A nano-satellite networking radar system for space target detection

Abstract

The present invention relates to a microsatellite networking radar system for space target detection. The main satellite of this system is equipped with a dual-band radar, which simultaneously transmits and receives electromagnetic waves in the C-band and Ku-band; the slave satellites are equipped with dual-band radar receivers to receive C-band and Ku-band signals; each slave satellite performs joint processing of dual polarization and dual bands on the received echo signals to complete rough target detection, intercepts suspicious target signal segments in the echo, and transmits the suspicious target signal segments to the main satellite after BAQ data compression; the main satellite performs joint processing of dual polarization, dual bands, and multiple angles on the echo signals received by itself and the target echoes from the slave satellites to complete fine target detection, thereby obtaining accurate target spatial position information, calculating beam pointing information based on the target spatial position information, and distributing the target position information and beam pointing information to the slave satellites in real time; each satellite performs beam reconstruction according to the received beam pointing information to complete target tracking and estimate target speed and trajectory information.

Description

Technical Field

[0001] The present invention relates to a nano-satellite networking radar system for space target detection, belonging to the field of radar technology. Background Art

[0002] Space target detection can provide a forecast for potential space threats faced by humans and also ensure the safety of human space activities. Compared with detection means such as optical and infrared, radar can detect and track space targets all day and all weather, especially making up for the deficiencies of optical detection means under backlight conditions.

[0003] Most traditional radars are single-station, single-band, and single-polarization radars, and the electromagnetic scattering information obtained for the target is relatively single. Space targets are diverse in type, and some space targets have weak electromagnetic scattering characteristics, especially the backward scattering in the head direction is very weak, and the target echo power is often submerged by noise and clutter, posing a huge challenge to traditional single-station radar detection. In addition, a few space targets have strong electromagnetic deception and interference capabilities, and traditional single-station radars are easily deceived and interfered by such targets. There is an urgent need to explore and research new radar detection technologies to improve the detection and tracking capabilities for space targets with weak scattering, strong deception, and strong interference. Summary of the Invention

[0004] The technical problem solved by the present invention is: overcoming the deficiencies of the prior art, providing a nano-satellite networking radar system for space target detection, and realizing the angular diversity, randomness, and band diversity of target detection.

[0005] The solution to the technical problem of the present invention is: a nano-satellite networking radar system for space target detection, which includes a main satellite and multiple slave satellites, and the main satellite and the slave satellites are time-frequency synchronized; the main satellite is equipped with a dual-band radar, which simultaneously transmits and receives electromagnetic waves in the C band and the Ku band, the polarization mode of the transmitted signal is vertical polarization, and vertical polarization and horizontal polarization signals are received, constituting a single-station, dual-band, and dual-polarization radar system; the slave satellites are equipped with dual-band radar receivers, which receive vertical polarization and horizontal polarization signals in the C band and the Ku band, constituting multiple bistatic, dual-band, and dual-polarization radar systems;

[0006] Each slave satellite performs joint dual-polarization and dual-band processing on the received echo signals to obtain distributed joint processing echo signals, and according to the distributed joint processing echo signals, completes target rough detection, intercepts suspicious target signal segments in the echo, and after compressing the suspicious target signal segments by BAQ data, transmits them to the main satellite;

[0007] The master satellite performs joint processing of dual-polarization, dual-band, and multi-angle on the echo signals received by itself and the target echo signals from the slave satellites to obtain a multi-dimensional information fusion processing signal. Based on the multi-dimensional information fusion processing signal, precise target detection is completed, thereby obtaining accurate target spatial position information. According to the target spatial position information, the beam pointing information is calculated and the target position information and beam pointing information are distributed to the slave satellites in real time; each satellite reconstructs the beam according to the received beam pointing information to complete the tracking of the target and estimate the target speed and trajectory information.

[0008] Preferably, the master satellite and the slave satellites achieve time synchronization by using a two-way single-frequency pseudo-code time synchronization method; frequency synchronization is performed using a two-way radio frequency link.

