A distributed phase comparison MIMO radar multi-channel multi-frame signal accumulation detection method

Abstract

The application discloses a distributed phase-tracking MIMO radar multi-channel multi-frame signal accumulation detection method, and is applied to the technical field of radars. In view of the problem that, when the echo signal of a distributed phase-tracking MIMO radar is accumulated, the envelope and phase of the target echo signal between different channels are space-varying, and the envelope and phase of the target echo signal between different frames are time-varying, so that the multi-channel multi-frame phase-tracking accumulation cannot be realized, firstly, a generalized Radon-Fourier transform (GRFT) is used to realize the signal accumulation in the channel, and a multi-channel accumulation method is designed by fully utilizing the output characteristics of the GRFT and the topological structure of the radar system, so as to compensate for the envelope and phase differences of the target signal between different channels, and then realize the phase-tracking accumulation of the target energy between different channels. Finally, a multi-frame accumulation processing method is provided, the envelope and phase differences between multi-frame echo signals are corrected and compensated, so that the multi-channel multi-frame phase-tracking accumulation of the echo signal is completed, and the detection performance of the radar on the target is significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of radar technology, and specifically relates to a target detection technology. Background Technology

[0002] With continuous technological advancements, the radar cross-section (RCS) of targets is gradually decreasing, leading to a reduction in the energy of the target echo signal and increasing the difficulty of detection. Therefore, improving the signal-to-noise ratio (SNR) of the target echo signal, thereby increasing the probability of radar detection of 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 obtains multi-frame echo data by extending the observation time. Accumulating multi-channel, multi-frame echo data can significantly improve the target signal-to-noise ratio. However, distributed coherent MIMO radar encounters several challenges during the accumulation process. First, within a single channel, high-speed targets cause range migration (RM) and Doppler frequency migration (DFM) between multiple pulses, making traditional moving target detection (MTD) algorithms difficult to apply. The second problem is accumulation between multiple channels; differences in node topology distribution lead to spatial variations in the envelope and phase of the target echo signal across different channels. The third problem is accumulation between multiple frames; target motion causes temporal variations in the envelope and phase of the target echo signal between different frames. Therefore, it is urgent to research a multi-channel, multi-frame signal accumulation and detection method for distributed coherent MIMO radar. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a distributed coherent MIMO radar multi-channel, multi-frame signal accumulation and detection method, which can accumulate multi-channel, multi-frame signals, greatly improving the target signal-to-noise ratio and increasing the probability of detecting weak targets.

[0005] The technical solution adopted in this invention is: a method for multi-channel, multi-frame signal accumulation and detection in distributed coherent MIMO radar, comprising:

[0006] S1. 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 to obtain a discrete echo signal.

[0007] S2. Determine the search parameters and use the generalized Radon-Fourier transform to perform in-channel accumulation on the discrete echo signal obtained in step S1.

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

[0009] S4. By using the inter-channel echo envelope alignment and phase compensation function, the envelope difference and phase difference of the inter-channel echo signal are eliminated, and multi-channel accumulation along the spatial dimension is completed.

[0010] S5. Based on the multi-channel accumulation results along the spatial dimension obtained in step S4, analyze the envelope and phase difference of the inter-frame echo signals, and design the envelope addressing method and phase compensation function of the inter-frame echo.

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

[0012] S7. Perform constant false alarm rate (CFAR) detection processing on the multi-frame accumulation results along the time dimension obtained in step S6 to obtain the target detection results.

[0013] The beneficial effects of this invention: This invention provides a multi-channel, multi-frame signal accumulation and detection method for distributed coherent MIMO radar, applied in the field of radar technology. Addressing the problem that multi-channel, multi-frame coherent accumulation cannot be achieved in distributed coherent MIMO radar echo signal accumulation due to the spatial variability of the target echo signal envelope and phase between different channels, and the time-varying nature of the target echo signal envelope and phase between different frames, this invention first utilizes the generalized Radon-Fourier transform (GRFT) to achieve signal accumulation within a channel. Then, fully leveraging the output characteristics of GRFT and the radar system topology, a multi-channel accumulation method is designed to compensate for the differences in the envelope and phase of the target signal between different channels, thereby achieving 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, thus completing multi-channel, multi-frame coherent accumulation of the echo signal and significantly improving the radar's target detection performance. Attached Figure Description

[0014] Figure 1 This is a flowchart of an embodiment of the present invention.

