Distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method

Abstract

The invention discloses a multi-channel multi-frame signal accumulation detection method for a distributed coherent MIMO radar, and is applied to the technical field of radars. The method aims to solve the problem that when distributed coherent MIMO radar echo signals are accumulated, due to space-variant characteristics of target echo signal envelopes and phases between different channels and time-variant characteristics of target echo signal envelopes and phases between different frames, multi-channel and multi-frame coherent accumulation cannot be achieved. Firstly, signal accumulation in channels is realized by utilizing generalized Radon-Fourier transform (GRFT), and a multi-channel accumulation method is designed by fully utilizing output characteristics of the GRFT and a topological structure of a radar system so as to compensate difference of envelopes and phases of target signals among different channels and further realize target energy coherent accumulation among the different channels. Finally, a multi-frame accumulation processing method is provided, envelope and phase differences among multi-frame echo signals are corrected and compensated, and therefore multi-channel multi-frame coherent accumulation of the echo signals is completed, and the target detection performance of the radar is remarkably improved.

Description

Technical Field

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

[0002] With the continuous advancement of technology, the radar cross-section (RCS) of the target is gradually reduced, resulting in a gradual reduction in the energy in the target echo signal, making detection increasingly difficult. Therefore, improving the signal-to-noise ratio (SNR) of the target echo signal, thereby increasing the probability of radar detecting weak targets, has become a research focus in recent years.

[0003] Distributed coherent multiple-input multiple-output (MIMO) radar acquires multi-channel echo data by transmitting orthogonal waveforms, and acquires multi-frame echo data by extending the observation time. By accumulating multi-channel and multi-frame echo data, the target signal-to-noise ratio can be significantly improved. However, distributed coherent MIMO radar encounters some challenges in the accumulation process. First, in a single channel, high-speed targets will cause range migration (RM) and Doppler frequency migration (DFM) between multiple pulses, making it difficult to apply the traditional moving target detection (MTD) algorithm. The second problem is the accumulation between multiple channels. Due to the difference in node topology distribution, the envelope and phase of the target echo signal vary spatially between different channels. The third problem is the accumulation between multiple frames. The target motion causes the envelope and phase of the target echo signal to vary temporally between different frames. Therefore, it is urgent to study a distributed coherent MIMO radar multi-channel and multi-frame signal accumulation detection method. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method, which can realize the accumulation of multi-channel multi-frame signals, greatly improve the target signal-to-noise ratio, and increase the probability of weak target detection.

[0005] The technical solution adopted by the present invention is: a distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method, comprising:

[0006] S1. The radar transmits an orthogonal frequency division multiplexing signal, establishes an echo signal model, performs matching separation and pulse compression on the obtained mixed echo, and obtains a discrete echo signal;

[0007] S2, determining search parameters, and using generalized Radon-Fourier transform to perform in-channel accumulation on the discrete echo signal obtained in step S1;

[0008] S3, analyzing the envelope and phase differences of echo signals between multiple channels, and constructing echo envelope alignment and phase compensation functions between channels;

[0009] S4, using the echo envelope alignment and phase compensation function between channels to eliminate the envelope difference and phase difference of the echo signals between channels, and complete the multi-channel accumulation along the spatial dimension;

[0010] S5, based on the multi-channel accumulation results along the spatial dimension obtained in step S4, analyzing the envelope and phase difference of the echo signals between multiple frames, and designing the envelope addressing mode and phase compensation function of the echo between frames;

[0011] S6. Using the designed envelope addressing method and phase compensation function, the envelope difference and phase difference between frames are eliminated to complete the multi-frame accumulation along the time dimension;

[0012] S7, performing constant false alarm detection processing on the multi-frame accumulation results along the time dimension obtained in step S6 to obtain a target detection result.

[0013] Beneficial effects of the invention: The invention provides a distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method, which is applied to the field of radar technology. The invention aims at the problem that when accumulating distributed coherent MIMO radar echo signals, multi-channel multi-frame coherent accumulation cannot be achieved due to the spatial variation of the envelope and phase of the target echo signal between different channels, and the time variation of the envelope and phase of the target echo signal between different frames. Firstly, the generalized Radon-Fourier transform (GRFT) is used to realize the signal accumulation within the channel, and a multi-channel accumulation method is designed by making full use of the output characteristics of the GRFT and the topological structure of the radar system to compensate for the differences in the envelope and phase of the target signal between different channels, thereby realizing the coherent accumulation of target energy between different channels. Finally, a multi-frame accumulation processing method is proposed to correct and compensate for the envelope and phase differences between multi-frame echo signals, thereby completing the multi-channel multi-frame coherent accumulation of echo signals and significantly improving the radar's detection performance for targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flow chart of an embodiment of the present invention.

