Space-time-range three-dimensional joint adaptive detection method for MIMO radar based on LCMV criterion

Abstract

The present invention relates to a MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion. The present invention first disassembles the received MIMO radar array element-pulse-range three-dimensional echo data into multiple "space-time-waveform" three-dimensional data matrices according to the waveform length, and then converts each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing; then, a joint adaptive filter is constructed based on the LCMV criterion, and the two-dimensional data matrix is ​​subjected to joint adaptive filtering processing; finally, the result of the joint adaptive filtering processing output is used as the detection statistic to implement the threshold detection. Compared with the traditional cascade processing method of "matched filtering + beamforming + Doppler domain detection", the present invention can suppress the side lobes generated by strong targets, avoid the shielding of adjacent weak targets, suppress clutter, reduce the demand for data, and has a faster computing speed, so it has the advantage of being easy to implement in engineering.

Description

Technical Field

[0001] The present invention belongs to the field of radar signal processing, and in particular relates to MIMO radar signal processing and target detection technology. Background Art

[0002] The working environment faced by radar is becoming increasingly complex. The complex background clutter and target characteristics make radar target detection more and more difficult, which puts higher requirements on radar signal processing and target detection technology. MIMO radar, as a new system radar with waveform diversity characteristics, has higher degrees of freedom and spatial resolution, and can distinguish targets and clutter backgrounds in higher dimensions, thereby improving target detection performance. However, the traditional cascade processing method of MIMO radar has problems such as difficulty in effectively separating waveforms, high data requirements, large algorithm calculation volume, and poor detection performance under low signal-to-noise ratio backgrounds. Therefore, it is urgent to develop signal processing and target detection methods that match MIMO radar.

[0003] In order to solve the above problems, the present invention provides a MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion. Summary of the invention

[0004] The purpose of the present invention is to provide a MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion for the problems that the traditional cascade processing method of MIMO radar has the problems of difficult effective waveform separation, high data demand, large algorithm calculation amount, and poor detection performance under low signal-to-noise ratio background. The technical problems to be solved include:

[0005] (1) The problem of effective separation of waveforms;

[0006] (2) Sidelobe suppression problem;

[0007] (3) Clutter suppression problem;

[0008] (4) Reduce the demand for data;

[0009] (5) Reduce the amount of calculation and improve the running speed.

[0010] The MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion of the present invention is characterized by comprising the following technical measures:

[0011] Step 1: Receive the element-pulse-range (corresponding to space-time-range) three-dimensional echo data of the MIMO radar, and decompose the space-time-range three-dimensional echo data into multiple "space-time-waveform" three-dimensional data matrices according to the waveform length, and then convert each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing;

[0012] Step 2: construct a joint adaptive filter based on the LCMV criterion, and perform joint adaptive filtering on the two-dimensional data matrix;

[0013] Step 3: Use the output of the joint adaptive filtering process as the detection statistic to implement over-threshold detection.

[0014] Compared with the traditional cascade processing method (i.e., "matched filtering + beamforming + Doppler domain detection" processing), the MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion described in the present invention has the following beneficial effects:

[0015] (1) This method solves the problem in the traditional cascade processing method that strong echo points are prone to produce high three-dimensional side lobes, thus avoiding the obstruction of adjacent weak targets.

[0016] (2) This method adopts a three-dimensional joint processing method based on the LCMV criterion, which has a fast processing speed while suppressing clutter, and is easy to implement in engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion. DETAILED DESCRIPTION

[0018] The present invention will be described in further detail below in conjunction with the accompanying drawings. Figure 1 The specific implementation of the present invention is divided into the following steps:

[0019] (1) receiving the element-pulse-range (corresponding to space-time-range) three-dimensional echo data of the MIMO radar, and decomposing the space-time-range three-dimensional echo data into multiple "space-time-waveform" three-dimensional data matrices according to the waveform length, and then converting each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing;

[0020] (2) constructing a joint adaptive filter based on the LCMV criterion and performing joint adaptive filtering on the two-dimensional data matrix;

[0021] (3) Using the output of the joint adaptive filtering process as the detection statistic, implement threshold detection.

[0022] The following is a detailed description of the above steps:

[0023] (1) Receive the three-dimensional echo data of element-pulse-range (corresponding to space-time-range) of the MIMO radar, and decompose the three-dimensional echo data of space-time-range into multiple three-dimensional data matrices of "space-time-waveform" according to the waveform length, and then convert each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing; the specific operations of this step are as follows:

[0024] ① Receive the three-dimensional echo data of element-pulse-distance (corresponding to space-time-distance respectively) of the MIMO radar, recorded as in, represents complex data, N represents the number of MIMO radar receiving array elements, L represents the number of pulses, Q represents the number of range units, and Q ≥ 2P-1, P represents the length of the phase encoding waveform; The (n,l,q)th element of n,l,q , n=0,…,N-1,l=0,…,L-1,q=1,…,Q;the three-dimensional echo data can be It is presented as Q two-dimensional data matrices of size N×L as follows,

[0025]

[0026]

[0027] ② 3D echo data According to the phase-encoded waveform length P, we disassemble it along the distance dimension to obtain Q-P+1 N×L×P dimensional "space-time-waveform" three-dimensional data matrices, recorded as r=1,2,…,Q-P+1; the three-dimensional data matrix corresponding to the r-th distance unit It is shown as the following P two-dimensional data matrices of size N×L, where p=1,2,…,P,

[0028]

[0029]

[0030] ③ The "space-time-waveform" three-dimensional data matrix corresponding to the r-th distance unit Convert it into a two-dimensional data matrix of size NL×P as follows, denoted as Y r , r=1,2,…,Q-P+1,

[0031]

[0032] in, Represents a two-dimensional matrix Stacked up by columns, they form a one-dimensional column vector of size NL×1; the superscript T represents the transpose operator.