[0009] Preferably, the data transmission rate from the slave satellite to the master satellite is <10 Mb / s.

[0010] Preferably, the method for the slave satellite to perform dual-polarization and dual-band joint processing on the received echo signal and then perform rough target detection is as follows:

[0011] S401-1: Perform range-direction pulse compression on the received dual-band and dual-polarization echo signals respectively;

[0012] S401-2: Use the method of weighted summation to perform dual-polarization and dual-band joint processing on the echo signal after pulse compression processing; specifically:

[0013]

[0014] where is the distributed joint processing echo signal, w1, w2, w3, w4, w5, w6 are distributed joint processing weight parameters, and satisfy the constraint conditions: w1 + w2 = 1, w3 + w4 = 1, w5 + w6 = 1, n ∈ [1, N], which is the serial number of the slave satellite, and N is the number of slave satellites.

[0015] Preferably, the particle swarm optimization algorithm is used to obtain the optimal values of the distributed joint processing weight parameters to minimize the entropy of the distributed joint processing echo signal where n ∈ [1, N] and N is the number of slave satellites.

[0016] Preferably, the slave satellite uses the CFAR target detection algorithm to perform rough target detection based on the signal after distributed joint processing. The specific method is as follows:

[0017] S402-1: Use the method of parametric statistics to estimate the clutter of the distributed joint processing echo signal and determine the clutter probability density distribution p(x) of the distributed joint processing echo signal;

[0018] S402-2. Determine the threshold T according to the clutter probability density distribution p(x) of the distributed joint processed echo signal according to the formula to satisfy the preset detection false alarm rate P fa ;

[0019] S402-3. Judge the sampled signal x of the distributed joint processed echo signal j . When the sampled signal x j >T, the sampled signal x j belongs to the suspicious target signal segment. If x j <T, the sampled signal x j belongs to clutter, where j is the subscript of the sampling point.

[0020] Preferably, the multi-dimensional information fusion processing steps of the master satellite are as follows:

[0021] S404-1. The master satellite performs range-direction pulse compression on the echo signal it receives and the echo signal from the slave satellite;

[0022] S404-2. Use the method of weighted summation to perform dual-polarization joint processing on the pulse-compressed echo signal;

[0023] S404-3. Perform multi-angle joint processing on the echo signals of the C-band and ku-band after dual-polarization joint processing respectively;

[0024] S404-4. Perform dual-band joint processing on the echo signal after multi-angle joint processing to obtain the multi-dimensional information fusion processing signal.

[0025] Preferably, the method for performing multi-angle joint processing on the echo signal of the C-band or ku-band is:

[0026] Use the space region division BP imaging algorithm and the interpolation algorithm to realize the synchronization of the space phases of the master satellite echo signal and the slave satellite echo signal, and perform coherent accumulation on the synchronized signal;

[0027] The specific steps are as follows:

[0028] S404-3.1. Divide the detection area into grids, each grid representing a spatial position of the target. Then, perform steps S404-3.2 to S404-3.6 on each spatial grid i to obtain the multi-angle joint processing result of the C-band or ku-band target echo signal in the detection area;

[0029] S404-3.2. Calculate the time delay R isis the radial distance of the spatial grid i relative to the main satellite;

[0030] S404-3.3. Calculate the time delay when the spatial grid point i is back-projected into the fast time dimension of the echo signals of each slave satellite. R in are respectively the radial distances of the spatial grid point i relative to the nth slave satellite, where n ∈ [1, N] and N is the number of slave satellites;

[0031] S404-3.4. According to the calculation results of steps S404-3.3 and S404-3.3, perform interpolation processing on the main satellite echo signal and the slave satellite echo signals respectively, find the projection point positions of the spatial grid i in the fast time dimensions of the main satellite echo signal and the slave satellite echo signals, and obtain the corresponding echo signal values;