[0015] Figure 2 The diagram is a diagram illustrating the topological structure relationship between nodes in an embodiment of the present invention.

[0016] Figure 3 1 is the noise-free pulse compression result of the radar 1 transmit and 1 receive channel in the first frame in an embodiment of the present invention.

[0017] Figure 4 It is the GRFT channel accumulation result (normalized) of radar 1 transmit and 1 receive channel in the first frame in the embodiment of the present invention.

[0018] Figure 5This is the inter-channel accumulation result of the multi-channel echo data of the first frame by the multi-channel accumulation method proposed in the embodiment of the present invention.

[0019] Figure 6 The distance dimension slice and speed dimension slice and the theoretical response curve of the multi-channel accumulation method in the embodiment of the present invention;

[0020] in Figure 6 (a) is the distance dimension slice of the proposed multi-channel accumulation method, Figure 6 (b) Velocity dimension slice of the proposed multi-channel accumulation method.

[0021] Figure 7 It is the multi-frame accumulation result of the multi-frame accumulation method proposed in the embodiment of the present invention.

[0022] Figure 8 The distance dimension slice and speed dimension slice and the theoretical response curve of the multi-frame accumulation method in the embodiment of the present invention;

[0023] in Figure 8 (a) is the distance dimension slice of the proposed multi-frame accumulation method, Figure 8 (b) Velocity dimension slice of the proposed multi-frame accumulation method.

[0024] Fig. 9 The test performance curve. DETAILED DESCRIPTION

[0025] To facilitate those skilled in the art to understand the technical content of the present invention, the present invention is further explained below with reference to the accompanying drawings.

[0026] The present invention mainly uses scientific computing software Matlab R2022a to perform simulation experiments to verify its correctness and effectiveness. The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0027] See also Figure 1 The present invention proposes a distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method, which is specifically implemented by the following steps:

[0028] Step 1: The radar transmits an orthogonal frequency division multiplexing signal, establishes an echo signal model, and performs matching separation and pulse compression on the obtained mixed echo.

[0029] In this embodiment, an orthogonal frequency-division multiplexing (OFDM) waveform is used as the transmission waveform of the distributed coherent MIMO radar. The transmission signal of the mth node is recorded as:

[0030] s m (t) = u m(t)exp(j2πf c t),n=1,2,...,N (1)

[0031] where f c is the radar initial carrier frequency, u m (t) is an orthogonal waveform, expressed as

[0032]

[0033] Where E represents the energy of the transmitted signal, is a rectangular window function, t represents fast time, T P represents pulse width, B represents signal bandwidth, Δf represents step frequency, μ=B / T p is the frequency modulation slope.

[0034] Assume that the distributed coherent MIMO radar system consists of N radar nodes. The coordinates of the mth node are defined as Target The coordinates, velocity and acceleration at the moment are represented by vectors and express. represents the qth pulse in the kth frame, N a is the number of pulses contained in a single frame, and K is the number of observation frames.

[0035] The target maintains uniform acceleration in the horizontal direction, which can be expressed as

[0036]

[0037] where t q =(q-1)T r is the slow time, T r is the pulse repetition time,

[0038] For far-field targets, the relative motion between the target and the node is assumed to maintain uniform acceleration over a short period of time. The radial distance between the mth node and the target at the moment is Derived The expression is

[0039]

[0040] in, represents the radial velocity between the mth node and the target;

[0041] At the moment The radial distance from the mth node to the target is recorded as The specific expression of this distance is:

[0042]

[0043] where ||.|| is the Euclidean norm.

[0044] Define the observation angle of the mth node at the kth frame as exist At time , the radial velocity between the mth node and the target is recorded as

[0045]

[0046] Similarly, the relative acceleration between the mth node and the target It can be expressed as

[0047]

[0048] Respectively expressed in The relative radial distance, velocity, and acceleration of the target observed by the signal transmitted by the mth node and the signal received by the nth node at the time.

