MIMO radar target echo coherent accumulation method and target detection method

Abstract

The invention discloses an MIMO (Multiple Input Multiple Output) radar target echo coherent accumulation method, which comprises the following steps of: preprocessing radar echo signals to obtain echo time domain pulse signals of different channels; constructing an error compensation and coherent accumulation model based on the echo time domain pulse signal; performing optimization solution on the error compensation and coherent accumulation model to obtain an optimal compensation phase; and simultaneously compensating the random phase and Doppler phase shift of the echo time-domain pulse signal by using the optimal compensation phase, and adding the compensated echo time-domain pulse signals of all channels to realize echo coherent accumulation. According to the method, the random phase of the inter-channel echo and Doppler phase shift caused by target motion can be compensated at the same time, so that coherent accumulation of the target echo under a low signal-to-noise ratio is realized, and compared with non-coherent accumulation, the method has higher accumulation gain.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a MIMO radar target echo coherent accumulation method and a target detection method. Background Art

[0002] MIMO (Multiple Input Multiple Output) radar has attracted more and more attention due to its good low intercept performance. In most cases, since it is impossible to detect the target from the target echo data under a single radar pulse, it is necessary to send and receive multiple pulses for accumulation to achieve target detection.

[0003] Radar multi-pulse accumulation technology is mainly divided into two types: incoherent accumulation and coherent accumulation. Among them, incoherent accumulation discards the echo phase information. When the echo pulse envelope is aligned, the amplitude is directly accumulated by taking the absolute value. Since the phase relationship between the sampling points is not considered, the phase information of the echo is not used during accumulation. Compared with the coherent accumulation method that uses both the amplitude and phase information of the echo to achieve signal accumulation, the gain that can be obtained by incoherent accumulation is lower, especially in the case of low signal-to-noise ratio. The gain that can be obtained by incoherent accumulation may not meet the task requirements.

[0004] In engineering applications, in order to improve the low intercept performance of the radar, it is necessary to increase the bandwidth of the transmitted signal as much as possible. However, for MIMO radars that transmit orthogonal frequency division multiplexing linear frequency modulation signals, each array element transmits a linear frequency modulation signal with a different center frequency. When the bandwidth of the transmitted signal increases, the problem of frequency dispersion will occur, that is, the scattering coefficient of the target for signals with different center frequencies becomes a random complex number. In addition, due to the difference in carrier frequencies between different channels, the Doppler frequency of the echoes between channels for the same moving target and the redundant items after down-conversion are also inconsistent. These differences make it difficult to perform echo coherent accumulation, which seriously affects the target detection capability of the centralized MIMO radar. Therefore, it is of great significance to study how to achieve coherent accumulation of target echoes under the condition of phase difference between channels caused by factors such as frequency dispersion in centralized MIMO radars.

[0005] Since incoherent accumulation discards the echo phase information, frequency dispersion does not affect the effect of incoherent accumulation. The incoherent accumulation method in MIMO radar is still applicable to centralized MIMO radar with frequency dispersion problem. For example, Deng Xuzhao et al. introduced the process of incoherent processing in distributed MIMO radar system in the document "Airborne Distributed MIMO Radar Target Detection", which can also be applied to centralized MIMO radar. Coherent accumulation requires the phase of the echo pulse to remain consistent, and the existence of frequency dispersion makes the current coherent accumulation method no longer applicable.

[0006] In summary, for centralized MIMO radars that transmit orthogonal frequency division multiplexing linear frequency modulation signals, the echoes between channels cannot be directly coherently accumulated due to the random phase caused by frequency dispersion of echoes between different channels and the Doppler frequency difference of moving targets caused by different carrier frequencies between channels. The gain of incoherent accumulation often cannot meet the requirements of target detection tasks under low signal-to-noise ratio conditions. Summary of the invention

[0007] In order to solve the above problems existing in the prior art, the present invention provides a MIMO radar target echo coherent accumulation method and a target detection method. The technical problem to be solved by the present invention is achieved by the following technical solutions:

[0008] In a first aspect, the present invention proposes a MIMO radar target echo coherent accumulation method and a target detection method, comprising:

[0009] Preprocess the radar echo signal to obtain the echo time domain pulse signals of different channels;

[0010] Construct error compensation and coherence accumulation model based on echo time domain pulse signal;

[0011] The error compensation and coherent accumulation model is optimized and solved to obtain the optimal compensation phase;

[0012] The random phase and Doppler phase shift of the echo time-domain pulse signal are compensated simultaneously by using the optimal compensation phase, and the echo time-domain pulse signals of all channels are added after compensation to achieve echo coherent accumulation.