[0015] Figure 2 This is an illustration of the topological relationships between nodes in an embodiment of the present invention.

[0016] Figure 3 This is the noiseless pulse compression result of the radar transmit and receive channels 1 and 1 receive in the first frame of this embodiment.

[0017] Figure 4 This is the normalized accumulation result within the GRFT channel of the radar 1 transmit 1 receive channel in the first frame of this embodiment.

[0018] Figure 5The image shows the inter-channel accumulation result of the multi-channel echo data of the first frame using the multi-channel accumulation method proposed in this embodiment of the invention.

[0019] Figure 6 The images show the distance dimension slice, velocity dimension slice, and theoretical response curve of the multi-channel accumulation method proposed in this embodiment of the invention.

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

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

[0022] Figure 8 The images show the distance-dimensional slices, velocity-dimensional slices, and theoretical response curves of the multi-frame accumulation method proposed in this embodiment of the invention.

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

[0024] Figure 9 This is for detecting performance curves. Detailed Implementation

[0025] To facilitate understanding of the technical content of this invention by those skilled in the art, the following description, in conjunction with the accompanying drawings, further illustrates the invention.

[0026] This invention primarily utilizes the scientific computing software Matlab R2022a for simulation experiments to verify its correctness and effectiveness. The embodiments of this invention are further described below with reference to the accompanying drawings.

[0027] Please see Figure 1 The present invention proposes a distributed coherent MIMO radar multi-channel multi-frame signal accumulation and detection method, which is implemented through the following steps:

[0028] Step 1: The radar transmits an orthogonal frequency division multiplexed 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 transmitted waveform for the distributed coherent MIMO radar. The transmitted signal of the m-th node is denoted as:

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

[0031] Where f c U is the initial carrier frequency of the radar. m (t) represents an orthogonal waveform, denoted as

[0032]

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

[0034] Assume a distributed coherent MIMO radar system consists of N radar nodes. The coordinates of the m-th node are defined as follows: The goal is The coordinates, velocity, and acceleration at each moment are represented by vectors. and express. N represents the q-th pulse within the k-th frame. a K represents the number of pulses contained in a single frame, and K represents the number of observation frames.

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

[0036]

[0037] Where t q =(q-1)T r For slow time, T r The pulse repetition time,

[0038] For far-field targets, it is assumed that the relative motion between the target and the node maintains uniform acceleration over a short period of time. Defined in The radial distance between the m-th node and the target at time m is Derivation The expression is

[0039]

[0040] in, This represents the radial velocity between the m-th node and the target;

[0041] At any moment The radial distance from the m-th node to the target is denoted as . The specific expression for this distance is:

[0042]

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

[0044] Define the observation angle of the m-th node at the k-th frame as: exist At time m, the radial velocity between the m-th node and the target is denoted as...

[0045]

[0046] Similarly, the relative acceleration between the m-th node and the target It can be represented as

[0047]

[0048] They represent in The relative radial distance, velocity, and acceleration of the target observed at time m are the signals transmitted by the m-th node and received by the n-th node. (Specify)

[0049]

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

[0051]

[0052] The delayed echo of the q-th pulse in the k-th frame transmitted and received by m can be expressed as:

[0053]

[0054] m = 1, 2...N; n = 1, 2...N

[0055] Where c is the speed at which electromagnetic waves propagate in the air.

[0056] The echo signal of the k-th frame received by the n-th node can be represented as:

[0057]

[0058] The echo from (13) is down-converted to obtain the baseband echo signal.

[0059]

[0060] Where f m =f c +(m-1)Δf, m=1,2,...,N.