[0049]

[0050] Combining (4) with (8)-(10), we can obtain

[0051]

[0052] The delayed echo of the qth pulse of the kth frame with m transmission and n reception can be expressed as

[0053]

[0054] Where c is the propagation speed of electromagnetic waves in air.

[0055] The echo signal of the kth frame received by the nth node can be expressed as

[0056]

[0057] The echo of (13) is down-converted to obtain the baseband echo signal:

[0058]

[0059] where f m =f c +(m-1)Δf, m=1,2,...,N.

[0060] The received mixed echo is matched, separated and pulse compressed, which can be expressed as

[0061]

[0062] Where E represents the electromagnetic wave energy, sinc(x)=sin(πx) / (πx), λ=c / f c is the wavelength of the initial carrier frequency, when f c >> When Δf, λ=c / (f c +(i-1)Δf)≈c / f c .

[0063] With sampling frequency f s The echo in (16) is sampled to generate a single-channel discrete echo in the following form.

[0064]

[0065] where r = ct, ρ r =c / (2B) is the range resolution of the radar.

[0066] In this embodiment, the parameters used are: Considering that the coherent MIMO radar system includes 3 radar nodes, in the actual application scenario, the coordinates of nodes 1, 2, and 3 are (3063.36, 1542.59) m, (2811.84, 862.93) m, and (3871.36, 1141.09) m, respectively. The specific parameters of the radar are: radar carrier frequency f c is 0.15GHz, signal bandwidth B is 5MHz, pulse width T p The pulse repetition frequency is 1 / T. r is 2048Hz, the number of coherent accumulation pulses Q is 128, the step frequency △f is 6MHz, and the sampling rate f s The frequency is 50MHz, and the number of observation frames is 5. Observe a moving target, the target's coordinates are (39000, 27000)m, the speed is (-500, 0)m / s, and the acceleration is (-50, 0)m / s 2 .

[0067] The radar node described in this step is specifically explained as follows: the distributed coherent MIMO radar includes multiple nodes for transmitting and receiving, and transmitting and receiving means that the signal can be transmitted and received, and each node is composed of a linear phased array radar.

[0068] Step 2, determine the search parameters. Due to the existence of range migration (RW) and Doppler frequency migration (DFM) between pulses, generalized Radon Fourier transform (GRFT) is used for in-channel accumulation.

[0069] In this embodiment, the configuration range of the search parameters includes the potential distance, speed and acceleration of all nodes by using the prior knowledge about the detection area and the target. The distance search range is set to [-r max ,r max ], the speed search range is [-v max ,v max ], the acceleration search range is [-a max ,a max ].

[0070] In the kth frame, the output of the m-transmit and n-receive channels of GRFT can be written as

[0071]

[0072] Substituting (17) into (18), we obtain

[0073]

[0074] After mathematical operations, the result of formula (19) can be expressed as

[0075]

[0076] From (20), we can see that when When GRFT is used, the target energy accumulation in the channel can be achieved.

[0077] In this embodiment, the parameters used are: the distance search range is 84.5km to 90.5km, the speed search range is -1720m / s to -1540m / s; the acceleration search range is -48m / s 2 To -80m / s 2 .

[0078] Step 3: Analyze the envelope and phase differences of echo signals between multiple channels, and construct echo envelope alignment and phase compensation functions between channels.

[0079] In this embodiment, the peak difference between channels is caused by the different topological distributions between nodes. To facilitate analysis, a diagram illustrating the topological structure relationship between nodes in the radar system is drawn, as shown in FIG. Figure 2 shown.

[0080] According to the principle of geometric topology, the transformation relationship of the radial distance parameter between node 1 and node n can be obtained as follows:

[0081]

[0082] where r 1,n =||p1-p n ||2 represents the baseline distance between node 1 and node n, represents the observation angle of the first node, Represents the angle between the straight line from node 1 to node n and the x-axis.