[0013] A second aspect of the present invention provides a MIMO radar target detection method, comprising:

[0014] Using the MIMO radar target echo coherent accumulation method provided by the first aspect of the present invention to coherently accumulate the target echo signal, and obtain a coherent accumulation result;

[0015] Based on the coherent accumulation results, the constant false alarm detection method is used to achieve target detection.

[0016] Beneficial effects of the present invention:

[0017] The MIMO radar target echo coherent accumulation method provided by the present invention first preprocesses the radar echo signal, then constructs an error compensation and coherent accumulation model according to the echo time domain pulse signal obtained after the preprocessing, and obtains the optimal compensation phase through optimization solution. The random phase of the echo between channels and the Doppler phase shift caused by the target motion can be compensated by using the optimal compensation phase, thereby realizing the coherent accumulation of the target echo under low signal-to-noise ratio, and having a higher accumulation gain than the incoherent accumulation.

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a MIMO radar target echo coherent accumulation method provided by an embodiment of the present invention;

[0020] Figure 2 It is a flow chart of implementing the coherent accumulation of MIMO radar target echoes by using the PSO algorithm provided by an embodiment of the present invention;

[0021] Figure 3 is a simulation result diagram of incoherent accumulation provided by an embodiment of the present invention;

[0022] Figure 4 is a simulation result of single-channel pulse compression before range migration correction provided by an embodiment of the present invention;

[0023] Figure 5 is a simulation result of single-channel pulse compression after range migration correction provided by an embodiment of the present invention;

[0024] Figure 6 This is a simulation result of coherent accumulation using the method of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] The first aspect of the present invention provides a MIMO radar target echo coherent accumulation method. Figure 1 , Figure 1 1 is a flow chart of a MIMO radar target echo coherent accumulation method provided by an embodiment of the present invention, which mainly includes the following four steps:

[0027] Step 1: Preprocess the radar echo signal to obtain the echo time domain pulse signals of different channels.

[0028] In this embodiment, the implementation of step 1 mainly includes two parts: one is to obtain the radar echo signal by modeling the radar echo; the other is to pre-process the obtained radar echo signal.

[0029] Specifically, the radar echo modeling is mainly implemented according to the following steps:

[0030] 11) Transmitted signal modeling.

[0031] Assume that the centralized MIMO radar has M transmitting array elements and N receiving array elements (generally speaking, M and N are equal), and the M array elements are arranged linearly, which can also be said that the radar has M channels. Each array element transmits a mutually orthogonal linear frequency modulation signal with a bandwidth of B. Then the transmission signal s of the mth subarray is m (t) can be expressed as:

[0032]

[0033] Where P t is the power of a single transmitting antenna, f m =f0+(m-1)B is the carrier frequency of the mth transmitted signal, B is the bandwidth of the transmitted signal, μ is the modulation frequency of the linear frequency modulation signal, T p is the pulse width, the transmitted signal vector can be expressed as s(t)=[s1(t),s2(t)…,s M (t)] T .

[0034] 12) Received signal modeling.

[0035] When the transmitted signal propagates through space and reaches the target, it can be expressed as:

[0036]

[0037] Where ξ1 is the propagation attenuation factor, τ = 2R / c is the total two-way propagation delay from each radar element to the target, R is the radial distance between the target and the radar, c is the speed of light, φ = 2πdsinθ / λ is the phase difference between the delays of two adjacent elements reaching the target relative to the reference element, d is the spacing between the radar elements, θ is the angle between the radar beam pointing and the normal to the array, and λ is the wavelength corresponding to the carrier frequency f0.

[0038] The signal after being scattered by the target can be recorded as r(t), and the expression is as follows:

[0039]

[0040] In the formula, represents the scattering coefficient of the mth channel, α m represents the magnitude of the scattering coefficient, β m Represents the phase of the scattering coefficient. Due to the existence of frequency dispersion, the amplitude and phase of RCS (Radar Cross section) are both random numbers, so the amplitude of the scattering coefficient α m and phase β m are also random numbers, f dm =2vf m / c represents the Doppler frequency of the mth transmitted signal, that is, the Doppler frequency of the mth channel, and v represents the moving speed of the target.