[0033] (2) constructing a joint adaptive filter based on the LCMV criterion, and performing joint adaptive filtering on the two-dimensional data matrix; the specific operations of this step are as follows:

[0034] ① Calculate the covariance matrix R(r), where the superscript H represents the conjugate transpose operator.

[0035] R(r)=Y r (Y r ) H

[0036] ② Based on the angular resolution, the angular range covered by the MIMO radar is discretized and recorded as θ i , i = 1, ..., I; for each angle resolution unit θ i , and obtain the steering vector a(θ i ),

[0037]

[0038] Among them, d t represents the distance between MIMO radar transmitting array elements, λ represents the wavelength of MIMO radar, and M represents the number of MIMO radar transmitting array elements.

[0039] ③ Using the covariance matrix R(r) and the emission steering vector a(θ i ) and the MIMO radar transmit waveform matrix S, calculate the weight vector w(r,θ i ),

[0040] w(r,θ i )=R(r) -1 S T a(θ i )(a(θ i ) H S * R(r) -1 S T a(θ i )) -1

[0041] ④Use the weight vector w(r,θ of the adaptive filter i ) for the input data Y r Perform filtering to obtain the joint adaptive filtering output result, which is recorded as z(r,θ i ),

[0042]

[0043] ⑤Traverse all angle resolution units θ iand all distance units r, repeat steps ② to ④ to obtain the corresponding parameter group (r, θ i ) joint adaptive filtering output result z(r,θ i ).

[0044] (3) For each parameter group (r, θ i ), and use joint adaptive filtering to output the result z(r,θ i ) is used as the detection statistic, and the threshold detection is performed as follows:

[0045]

[0046] Among them, Λ is the detection threshold, which is determined by the false alarm probability.

Claims

1. A MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion, characterized in that: The following steps are involved: S1, receiving the three-dimensional echo data of element-pulse-range of the MIMO radar, where the element-pulse-range corresponds to space-time-range respectively, and decomposing the three-dimensional echo data of space-time-range into multiple three-dimensional data matrices of "space-time-waveform" according to the waveform length, and then converting each three-dimensional data matrix into a two-dimensional data matrix as the input of the joint adaptive processing; S2, constructing a joint adaptive filter based on the LCMV criterion, and performing joint adaptive filtering on the two-dimensional data matrix; S3. Use the output result of the joint adaptive filtering process as a detection statistic to implement over-threshold detection.

2. The LCMV criterion-based MIMO radar space-time-range three-dimensional joint adaptive detection method according to claim 1, characterized in that: The step S1 specifically includes: S11, receiving the element-pulse-range three-dimensional echo data of the MIMO radar, recorded as in, represents complex data, N represents the number of MIMO radar receiving array elements, L represents the number of pulses, Q represents the number of range units, and Q ≥ 2P-1, P represents the length of the phase encoding waveform; The (n,l,q)th element of n,l,q , n=0,…,N-1,l=0,…,L-1,q=1,…,Q;the three-dimensional echo data can be It is presented as Q two-dimensional data matrices of size N×L as follows, S12, the three-dimensional echo data According to the phase-encoded waveform length P, we disassemble it along the distance dimension to obtain Q-P+1 N×L×P dimensional "space-time-waveform" three-dimensional data matrices, recorded as The three-dimensional data matrix corresponding to the r-th distance unit It is shown as the following P two-dimensional data matrices of size N×L, where p=1,2,…,P, S13, the "space-time-waveform" three-dimensional data matrix corresponding to the r-th distance unit Convert it into a two-dimensional data matrix of size NL×P as follows, denoted as Y r , r=1,2,…,Q-P+1, in, Represents a two-dimensional matrix Stacked up by columns, they form a one-dimensional column vector of size NL×1; the superscript T represents the transpose operator.

3. The MIMO radar space-time-range three-dimensional joint adaptive detection method based on the LCMV criterion according to claim 1 is characterized in that: The step S2 specifically includes: S21. Calculate the covariance matrix R(r), R(r)=Y r (Y r ) H , where the superscript H represents the conjugate transpose operator; S22. Based on the angular resolution, the angular range covered by the MIMO radar is discretized and recorded as θ i , i = 1, ..., I; for each angle resolution unit θ i , and obtain the steering vector a(θ i ), Among them, d t represents the MIMO radar transmitting array element spacing, λ represents the wavelength of the MIMO radar, and M is the number of MIMO radar transmitting array elements; S23, using the covariance matrix R(r), the transmission steering vector a(θ i ) and the MIMO radar transmit waveform matrix S, calculate the weight vector w(r,θ i ), w(r,θ i )=R(r) -1 S T a(θ i )(a(θ i ) H S * R(r) -1 S T a(θ i )) -1 ; S24, using the weight vector w(r,θ i ) for the input data Y r Perform filtering to obtain the joint adaptive filtering output result, which is recorded as z(r,θ i ), S25, traverse all angle resolution units θ i and all distance units r, repeating steps S22 to S24 to obtain the corresponding parameter group (r, θ i ) joint adaptive filtering output z(r,θ i ).

4. The LCMV criterion-based MIMO radar space-time-range three-dimensional joint adaptive detection method according to claim 3, characterized in that: The step S3 specifically includes: For each parameter group (r,θ i ), and use joint adaptive filtering to output the result z(r,θ i ) is used as the detection statistic, and the threshold detection is performed as follows: Among them, Λ is the detection threshold, which is determined by the false alarm probability.

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