[0032] S404-3.5. Based on the signal value corresponding to the spatial grid i in the main satellite echo signal, perform phase compensation on the signal values corresponding to the spatial grid i in the echo signals of each slave satellite, so that the signal values corresponding to the spatial grid i in the echo signals of each slave satellite have the same phase as the signal value corresponding to the spatial grid i in the main satellite echo signal;

[0033] The phase compensation factor of the signal value corresponding to the spatial grid i in the echo signals of each slave satellite relative to the signal value corresponding to the spatial grid i in the main satellite echo signal is:

[0034] where f c is the carrier frequency of the C-band signal;

[0035] S404-3.6. Perform coherent superposition on the signal values corresponding to the spatial grid i in the echo signals of each slave satellite and the signal value corresponding to the spatial grid i in the main satellite echo signal to obtain the multi-angle joint processing result of a single spatial grid i.

[0036] Preferably, the dual-band joint processing in step S404-2 is implemented by the method of weighted addition.

[0037] Preferably, the dual-polarization joint processing method in step S404-2 is as follows:

[0038]

[0039] where the subscript a = s represents the echo signal received by the main satellite, a = n represents the echo signal from the slave satellite, b = C represents the C-band echo signal, b = ku represents the ku-band echo signal, γ1, γ2 are dual-polarization weight parameters, n ∈ [1, N], and N is the number of slave satellites.

[0040] Preferably, the method of parallel search is used to determine the dual-polarization weight parameters to make the echo signal after dual-polarization processing have the minimum entropy.

[0041] The main satellite processes the signal based on multi-dimensional information fusion and uses the CFAR target detection algorithm to complete the target precise detection.

[0042] The beneficial effects of the present invention relative to the prior art are:

[0043] (1) The present invention proposes to use multiple distributed micro-nano satellites to carry a networked radar system to synchronously obtain multi-dimensional scattering information of space targets. By multi-dimensional information fusion processing, the SCNR of space targets is improved, the detection and tracking reliability of space targets is greatly improved, the anti-deception and anti-interference capabilities of radar are enhanced, and the target detection and tracking performance is more robust.

[0044] (2) The present invention adopts an on-board processing method that combines distributed joint preprocessing with centralized fusion processing. While ensuring detection reliability, it greatly reduces the pressure of inter-satellite transmission data, reduces the data rate to 10Mbps, and simplifies the inter-satellite link structure of multiple micro-nano satellites.

[0045] (3) The networked radar of the present invention obtains the target scattering characteristics through a multi-angle synchronous reception method. When a certain angle is deceived or interfered by the target, the remaining angles can still detect and track the space. Therefore, the networked radar has good anti-deception and anti-interference capabilities;

[0046] (4) The networked radar of the present invention adopts only one transmitting system, and the rest are receiving systems, which simplifies the radar subsystem structure; it adopts an on-board processing mode that combines distributed joint preprocessing with centralized fusion processing, which simplifies the inter-satellite link system structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a block diagram of a detection system for a micro-nano satellite network radar system provided by an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of a detection scenario of a micro-nano satellite network radar system provided by an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram of pulse signal transmission and reception of a Venus satellite network radar system provided by an embodiment of the present invention;

[0050] Figure 4 This is a flow chart of radar multi-dimensional information fusion processing provided by an embodiment of the present invention;

[0051] Figure 5 This is a schematic diagram of spatial grid division of a BP algorithm provided by an embodiment of the present invention;

[0052] Figure 6It is a processing flowchart of a micro-nano satellite networking radar system provided by an embodiment of the present invention. Detailed implementation manners

[0053] The present invention will be described below with reference to the accompanying drawings and embodiments.

[0054] In the following description, specific details such as specific technologies and processing methods are presented for the purpose of illustration rather than limitation, so as to understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details.