[0041] The scattered signal is received by the receiving array element after spatial transmission, then the signal x received by the nth receiving array element is n (t) can be expressed as:

[0042]

[0043] In the formula, ξ=ξ2ξ1 represents the propagation loss of the signal from being transmitted to being received, ξ1 represents the transmission loss of the transmitted signal from being transmitted to encountering the target, ξ2 represents the transmission loss of the transmitted signal from being scattered by the target to being received by the radar, and v n (t) represents the noise of the nth receiving array element.

[0044] Then the received signal vector can be expressed as:

[0045]

[0046] In the formula, a(θ)=[1,e -jφ ,…e -j(N-1)φ ] T is the receiving direction vector, v(t)=[v1(t),v1(t),…,v N (t)] T is the noise vector.

[0047] The received signal vector is used to represent the radar echo signal, and it is preprocessed as follows:

[0048] 1a) Form receiving beams in different directions based on radar echo signals.

[0049] Specifically, in a certain receiving direction θ b The receiving beam y formed on b (t) can be expressed as:

[0050]

[0051] In the formula, is the receiving beam pointing vector, φ b =2πdsinθ b / λ.

[0052] When the beamformer is aligned with the target, φ = φ b Substitute it into the calculation and we get:

[0053]

[0054] 1b) performing digital channelization processing on the receiving beam to separate the transmitting signal from the receiving beam and obtain the first echo signals of different channels;

[0055] Specifically, since the transmission signals are mutually orthogonal OFDM linear frequency modulation signals, each transmission signal can be separated from the echo according to the different frequency band ranges of each transmission signal. The output result of the mth channel after digital channelization is also called the first echo signal, which can be expressed as The expression is:

[0056]

[0057] In the formula, v′ m (t) is the noise of the mth channel after digital channelization.

[0058] 1c) performing equivalent transmit beamforming processing on the first echo signal to remove the phase term, thereby obtaining a second echo signal of a different channel.

[0059] Specifically, for the first echo signal shown in formula (8), the phase term e -j(m-1)φ It can be removed by equivalent transmit beamforming. After equivalent transmit beamforming, the second echo signal can be obtained. The expression is:

[0060]

[0061] In the formula, is the amplitude of the mth channel signal after equivalent transmit beamforming.

[0062] 1d) Down-converting the second echo signal to obtain a third echo signal of a different channel.

[0063] The second echo signal of the mth channel is down-converted to obtain the third echo signal The expression is:

[0064]

[0065] 1e) performing pulse compression processing on the third echo signal to obtain echo time domain pulse signals of different channels.

[0066] Specifically, consider the multi-pulse, the third echo signal of the mth channel after down-conversion The time domain expression after pulse compression is:

[0067]

[0068] In the formula, is the complex envelope of the echo signal of the mth channel after pulse compression, wm (t) is the noise after pulse compression.

[0069] The time delay τ can be written as τ(k)=2(R-vt k ) / c,t k is the slow time, assuming that there are K pulses in a coherent integration time, and the value of k is 0, 1, ..., K-1. The echo time domain pulse signal of the mth channel is expressed as:

[0070]

[0071] Where, τ0 = 2R / c, γ m (v,k)=2πf dm t k =4πvf m t k / c is the slow-time Doppler phase shift of the k-th pulse in the m-th channel, which is related to the velocity v and the slow-time independent variable t k Related, is a random phase composed of the random phase of the scattering coefficient, the down-conversion term, and the fast-time Doppler phase shift. The corresponding positions between different pulses in a channel have the same value, and the corresponding positions between different channels have different values.

[0072] Ignoring the noise, the K echo time domain pulse signals of the mth channel can be recorded as:

[0073]

[0074] At this point, the preprocessing of the radar echo signal is completed, and the echo time domain pulse signal of the same channel is obtained.

[0075] Step 2: Construct an error compensation and coherent accumulation model based on the echo time domain pulse signal.

[0076] Specifically, in this embodiment, the compensation function vector of the mth channel can be expressed as:

[0077]

[0078] In the formula, γ′ m (v,k) is the compensation phase of the slow-time Doppler phase shift of the kth pulse. k is a known variable with values ​​of 0, 1, ..., K-1. The only unknown variable is v. It is the compensation phase for the random phase of the mth channel and is also an unknown variable.