[0061] Matching, separating, and pulse compression of the received mixed echoes can be represented as follows:

[0062]

[0063] Where E represents the electromagnetic wave energy, sinc(x) = sin(πx) / (πx), λ = c / f c The wavelength of the initial carrier frequency, when f c >>When △f, we have λ=c / (f) c +(i-1)△f)≈c / f c .

[0064] With sampling frequency f s The echo in (16) is sampled to generate a single-channel discrete echo in the following form.

[0065]

[0066] q = 1, 2, ..., Q

[0067] Where r = ct, ρ r =c / (2B) is the range resolution of the radar.

[0068] In this embodiment, the parameters used are as follows: Considering that the coherent MIMO radar system contains 3 radar nodes, in a practical 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 radar parameters are: radar carrier frequency f... c The signal bandwidth B is 5MHz, and the pulse width T is 0.15GHz. p The pulse repetition frequency is 1 / T and the pulse duration is 20µs. r The frequency is 2048Hz, the coherent accumulation pulse number Q is 128, the step frequency Δf is 6MHz, and the sampling rate f is... s The frequency is 50MHz, and the observation frame count is 5 frames. A moving target is observed with coordinates (39000, 27000) m, velocity (-500, 0) m / s, and acceleration (-50, 0) m / s². 2 .

[0069] The radar nodes mentioned in this step are specifically explained as follows: Distributed coherent MIMO radar includes multiple nodes that share both transmitting and receiving capabilities. Shared transmission and receiving means that it can both transmit and receive signals, and each node is composed of a linear phased array radar.

[0070] Step 2: Determine the search parameters. Due to the existence of inter-pulse distance migration (RW) and Doppler frequency migration (DFM), channel accumulation is performed using the Generalized Radon Fourier Transform (GRFT).

[0071] In this embodiment, utilizing prior cognitive information related to the detection area and target, the configuration range of the search parameters includes the potential distance, velocity, and acceleration of all nodes. 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 ].

[0072] In the k-th frame, the output of the m transmit and n receive channels of the GRFT can be written as

[0073]

[0074] Substituting (17) into (18) gives us

[0075]

[0076] After mathematical calculation, the result of equation (19) can be expressed as follows:

[0077]

[0078] From (20), we can see that when At that time, the accumulation of target energy within the channel can be achieved through GRFT.

[0079] In this embodiment, the parameters used are: distance search range of 84.5km to 90.5km, speed search range of -1720m / s to -1540m / s, and acceleration search range of -48m / s². 2 up to -80m / s 2 .

[0080] Step 3: Analyze the envelope and phase differences of the echo signals between multiple channels, and construct the echo envelope alignment and phase compensation functions between channels.

[0081] In this embodiment, the peak value difference between channels is caused by the different topological distributions between nodes. For ease of analysis, a diagram illustrating the topological relationship between radar system nodes is provided, such as... Figure 2 As shown.

[0082] Based on the principles of geometric topology, the transformation relationship of the radial distance parameter between node 1 and node n can be obtained as follows:

[0083]

[0084] Where r 1,n =||p1-p n ||2 represents the baseline distance between node 1 and node n. This represents the observation angle of the first node. This represents the angle between the line from node 1 to node n and the x-axis.

[0085] We can obtain the conversion relationship between radial velocity and acceleration between the 1st node and the nth node, as shown below.

[0086]

[0087] (1) Multi-channel envelope difference analysis

[0088] To avoid loss of generality, we take the k-th frame as an example. From equation (20), we can see that... The peak coordinates are The peak coordinates are and The peak envelope difference can be determined as

[0089]

[0090] Substituting (21)-(23) into (24)-(26) yields

[0091]

[0092] (2) Multi-channel phase difference analysis

[0093] From equation (20), we can see that The peak phase is

[0094]

[0095] The peak phase is

[0096]

[0097] From equations (30) and (31), it can be seen that, and The peak phase difference can be calculated as

[0098]

[0099] Substituting equation (27) into equation (32), we get:

[0100]

[0101] As can be seen from (27) and (33), by using the relative motion parameters between node 1 and the target, combined with the known prior geometric topology information, the envelope difference and phase difference between multiple channels can be calculated.