[0055] The micro-nano satellite networking radar system proposed by the present invention can synchronously obtain multi-dimensional scattering characteristics of space targets, such as multiple angles, multiple bands, and multiple polarizations. Using the multi-dimensional information fusion processing method can greatly improve the SCNR and measurement accuracy of space targets. Adopting a processing mode that combines distributed joint preprocessing and centralized fusion processing greatly reduces the information transmission data rate between multiple micro-nano satellites, simplifies the inter-satellite transmission pressure, and improves the information timeliness. Compared with traditional single-station radars, this micro-nano satellite networking radar has a longer detection range, stronger anti-stealth, anti-jamming, and anti-deception capabilities, and can greatly improve the detection and tracking performance of space targets.

[0056] This embodiment provides a micro-nano satellite networking radar system for space target detection. Refer to Figure 1 , which is an illustration diagram of an embodiment of a micro-nano satellite networking radar system for space target detection in this embodiment. This networking radar system mainly includes a main satellite and multiple slave satellites, and the main satellite and slave satellites are time-frequency synchronized; the main satellite is equipped with a dual-band radar, which simultaneously transmits and receives electromagnetic waves in the C-band and Ku-band, the polarization mode of the transmitted signal is vertical polarization, and it receives vertical polarization and horizontal polarization signals, constituting a single-station, dual-band, dual-polarization radar system; the slave satellites are equipped with dual-band radar receivers, which receive vertical polarization and horizontal polarization signals in the C-band and Ku-band, constituting multiple bistatic, dual-band, dual-polarization radar systems;

[0057] Each slave satellite performs dual-polarization and dual-band joint processing on the received echo signals to obtain distributed joint processing echo signals. Based on the distributed joint processing echo signals, rough target detection is completed, the suspicious target signal segments in the echo are intercepted, and the suspicious target signal segments are transmitted to the main satellite after BAQ data compression;

[0058] The master satellite performs joint processing of dual-polarization, dual-band, and multi-angle on the echo signals received by itself and the target echoes from the slave satellites, obtains a multi-dimensional information fusion processing signal, completes fine detection of the target based on the multi-dimensional information fusion processing signal, thereby obtaining accurate target spatial position information, calculates the beam pointing information according to the target spatial position information, and distributes the target position information and beam pointing information to the slave satellites in real time; each satellite performs beam reconstruction according to the received beam pointing information, completes the tracking of the target, and estimates the target speed and trajectory information. Compared with traditional single-station radars, this nano-satellite networking radar has stronger anti-stealth and anti-deception capabilities and has important application prospects in the field of long-distance detection applications of future space debris, space vehicles, and other targets.

[0059] As Figure 1 shown, this networking radar system consists of a master satellite and multiple slave satellites10;

[0060] The master satellite is equipped with a dual-band radar for signal transmission and reception, and the slave satellites are equipped with dual-band radar receivers20, forming multiple bistatic angle detections to achieve angle diversity, randomness, and band diversity in target detection;

[0061] By multiple satellites simultaneously receiving dual-band, dual-polarization target echo signals, multi-dimensional target echo signals30 are obtained;

[0062] The master satellite and the slave satellites achieve time-frequency synchronization40, and store and process the echo data50;

[0063] Real-time data transmission60 is carried out between the master satellite and the slave satellites.

[0064] Specifically, referring to Figure 2 , the networking radar system consists of a master satellite and multiple slave satellites10; the master satellite is equipped with a dual-band radar for signal transmission and reception, and the slave satellites are equipped with dual-band radar receivers20, forming a "one-transmitter and multiple-receivers" space target detection system for single-station and multiple bistatic angle detections to achieve angle diversity, randomness, and band diversity in target detection, and obtain the scattering characteristics of space targets from multiple angles and multiple bands; after the master satellite emits a pulse signal, by multiple satellites simultaneously receiving dual-band, dual-polarization target echo signals, multi-dimensional target echo signals30 are obtained, including multi-angle, dual-band (C and Ku bands), dual-polarization (V and H polarizations) multi-dimensional target echo signals; then the master satellite and the slave satellites achieve time-frequency synchronization40, and then store and process the echo signals50, where the slave satellites perform distributed joint preprocessing on the echo signals, and the master satellite performs multi-dimensional information fusion processing on the echo signals; real-time data transmission60 is carried out between the master satellite and the slave satellites, including the slave satellites compressing the echo signals after distributed joint preprocessing and transmitting them to the master satellite in real time through the inter-satellite link, and the master satellite distributing the target information obtained after multi-dimensional information fusion processing to each slave satellite in real time, finally realizing beam reconstruction and target tracking.