[0079] Then the error compensation and coherent accumulation model can be constructed as:

[0080]

[0081] In the formula, represents the compensation phase of the random phase of all channels, v represents the moving speed of the target, E represents the expectation, represents the compensation phase of the random phase of the mth channel, P m represents the compensation function vector of the mth channel, y m represents the echo time domain pulse signal of the mth channel, || represents the absolute value, and M represents the number of transmitting array elements, that is, the total number of channels.

[0082] When the Doppler phase shift γ m (v,k) is compensated to zero, and the phase between channels is random When compensated to the same value, all pulses can achieve coherent accumulation and optimize the function Reached maximum value.

[0083] Step 3: Optimize and solve the error compensation and coherent accumulation model to obtain the optimal compensation phase.

[0084] Optionally, as an implementation method, this embodiment can take the compensation phase of the random phase of all channels and the movement speed of the target as the dimension of a particle, and use the particle swarm optimization (PSO) algorithm to optimize and solve the error compensation and coherent accumulation model to obtain the optimal compensation phase.

[0085] For details, see Figure 2 , Figure 2 1 is a flow chart of using the PSO algorithm to implement MIMO radar target echo coherent integration and target detection according to an embodiment of the present invention; the process of optimizing and solving the error compensation and coherent accumulation model using the PSO algorithm is as follows:

[0086] a) Taking the compensation phase of the random phase of all channels and the moving speed of the target as the dimension of a particle, the parameters of the particle swarm algorithm are initialized.

[0087] Specifically, for the particle population size N, particle dimension D, number of iterations l, individual learning factor c1, social learning factor c2, inertia factor ω, and the historical optimal direction of particle i in the dth dimension in the lth iteration, The historical optimal vector of the dth dimension of the population in the lth iteration Perform initial settings.

[0088] Set the motion vector of particle i in the dth dimension in the lth iteration Set the position vector of particle i in the dth dimension in the lth iteration in is the compensation phase of the random phase of the mth channel, v is the searched velocity, and the Doppler phase shift γ′ to be compensated for the kth pulse of the mth channel can be determined based on v m (v,k).

[0089] b) Update the velocity of each particle. The update formula is:

[0090]

[0091] In the formula, and denote the d-th dimension velocity of particle i in the l+1th and lth iterations, respectively. reflects the particle's confidence in the current state, ω represents the inertia factor, represents the historical optimal fitness value of particle i in the dth dimension in the lth iteration, represents the position of particle i in the dth dimension in the lth iteration, It reflects the influence of the optimal position of individual particles on particle update, c1 represents the individual learning factor, r1 represents a random number in [0,1], represents the historical optimal fitness value of the dth dimension of the group in the lth iteration, It reflects the influence of the optimal position of the group on the particle update, c2 represents the social learning factor, and r2 represents a random number in [0,1].

[0092] c) Update the position of each particle. The update formula is:

[0093]

[0094] In the formula, and denote the position of particle i in the dth dimension in the l+1th and lth iterations respectively, represents the d-th dimension velocity of particle i in the l-th iteration.

[0095] d) Calculate the fitness value of each particle, and update the individual historical optimal fitness value, individual optimal position, group historical optimal fitness value, group optimal position and number of inertia weight iterations of each particle.

[0096] e) Repeat steps b)-d) until the end condition is met and the optimal compensation phase and optimal movement speed are obtained.

[0097] Specifically, the optimization algorithm ends with It reaches the maximum, which means that the search has obtained the optimal solution, that is, the optimal compensation phase and the optimal movement speed of the target.

[0098] Step 4: Using the optimal compensation phase, the random phase and Doppler phase shift of the echo time-domain pulse signal are simultaneously compensated, and all the compensated echo time-domain pulse signals are added together to achieve echo coherent accumulation.

[0099] In another embodiment of the present invention, before adding all the compensated echo time domain pulse signals, the method further includes:

[0100] The range migration of each pulse in each channel is calculated using the optimal motion speed, and the range migration correction is performed on the compensated signal through translation operation.

[0101] Finally, the signals of all channels after phase compensation and range migration correction are added to achieve efficient accumulation of echoes.