[0102] Step 4: Using the inter-channel echo envelope alignment and phase compensation function, eliminate the envelope and phase differences of the inter-channel echo signals, complete the multi-channel accumulation along the spatial dimension, and give its theoretical output response.

[0103] In this embodiment, by utilizing inter-channel echo envelope alignment and phase compensation functions, the envelope and phase differences of inter-channel echo signals are eliminated, and a multi-channel accumulation algorithm along the spatial dimension is proposed. The accumulation results are as follows:

[0104]

[0105] in This represents the convolution operation. For phase compensation function, For the envelope compensation function, according to equations (27)-(33), and It can be represented as

[0106]

[0107] in

[0108]

[0109] In equation (37), when When equation (33) holds, the phase compensation function is obtained as equation (36), and the phase can be accurately compensated;

[0110] The theoretical output response of the multi-channel accumulation algorithm along the spatial dimension of the k-th frame can be obtained as follows:

[0111]

[0112] Step 5: Analyze the envelope and phase differences of the inter-frame echo signals, and design the envelope addressing method and phase compensation function for the inter-frame echoes.

[0113] In this embodiment, the envelope difference and phase difference of the output peaks between multiple frames are analyzed first.

[0114] (1) Inter-frame envelope difference analysis

[0115] From equation (40), we can see that I kThe peak coordinates of (r,v,a) are I k+1 The peak coordinates of (r,v,a) are The peak envelope difference accumulated by multiple channels between adjacent frames can be obtained as follows:

[0116]

[0117]

[0118] It's easy to understand that the distance parameter changes with time as a quadratic function of velocity and acceleration. The velocity parameter changes with time as a linear function of acceleration. Therefore, we can obtain...

[0119]

[0120] Where T F =N a T r The duration of a single frame.

[0121] We can calculate the target peak coordinates for the next frame from the target peak coordinates of any one frame.

[0122] (2) Multi-frame phase difference analysis

[0123] From equation (40), we can see that I k The peak phase of (r,v,a) is

[0124]

[0125] I k+1 The peak phase of (r,v,a) is

[0126]

[0127] 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:

[0128]

[0129] Similarly, we can use equation (49) to calculate the target peak phase of the next frame from the target peak phase of any frame.

[0130] 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.

[0131] Based on equations (44) and (49), the phase compensation function is defined as follows:

[0132]

[0133] In this embodiment, by utilizing the designed inter-frame echo envelope addressing method and phase compensation function, the envelope and phase differences between frames are eliminated, and a multi-frame accumulation algorithm along the time dimension is proposed to achieve coherent accumulation of energy between multiple frames. The accumulation results are as follows:

[0134]

[0135] The theoretical output response of the multi-frame accumulation algorithm along the time dimension of k frames can be obtained as follows:

[0136]

[0137] Step 7: Perform constant false alarm rate (CFAR) detection processing based on the multi-frame, multi-channel accumulation results from step S6 to obtain the target detection results.

[0138] In this embodiment, the parameter used is: the false alarm probability is P. f =10 -4 After matched filtering, the input signal-to-noise ratio (SNR) ranges from -38dB to 0dB.

[0139] To demonstrate the effectiveness of the method of the present invention, Figure 3 The noiseless pulse compression results of the transmit and receive channels in the first frame are shown. We can see that the target's trajectory is curved, which is due to the RM phenomenon in the channel caused by the target's high-speed movement. Figure 4 The image shows the normalized accumulation results of the transmit and receive channels obtained using the GRFT method in the first frame. It can be seen that the GRFT algorithm effectively corrects the RM and DFM problems in the channel and successfully achieves coherent accumulation of multiple pulses. Figure 5 This paper demonstrates the results of inter-channel accumulation of multi-channel echo data from the first frame using the multi-channel accumulation algorithm along the spatial dimension proposed in this invention. Figure 5 As can be seen, nine channels were precisely accumulated within this frame, and the accumulation peak was nine times that of GRFT. To verify the output response of the multi-channel accumulation algorithm along the spatial dimensions, we plotted the distance and velocity slices 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 agree well with the theoretical curve, indicating that the performance of the algorithm in this paper matches the theoretical value well.