[0083] We can get the conversion relationship between radial velocity and acceleration at the 1st node and the nth node as follows

[0084]

[0085] (1) Envelope difference analysis between multiple channels

[0086] In order to retain the generality, we take the kth frame as an example. From formula (20), we can see that The peak coordinates are The peak coordinates are and The peak envelope difference can be determined as

[0087]

[0088] Substituting (21)-(23) into (24)-(26) we obtain

[0089]

[0090] (2) Phase difference analysis between multiple channels

[0091] From formula (20), we can see that The peak phase is

[0092]

[0093] The peak phase is

[0094]

[0095] From formula (30) and formula (31), we can see that and The peak phase difference can be calculated as

[0096]

[0097] Substituting formula (27) into formula (32), we can obtain:

[0098]

[0099] From (27) and (33), we can see that by using the relative motion parameters between node 1 and the target and combining the known prior geometric topology information, the envelope difference and phase difference between multiple channels can be calculated.

[0100] Step 4: Use the inter-channel echo envelope alignment and phase compensation function to eliminate the envelope difference and phase difference of the echo signals between channels, complete the multi-channel accumulation along the spatial dimension, and give its theoretical output response.

[0101] In this embodiment, the envelope difference and phase difference of the echo signals between the channels are eliminated by using the echo envelope alignment and phase compensation function between the channels. A multi-channel accumulation algorithm along the spatial dimension is proposed. The accumulation results are as follows:

[0102]

[0103] in represents the convolution operation, is the phase compensation function, is the envelope compensation function. According to equations (27)-(33), and It can be expressed as

[0104]

[0105] in

[0106]

[0107] In formula (37), when When , equation (33) holds, and the phase compensation function is equation (36), and the phase can be accurately compensated;

[0108] The theoretical output response of the multi-channel accumulation algorithm along the spatial dimension of the kth frame can be obtained as

[0109]

[0110] Step 5: Analyze the envelope and phase differences of echo signals between multiple frames, and design an envelope addressing method and phase compensation function for echoes between frames.

[0111] In this embodiment, the envelope difference and phase difference of the output peaks between multiple frames are analyzed first.

[0112] (1) Envelope difference analysis between multiple frames

[0113] From formula (40), we can see that I k The peak coordinates of (r,v,a) are I k+1 The peak coordinates of (r,v,a) are The peak envelope difference of multi-channel accumulation between adjacent frames can be obtained as

[0114]

[0115]

[0116] It is not difficult to understand that the change of distance parameter with time is a quadratic function related to speed and acceleration. The change of speed parameter with time is a linear function related to acceleration. Therefore, we can get

[0117]

[0118] Where T F =N a T r The duration of a single frame.

[0119] We can calculate the target peak coordinates of the next frame from the target peak coordinates of any frame.

[0120] (2) Phase difference analysis between multiple frames

[0121] From formula (40), we can see that I k The peak phase of (r,v,a) is

[0122]

[0123] I k+1 The peak phase of (r,v,a) is

[0124]

[0125] From equations (47) and (48), we can see that I k (r, v, a) and I k+1 The peak phase difference of (r,v,a) can be calculated as

[0126]

[0127] Similarly, we can use formula (49) to calculate the target peak phase of the next frame from the target peak phase of any frame.

[0128] Step 6, using the designed envelope addressing method and phase compensation function, eliminate the envelope difference and phase difference between frames, complete the multi-frame accumulation along the time dimension, and give its theoretical output response.

[0129] According to equation (44) and equation (49), the phase compensation function is defined as:

[0130]

[0131] In this embodiment, the designed inter-frame echo envelope addressing method and phase compensation function are used to eliminate the envelope difference and phase difference between frames, and a multi-frame accumulation algorithm along the time dimension is proposed to achieve the coherent accumulation of energy between multiple frames. The accumulation results are as follows:

[0132]

[0133] The theoretical output response of the multi-frame accumulation algorithm of k frames along the time dimension can be obtained as follows:

[0134]

[0135] Step 7: Perform constant false alarm detection processing according to the multi-frame multi-channel accumulation result of step S6 to obtain a target detection result.

[0136] In this embodiment, the parameters used are: the false alarm probability is P f =10 -4 , the input signal-to-noise ratio (SNR) ranges from -38dB to 0dB after matched filtering.