[0102] The MIMO radar target echo coherent accumulation method provided by the present invention first preprocesses the radar echo signal, then constructs an error compensation and coherent accumulation model according to the echo time domain pulse signal obtained after the preprocessing, and obtains the optimal compensation phase through optimization solution. The random phase of the echo between channels and the Doppler phase shift caused by the target motion can be compensated by using the optimal compensation phase, thereby realizing the coherent accumulation of the target echo under low signal-to-noise ratio, and having a higher accumulation gain than the incoherent accumulation.

[0103] A second aspect of the present invention further provides a MIMO radar target detection method, comprising:

[0104] Using the MIMO radar target echo coherent accumulation method based on the particle swarm algorithm provided in the first aspect of the present invention to coherently accumulate the echo signal of the target, and obtain a coherent accumulation result;

[0105] Based on the coherent accumulation results, the constant false alarm detection method is used to achieve target detection.

[0106] The detection method provided by the present invention constructs an error compensation and coherent accumulation model when performing radar echo coherent accumulation, and uses the optimal compensation phase obtained by optimization to simultaneously compensate for the random phase difference of echoes between channels and the Doppler phase shift caused by target motion. Compared with the usual incoherent accumulation, the detection method has a higher accumulation gain, thereby improving the target detection capability of the centralized MIMO radar.

[0107] Furthermore, the effect of the method of the present invention is verified by the following simulation experiment:

[0108] 1. Simulation conditions

[0109] This section further verifies the effectiveness of the algorithm proposed in this invention through matlab simulation. Assume that the ambient temperature is 290K and the noise coefficient is 5dB. Set the number of transmitting and receiving array elements of the radar to 64, and the transmitting signal is an orthogonal frequency division multiplexing linear frequency modulation signal, with a total of 64 channels, a carrier frequency of 4-5GHz, a bandwidth of 15MHz, a pulse width of 200μs, a pulse repetition period of 760μs, a transmitting power of 16dBm, a sampling rate of 19MHz, and a coherent integration time of 1s. Set the target RCS to 10m 2 , the target distance is 70km and the target speed is 70m / s.

[0110] Set the initial parameters of the particle swarm optimization algorithm, where the particle swarm size is 40, the particle dimension, that is, the variable to be optimized is the phase of 64 channels that need to be compensated and a speed variable, a total of 65 dimensions, the maximum number of iterations is 400, the individual learning factor is 2, the social learning factor is 2, and the inertia factor is 0.9.

[0111] 2. Simulation experiment content and result analysis

[0112] 2.1 Incoherent accumulation simulation

[0113] The target echo multi-pulse signal is simulated by incoherent accumulation. The results are as follows: Figure 3 As shown, the target signal-to-noise ratio is 7.38 dB, and the constant false alarm detection cannot detect the target at this time.

[0114] 2.2 Coherent accumulation simulation

[0115] Firstly, the optimal compensation phase, the optimal compensation phase and the optimal motion speed are obtained by using the PSO method provided by the present invention.

[0116] Then, the random phase and Doppler phase shift of the target echo time domain pulse signal are compensated simultaneously by using the optimal compensation phase, and the single-channel pulse compression is simulated after compensation, that is, the single-channel pulse compression before the range migration correction is simulated. The results are as follows: Figure 4 As shown;

[0117] In addition, a single-channel pulse compression with range migration correction using the optimal motion speed was simulated. Figure 5 shown.

[0118] from Figure 4 and Figure 5 It can be seen that after performing range migration correction by searching for the optimal motion speed, the position of the pulse compression peak changes from a slant line before correction to a straight line, which indicates the correctness of the speed search.

[0119] Finally, the target echo multi-pulse signal is subjected to the coherent accumulation simulation provided by the present invention, and the result is as follows: Figure 6As shown, in theory, the coherent accumulation gain should be improved by 9 dB compared with the incoherent accumulation. After the PSO algorithm accumulation of the present invention, the target gain is improved by about 7.5 dB compared with the incoherent accumulation, and the loss is within an acceptable range.

[0120] It can be seen from the simulation results that, under the same conditions, the method proposed in the present invention has a higher echo accumulation gain than the incoherent integration.