[0140] Figure 7The results of the proposed multi-frame accumulation algorithm accumulating 5 frames along the time dimension are presented. Compared with the multi-channel accumulation results, its accumulation peak value is 5 times that of the multi-channel accumulation peak value. Compared with the GRFT accumulation peak value, the accumulation peak value amplitude is increased by 45 times. The results show that the algorithm can accurately accumulate multi-channel, multi-frame echo data. Similarly, to further analyze the output response of the multi-frame accumulation algorithm, we plotted the distance dimension slice and velocity dimension slice of the multi-frame accumulation algorithm and the corresponding theoretical response curve (see Equation 51), as shown below. Figure 8 As shown. From Figure 8 As can be seen, the results agree well with the theoretical response curve.

[0141] Figure 9 The detection performance curves of GRFT single-channel accumulation, the pre-detection tracking algorithm based on Hough transform, the pre-detection tracking algorithm based on greedy-dynamic programming, the single-radar multi-frame accumulation algorithm, the parameter iterative estimation algorithm, and the multi-channel multi-frame accumulation algorithm proposed in this invention are shown. Figure 9 As can be seen, the multi-channel, multi-frame accumulation algorithm proposed in this invention outperforms other algorithms in detection performance. 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 a coherent MIMO radar system, thus failing to gain in either the spatial or temporal dimensions. The detection-before-tracking algorithm based on Hough transform suffers performance loss when handling highly maneuverable targets due to target loss. The detection-before-tracking algorithm based on greedy-dynamic programming is incoherent, causing some performance loss. The single-radar multi-frame accumulation algorithm is tailored for multi-frame accumulation in monostatic radars, therefore lacking spatial dimension gain in coherent MIMO radars. The parameter iterative estimation algorithm only accumulates one frame of data in a coherent MIMO radar system, lacking temporal accumulation gain.

[0142] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of the claims of the invention.

Claims

1. A method for detecting multi-channel, multi-frame signal accumulation in distributed coherent MIMO radar, 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. Determine the search parameters and use the generalized Radon-Fourier transform to perform in-channel accumulation on the discrete echo signal obtained in step S1. The search parameters mentioned in step S2 include: distance ,speed acceleration ; S3. Analyze the envelope and phase differences of echo signals between multiple channels, and construct the echo envelope compensation function and phase compensation function between channels; S4. By using the inter-channel echo envelope alignment and phase compensation function, the envelope difference and phase difference of the inter-channel echo signal are eliminated, and multi-channel accumulation along the spatial dimension is completed. S5. Based on the multi-channel accumulation results along the spatial dimension obtained in step S4, analyze the envelope and phase difference of the inter-frame echo signals, and design the envelope addressing method and phase compensation function for the inter-frame echoes; the process of constructing the phase compensation function for the inter-frame echoes in step S5 is as follows: Step S4 completes the multi-channel accumulation along the spatial dimension, obtaining the theoretical output response of the multi-channel accumulation algorithm along the spatial dimension for the k-th frame. for ； N represents the total number of radar nodes. This represents the output of a GRFT transmit / receive channel, where E represents the electromagnetic wave energy. To accumulate pulse count for coherence, Let m = 1, 2, ..., N, and n = 1, 2, ..., N, be the wavelength of the initial carrier frequency. Indicates in The relative radial distance between the target observed by the signal transmitted by the first node and the signal received by the first node at time 1; Indicates in The relative velocity of the target observed by the signal transmitted by the first node and the signal received by the first node at time 1; Indicates in The relative acceleration of the target observed by the signal transmitted by the first node and the signal received by the first node at time 1; According to formula (40), we get The peak coordinates are , The peak coordinates are The peak envelope difference accumulated across multiple channels between adjacent frames is obtained as follows: ； ； ； express The radial distance between the first node and the target at time t. express The radial velocity between the first node and the target at time t. express The radial acceleration between the first node and the target at time 1; Furthermore, we obtain: ； ； ； in The duration of a single frame; From equation (40) we get peak phase for: ； The theoretical output response of the multi-channel accumulation algorithm along the spatial dimension in the (k+1)th frame peak phase for: ； According to equations (47) and (48), and Peak phase difference The calculation is as follows: ； S6. Using the designed envelope alignment addressing method and phase compensation function, eliminate the envelope difference and phase difference between frames to complete the multi-frame accumulation along the time dimension; define the phase compensation function according to formula (44) and formula (49). for: ； K is the number of observation frames; Step S6: Multi-frame accumulation results along the time dimension Represented as: ； S7. Perform constant false alarm rate (CFAR) detection processing on the multi-frame accumulation results along the time dimension obtained in step S6 to obtain the target detection results.