[0065] Further, referring to Figure 3 , the target multi-dimensional echo signal 30 is obtained, including:

[0066] The dual-band radar carried by the main satellite serves as the only signal transmitter in the system, transmitting continuous pulse signals with carrier frequencies in the C-band and Ku-band, and the polarization mode is V polarization, the pulse width is 1 - 100 μs, and there is a transmission time interval of 1 - 2 μs between the C-band and Ku-band signals.

[0067] Meanwhile, the main satellite serves as a signal receiver and can simultaneously receive V and H dual-polarization echo signals, constituting a single-station, dual-band, dual-polarization radar system;

[0068] The slave satellite serves as a signal receiver and can simultaneously receive V and H dual-polarization echo signals after receiving the signal reception time synchronization signal from the main satellite, constituting multiple multi-station, dual-band, dual-polarization radar systems;

[0069] The networked radar system forms the multi-dimensional echo signal of the target by receiving dual-band, dual-polarization signals of V and H polarizations in the C-band and V and H polarizations in the Ku-band from multiple angles respectively.

[0070] Further, the main satellite and the slave satellite achieve time synchronization by using the bidirectional single-frequency pseudo-code time synchronization method; frequency synchronization 40 is performed using a bidirectional radio frequency link, including:

[0071] Using the bidirectional single-frequency pseudo-code time synchronization technology, the same ranging code is modulated on two different carriers, and then the pseudo-code phase measurement values and carrier phase measurement values of the two carriers are respectively solved by the receiving end, and through calculation, high-precision distance measurement values and time difference measurement values are obtained, and a time synchronization accuracy better than 1 ns can be achieved;

[0072] Phase synchronization is performed using a bidirectional radio frequency link. The receiving end first sends its generated local carrier frequency signal to the transmitting end. After receiving the carrier, the transmitting end uses it as the carrier of the radar signal and simultaneously coherently forwards it back to the radar receiving end. The receiving end can calculate the Doppler frequency shift based on the local carrier frequency signal and the received carrier signal to achieve frequency synchronization.

[0073] Furthermore, real-time data transmission 60 is performed between the master satellite and the slave satellites, including: the slave satellites perform distributed joint preprocessing on the received echo signals, complete coarse target detection, intercept suspicious target signal segments, and after BAQ data compression, greatly reduce the data volume and transmit it to the master satellite, so that the data transmission rate < 10 Mb / s, meeting the requirements of real-time data transmission; the master satellite performs multi-dimensional information fusion processing on the received echo signals from the slave satellites and completes coarse target detection, thereby obtaining accurate target position and velocity information; the master satellite distributes the target information and beam pointing information to each slave satellite in real time, and each satellite realizes target tracking through beam reconstruction.

[0074] This embodiment also provides a method for multi-dimensional information fusion processing. Refer to Figure 4 and Figure 6 , which is a schematic diagram of the implementation process of an embodiment of a method for multi-dimensional information fusion processing of radar target echo signals in this embodiment, including the following steps:

[0075] Step S401, the slave satellites perform joint processing on the received dual-band and dual-polarization echo signals to complete the distributed joint preprocessing of the echo signals;

[0076] Step S402, perform coarse target detection on the echo signals after distributed joint preprocessing;

[0077] Step S403, according to the coarse target detection result, intercept suspicious target signal segments and transmit them to the master satellite;

[0078] Step S404, the master satellite performs multi-dimensional information fusion processing on the received echo signals from the slave satellites;

[0079] Step S405, perform fine target detection on the echo signals after multi-dimensional information fusion processing to obtain accurate target information;

[0080] Step S406, the master satellite distributes the target information and beam pointing information to each slave satellite, and each satellite realizes target tracking through beam reconstruction, estimating the target speed and trajectory information.

