solving the Lagrange multiplier; d11The (1,1) th element representing D; d12The (1,2) th element representing D; d21The (2,1) th element representing D; d22The (2,2) th element representing D;
Figure FDA00030149176500000515
denotes s1The conjugate transpose of (1);
Figure FDA00030149176500000516
denotes s2The conjugate transpose of (c).
2. The method of claim 1 for adaptive space-time transmit weight generation by an adaptive space-time transmit weight generator for centralized MIMO radar, wherein the method comprises: when the radar works in the active mode to irradiate any observation area for the first time, the space-time emission weight of the emission signal is recorded as Wt0(ii) a Since the irradiation of the observation region is performed for the first time, Wt0The middle space-time transmit weight is assigned to 1, and then:
Figure FDA0003014917650000061
。
3. the method of claim 1 for adaptive space-time transmit weight generation by an adaptive space-time transmit weight generator for centralized MIMO radar, wherein the method comprises: if the target is detected in the fifth step, the distance-direction-Doppler information of the target is obtained, and the output space-time transmitting weight is obtained through the sixth step by utilizing the covariance matrix of the clutter characteristics expressed in the third step, the space-time receiving weight in the fourth step and the distance-direction-Doppler information of the target in the fifth step.
4. The method of claim 1 for adaptive space-time transmit weight generation by an adaptive space-time transmit weight generator for centralized MIMO radar, wherein the method comprises: and if the target is not detected in the step five, assigning the space-time transmission weight of the previous frame of radar to the current frame of space-time transmission weight, and then returning to the step four.
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