2. The method for detecting multi-channel, multi-frame signal accumulation in distributed coherent MIMO radar according to claim 1, characterized in that, The process of establishing the echo signal model in step S1 is as follows: A1. The radar transmits orthogonal frequency division multiplexed signals. The transmitted signal of the m-th node is denoted as: ； in, The initial carrier frequency of the radar. The waveforms are orthogonal, and t represents fast time. A2, the delayed echo of the q-th pulse in the k-th frame transmitted and received by m is represented as: ； in, Indicates in The relative radial distance of the target observed by the signal transmitted by the m-th node and the signal received by the n-th node at time m, where c is the speed of electromagnetic wave propagation in air; A3. The echo signal of the k-th frame received by the n-th node is represented as: ； A4. Perform down-conversion processing on the echo signal obtained in step A3 to obtain the baseband echo signal: ； in , Indicates the step frequency. .

3. The method for multi-channel, multi-frame signal accumulation and detection in distributed coherent MIMO radar according to claim 2, characterized in that, Step S3 involves constructing the inter-channel echo envelope compensation function as follows: S311. According to the principles of geometric topology, the transformation relationship of the radial distance parameter between node 1 and node n is obtained as follows: ； in, This represents the baseline distance between node 1 and node n. This represents the observation angle of the first node. This represents the angle between the line from node 1 to node n and the x-axis. S312. The conversion relationship between radial velocity and acceleration between the 1st node and the nth node is obtained as follows: ； ； in, This represents the observation angle of the nth node; S313, Taking the k-th frame as an example, according to Peak coordinates , Peak coordinates ; and The peak envelope difference is ； ； ； in, This represents the output of the m transmit and n receive channels of GRFT. Indicates in The relative radial distance of the target observed at time m is the signal transmitted by the m-th node and the signal received by the n-th node. This represents the transformation relationship of the radial distance parameter between the first node and node m. This represents the transformation relationship of the radial distance parameter between the first node and node n. Indicates in The relative velocity of the target observed at time m is the signal transmitted by the m-th node and the signal received by the n-th node. This represents the radial velocity conversion relationship between the 1st node and the mth node. This represents the radial velocity conversion relationship between the 1st node and the nth node. Indicates in The relative radial acceleration of the target observed at time m is the signal transmitted by the m-th node and the signal received by the n-th node. This represents the radial acceleration conversion relationship between the 1st node and the mth node. This represents the radial acceleration conversion relationship between the 1st node and the nth node; S314. Substituting equations (21)-(23) into (24)-(26), we get: ； ； ； in, This represents the angle between the line from node 1 to node m and the x-axis. This represents the observation angle of the m-th node; S315. Based on the results obtained in (27)-(29), construct the inter-channel echo envelope compensation function. : ； in, , , The peak envelope difference, , , , .

4. The method for detecting multi-channel, multi-frame signal accumulation in distributed coherent MIMO radar according to claim 3, characterized in that, Step S3 involves constructing the inter-channel echo phase compensation function as follows: S321, The peak phase is: ； S322, The peak phase is: ； in, The wavelength of the initial carrier frequency; S323, obtained from equations (30) and (31) and The peak phase difference is: ； S324. Substituting equation (27) into equation (32), we get: ； S325. Construct an inter-channel echo phase compensation function based on the peak phase difference. 。

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