[0081] The slave satellites in Step S401 perform joint processing on the received dual-band and dual-polarization echo signals to complete the distributed joint preprocessing of the echo signals. The specific implementation process includes:

[0082] Step S401-1, the slave satellites perform range-direction pulse compression on the received dual-band and dual-polarization echo signals respectively to improve the echo signal-to-noise ratio;

[0083] Step S401-2, perform dual-band and dual-polarization joint processing on the echo signals after pulse compression processing. Here, the method of weighted summation can be used to achieve this.

[0084] In this embodiment, the master satellite transmits C and Ku dual-band V-polarized pulse signals, and each slave satellite receives C and Ku dual-band, H and V dual-polarized echo signals; for the nth slave satellite, four echo signals are received, namely: H and V polarized echo signals in the C band, S rn,CVH and S rn,CVV , H and V polarized echo signals in the Ku band, S rn,KuVH and S rn,KuVV ; First, through the time-frequency synchronization between the slave satellite and the master satellite, range-direction pulse compression is performed on the four echo signals received by the slave satellite to improve the echo signal-to-noise ratio; then, dual-polarization and dual-band joint processing is performed on the echo signals after pulse compression processing.

[0085] Exemplarily, the range-direction pulse compression is achieved by convolving the echo signal with the pulse response of the matched filter . According to the properties of the Fourier transform, convolution in the time domain is equivalent to multiplication in the frequency domain:

[0086] S n,CVH (f,t m ) = S rn,CVH (f,t m )·H(f)

[0087] where is the fast time, t m = mT r (m = 0, 1, … M - 1) is the slow time, T r is the pulse repetition period, M is the number of pulses, S rn,CVH (f,t m ) is the Fourier transform of the echo signal in the fast time dimension, H(f) is the Fourier transform of , according to the matched filtering theory, is the complex conjugate of the transmitted signal, S n,CVH (f,t m ) is the echo signal after pulse compression processing, and its time-domain echo signal can be obtained through the inverse Fourier transform:

[0088] Then, dual-band and dual-polarization joint processing is performed on the echo signals after pulse compression processing. Here, the following weighted addition method can be adopted:

[0089]

[0090] Among them, w1, w2, w3, w4, w5, and w6 are distributed joint processing weight parameters, and satisfy the constraint conditions: w1 + w2 = 1, w3 + w4 = 1, w5 + w6 = 1, n ∈ [1, N], where n is the serial number of the slave satellite, and N is the number of slave satellites. That is, first perform weighted addition on the dual-polarization echo signals, and then perform weighted addition on the dual-band echo signals. is the echo signal after dual-polarization and dual-band distributed joint preprocessing; to obtain the maximum target information volume, the information entropy is introduced here, and it is required that the entropy of is the smallest, and the definition of entropy is:

[0091]

[0092] Among them, p k is the probability of the possible value a k of the discrete random variable X appearing; through certain optimization methods, such as using the particle swarm optimization algorithm to obtain the optimal values of the distributed joint processing weight parameters, so that the entropy of the distributed joint processing echo signal is the smallest, thereby obtaining the maximum target information volume.