[0137] In order to illustrate the effectiveness of the method of the present invention, Figure 3 The noise-free pulse compression result of a transmit-receive channel in the first frame is shown. We can see that the target motion trajectory is curved. This is because the high-speed motion of the target causes the RM phenomenon in the channel. Figure 4 The accumulation results (normalized) of the one-transmit-one-receive channel obtained by using the GRFT method in the first frame are shown. It can be seen that the GRFT algorithm effectively corrects the RM and DFM problems in the channel and successfully realizes the coherent accumulation of multiple pulses. Figure 5 The results of channel-to-channel accumulation of multi-channel echo data of frame 1 using the multi-channel accumulation algorithm along the spatial dimension proposed by the present invention are shown. Figure 5 It can be seen that 9 channels are accurately accumulated in this frame, and the accumulation peak is 9 times the GRFT accumulation peak. In order to verify the output response of the multi-channel accumulation algorithm along the spatial dimension, we plotted the distance dimension slice and speed dimension slice of the multi-channel accumulation algorithm, as well as the theoretical response curve (see equation 40). Figure 6 As shown in the figure, the results are consistent with the theoretical curve, indicating that the performance of the algorithm in this paper is consistent with the theoretical value.

[0138] Figure 7 The results of accumulating 5 frames along the time dimension using the multi-frame accumulation algorithm proposed in the present invention are shown. Compared with the multi-channel accumulation results, its accumulation peak is 5 times that of the multi-channel accumulation peak. Compared with the GRFT accumulation peak, the accumulation peak amplitude is increased by 45 times. The results show that the algorithm can accurately accumulate multi-channel multi-frame echo data. Similarly, in order to further analyze the output response of the multi-frame accumulation algorithm, we plotted the distance dimension slices and velocity dimension slices of the multi-frame accumulation algorithm and the corresponding theoretical response curves (see Equation 51), as shown in Figure 8 As shown. Figure 8 It can be seen that the results are in good agreement with the theoretical response curve.

[0139] Fig. 9 The detection performance curves of GRFT single-channel accumulation, Hough transform-based pre-detection tracking algorithm, greedy-dynamic programming-based pre-detection tracking algorithm, single radar multi-frame accumulation algorithm, parameter iterative estimation algorithm and the multi-channel multi-frame accumulation algorithm proposed by the present invention are shown. Fig. 9 It can be seen that the detection effect of the multi-channel multi-frame accumulation algorithm proposed in the present invention is better than other algorithms. This is because GRFT can only accumulate multi-pulse energy in a single channel, and cannot utilize the multi-channel, multi-frame echo data of the coherent MIMO radar system, so it cannot obtain gains in both spatial and temporal dimensions. The detection-before-tracking algorithm based on Hough transform will cause algorithm performance loss due to target loss when dealing with highly maneuverable targets. The detection-before-tracking algorithm based on greedy-dynamic programming is incoherent and will cause certain performance losses. The single-radar multi-frame accumulation algorithm is customized for multi-frame accumulation in a single-base radar, so it lacks spatial dimension gain in a coherent MIMO radar. The parameter iterative estimation algorithm only accumulates one frame of data in a coherent MIMO radar system, lacking temporal accumulation gain.

[0140] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. For those skilled in the art, the present invention may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method, characterized in that: include: S1. The radar transmits an orthogonal frequency division multiplexing signal, establishes an echo signal model, performs matching separation and pulse compression on the obtained mixed echo, samples the matching separation and pulse compression results, and obtains a discrete echo signal; S2, determining search parameters, and using generalized Radon-Fourier transform to perform in-channel accumulation on the discrete echo signal obtained in step S1; S3, analyzing the envelope and phase differences of echo signals between multiple channels, and constructing an echo envelope compensation function and a phase compensation function between channels; S4, using the echo envelope alignment and phase compensation function between channels to eliminate the envelope difference and phase difference of the echo signals between channels, and complete the multi-channel accumulation along the spatial dimension; S5, based on the multi-channel accumulation results along the spatial dimension obtained in step S4, analyzing the envelope and phase difference of the echo signals between multiple frames, and designing the envelope addressing mode and phase compensation function of the echo between frames; S6. Using the designed envelope alignment addressing mode and phase compensation function, the envelope difference and phase difference between frames are eliminated to complete the multi-frame accumulation along the time dimension; S7, performing constant false alarm detection processing on the multi-frame accumulation results along the time dimension obtained in step S6 to obtain a target detection result.

2. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 1, characterized in that: The process of establishing the echo signal model in step S1 is: A1. The radar transmits an orthogonal frequency division multiplexing signal. The transmission signal of the mth node is recorded as: s m (t)=u m (t)exp(j2πf c t),n=1,2,...,N Among them, f c is the radar initial carrier frequency, u m (t) is an orthogonal waveform, t represents fast time, and N represents the total number of radar nodes; A2, the delayed echo of the qth pulse of the kth frame with m transmission and n reception is expressed as in, Indicated in The relative radial distance between the target observed by the signal transmitted by the mth node and the signal received by the nth node at the moment, c is the propagation speed of electromagnetic waves in the air; A3. The echo signal of the kth frame received by the nth node is expressed as A4, down-convert the echo signal obtained in step A3 to obtain a baseband echo signal: where f m =f c +(m-1)Δf,m=1,2,...,N.

3. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 2, characterized in that: The search parameters in step S2 include: distance r, speed v, acceleration a.

4. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 3, characterized in that: The process of constructing the inter-channel echo envelope compensation function in step S3 is as follows: S311. According to the principle of geometric topology, the transformation relationship of the radial distance parameter between node 1 and node n is obtained as follows: Among them, r 1,n represents the baseline distance between node 1 and node n, Represents the observation angle of the first node, θ 1,n Represents the angle between the straight line from node 1 to node n and the x-axis, express The radial distance between the first node and the target at the moment; S312, the conversion relationship between the radial velocity and the acceleration at the first node and the nth node is obtained as follows: in, Indicates the radial velocity between the first node and the target Spend, represents the observation angle of the nth node, Represents the radial acceleration between the first node and the target; S313, taking the kth frame as an example, according to The peak coordinates The peak coordinates and The peak envelope difference is in, express, express, Indicated in The relative radial distance between the target observed by the signal transmitted by the mth node and the signal received by the nth node at the moment, Represents the transformation relationship of the radial distance parameter between the first node and node n, represents the transformation relationship of the radial distance parameter between the first node and node m, Indicated in The relative speed of the target observed by the signal transmitted by the mth node and the signal received by the nth node at the moment, represents the radial velocity conversion relationship between the 1st node and the mth node, represents the radial velocity conversion relationship between the 1st node and the nth node, Indicated in The relative radial acceleration of the target observed by the signal transmitted by the mth node and the signal received by the nth node at the moment, Represents the radial acceleration conversion relationship between the 1st node and the mth node, Indicates the radial acceleration conversion relationship between the 1st node and the nth node; S314. Substituting equations (21)-(23) into equations (24)-(26), we obtain: Among them, θ 1,m represents the angle between the straight line from node 1 to node m and the x-axis, represents the observation angle of the mth node; S315. According to the results obtained from (27) to (29), construct an inter-channel echo envelope compensation function: Among them, Δr, -Δv, and Δa are the peak envelope differences, 5. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 4, characterized in that: The process of constructing the inter-channel echo phase compensation function in step S3 is as follows: S321, The peak phase is S322, The peak phase is Where λ is the wavelength of the initial carrier frequency; S323, obtained from equation (30) and equation (31) and The peak phase difference is S324. Substituting formula (27) into formula (32), we obtain: S325, constructing an inter-channel echo phase compensation function according to the peak phase difference 6. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 5, characterized in that: The process of constructing the phase compensation function of the inter-frame echo in step S5 is: Step S4 completes the multi-channel accumulation along the spatial dimension, and the theoretical output response of the multi-channel accumulation algorithm along the spatial dimension of the kth frame is obtained as follows: According to formula (40), we get I k The peak coordinates of (r,v,a) are I k+1 The peak coordinates of (r,v,a) are The peak envelope difference of multi-channel accumulation between adjacent frames is obtained as Further, we get Where T F is the duration of a single frame; From formula (40), we can get I k The peak phase of (r,v,a) is Theoretical output response of the multi-channel accumulation algorithm along the spatial dimension of the k+1th frame I k+1 The peak phase of (r,v,a) is According to formula (47) and formula (48), I k (r, v, a) and I k+1 The peak phase difference of (r,v,a) is calculated as According to formula (44) and formula (49), the phase compensation function is defined as:

7. A distributed coherent MIMO radar multi-channel multi-frame signal accumulation detection method according to claim 6, characterized in that: The multi-frame accumulation result along the time dimension in step S6 is expressed as:

Images