[0121] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A MIMO radar target echo coherent integration method, characterized in that: include: Preprocess the radar echo signal to obtain the echo time domain pulse signals of different channels; Building an error compensation and coherence accumulation model based on the echo time domain pulse signal; Optimizing and solving the error compensation and coherent accumulation model to obtain an optimal compensation phase; The random phase and Doppler phase shift of the echo time-domain pulse signal are compensated simultaneously by using the optimal compensation phase, and the echo time-domain pulse signals of all channels after compensation are added to realize echo coherent accumulation.

2. A MIMO radar target echo coherent accumulation method according to claim 1, characterized in that: Preprocess the radar echo signal to obtain the echo time domain pulse signals of different channels, including: Form receiving beams in different directions for radar echo signals; Performing digital channelization processing on the receiving beams in different directions to separate the transmit signal from the receiving beams and obtain first echo signals of different channels; Performing equivalent transmit beamforming processing on the first echo signal to remove a phase term to obtain a second echo signal of a different channel; Performing down-conversion processing on the second echo signal to obtain a third echo signal of a different channel; The third echo signal is pulse compressed to obtain echo time-domain pulse signals of different channels.

3. A MIMO radar target echo coherent accumulation method according to claim 1, characterized in that: The expression of the error compensation and coherent accumulation model is: In the formula, represents the compensation phase of the random phase of all channels, v represents the moving speed of the target, E represents the expectation, represents the compensation phase of the random phase of the mth channel, P m represents the compensation function vector of the mth channel, y m represents the echo time domain pulse signal of the mth channel, || represents the absolute value, and M represents the number of transmitting array elements, that is, the total number of channels.

4. A MIMO radar target echo coherent integration method according to claim 1, characterized in that: Optimizing and solving the error compensation and coherent accumulation model to obtain the optimal compensation phase includes: Taking the compensation phase of the random phase of all channels and the moving speed of the target as the dimension of a particle, the error compensation and coherent accumulation model is optimized and solved using the particle swarm algorithm to obtain the optimal compensation phase.

5. A MIMO radar target echo coherent integration method according to claim 4, characterized in that: Taking the compensation phase of the random phase of all channels and the moving speed of the target as the dimension of a particle, the error compensation and coherent accumulation model is optimized and solved using the particle swarm algorithm to obtain the optimal compensation phase, which specifically includes: a) Taking the compensation phase of the random phase of all channels and the moving speed of the target as the dimension of a particle, the parameters of the particle swarm algorithm are initialized; b) Update the velocity of each particle; c) Update the position of each particle; d) Calculate the fitness value of each particle, and update the individual historical optimal fitness value, individual optimal position, group historical optimal fitness value, group optimal position and inertia weight iteration number of each particle; e) Repeat steps b)-d) until the end condition is met and the optimal compensation phase and optimal movement speed are obtained.

6. A MIMO radar target echo coherent integration method according to claim 5, characterized in that: The formula for updating the velocity of each particle is expressed as: In the formula, and denote the d-th dimension velocity of particle i in the l+1th and lth iterations, respectively. reflects the particle's confidence in the current state, ω represents the inertia factor, represents the historical optimal fitness value of particle i in the dth dimension in the lth iteration, represents the position of particle i in the dth dimension in the lth iteration, It reflects the influence of the optimal position of individual particles on particle update, c1 represents the individual learning factor, r1 represents a random number in [0,1], represents the historical optimal fitness value of the dth dimension of the group in the lth iteration, It reflects the influence of the optimal position of the group on the particle update, c2 represents the social learning factor, and r2 represents a random number in [0,1].

7. A MIMO radar target echo coherent integration method according to claim 5, characterized in that: The formula for updating the position of each particle is expressed as: In the formula, and denote the position of particle i in the dth dimension in the l+1th and lth iterations respectively, represents the d-th dimension velocity of particle i in the l-th iteration.

8. A MIMO radar target echo coherent integration method according to claim 5, characterized in that: Before adding the echo time domain pulse signals of all channels after compensation, it also includes: The optimal motion speed is used to calculate the range migration of each pulse in each channel, and the compensated signal is corrected for the range migration through a translation operation.

9. A MIMO radar target detection method, characterized in that: include: Using the MIMO radar target echo coherent accumulation method based on particle swarm algorithm as described in any one of claims 1 to 8 to coherently accumulate the echo signal of the target to obtain a coherent accumulation result; Based on the coherent accumulation result, a constant false alarm detection method is used to achieve target detection.

Images