[0093] The slave satellite performs coarse target detection on the signal after distributed joint processing by using the CFAR target detection algorithm. The specific method is as follows:

[0094] S402-1. Adopt the method of parametric statistics to estimate the clutter of the distributed joint processing echo signal and determine the clutter probability density distribution p(x) of the distributed joint processing echo signal;

[0095] S402-2. According to the clutter probability density distribution p(x) of the distributed joint processing echo signal, determine the threshold T according to the formula so that it satisfies the preset detection false alarm rate P fa ;

[0096] S402-3. Judge the sampling signal x of the distributed joint processing echo signal. When the sampling signal x j > T, the sampling signal x j belongs to the suspicious target signal segment. When x j < T, the sampling signal x j belongs to the clutter, and j is the sampling point subscript. j

[0097] In this embodiment, the CFAR target detection algorithm is used to implement rough target detection. Considering multiple targets and the large contrast in the strength of multiple target signals, in order to reduce the missed detection rate, a sliding window can be set here, including a target window, a protection window, and a background window. The size of the target window is set according to the prior knowledge of the target. Generally, the size of the target window is twice the size of the target. The half-width of the protection window is generally 2-3 resolution units larger than the half-width of the target window, and the half-width of the background window is generally 2-3 resolution units larger than the half-width of the protection window. The background window is used to estimate the clutter distribution, and the protection window is to prevent target information from leaking into the background window to affect the accuracy of clutter estimation. The echo signal is completed by moving the sliding window: for detection, and the moving step size is one resolution unit.

[0098] In each sliding window, the clutter is estimated by the background window to determine the clutter probability density distribution: p(x). Here, the method of parametric statistics is used to implement clutter estimation, that is, by using a typical clutter probability density distribution model to fit the background window clutter data and giving the fitting error statistic:

[0099]

[0100] where N is the clutter intensity range, p(i) is the probability density of the actual clutter with intensity i, is the probability density of the clutter model with intensity i; the smaller the fitting error statistic, the better the fitting effect, and then the clutter probability density distribution model with the best fitting effect is selected. Typical clutter probability density distribution models include Gaussian distribution model, log-normal distribution model, Weibull distribution model, K-distribution model, etc.

[0101] After obtaining the clutter probability density distribution: p(x), the false alarm rate: P fa is set, and then the detection threshold T is adaptively determined: The P fa set here is relatively high to further reduce the missed detection rate.

[0102] Target detection is performed on the signal within the sliding window. When x i >T, it is a target, and when x i <T, it is clutter.

[0103] Finally, by moving the sliding window, the echo signal: is completed for rough target detection, and then the suspicious target area is determined.

[0104] As described in step S402, according to the rough target detection result, the suspicious target signal segment is intercepted and transmitted to the main satellite. The specific implementation is as follows: According to the rough target detection result, the echo signal for distributed joint preprocessing is determined: For the suspicious target area, find the corresponding area in the original echo signal, intercept it, and transmit it to the main satellite.

[0105] In step S404, the main satellite performs multi-dimensional information fusion processing on the echo signals it receives from the slave satellites. The specific implementation process includes:

[0106] Step S404-1: The main satellite performs range-direction pulse compression on the echo signals it receives and the echo signals from the slave satellites to improve the echo signal-to-noise ratio.

[0107] Step S404-2: Perform dual-polarization joint processing on the echo signals after pulse compression processing. The weighted addition method can be used:

[0108]

[0109] Among them, the subscript a = s represents the echo signal received by the main satellite, a = n (n = 1, 2,..., N) represents the echo signals from each slave satellite, b = C represents the C-band echo signal, b = ku represents the ku-band echo signal, and γ1, γ2 are dual-polarization weight parameters. The dual-polarization weight parameters can be determined by the parallel search method, so that the echo signal after dual-polarization processing has the minimum entropy, thereby obtaining the maximum target information volume, n ∈ [1, N], and N is the number of slave satellites;

[0110] Step S404-3: Perform multi-angle joint processing on the C-band and ku-band echo signals after dual-polarization joint processing respectively. Here, the spatial region division BP imaging algorithm and the interpolation algorithm are used to achieve the spatial frequency synchronization of different radar echo signals and obtain the echo signal with the maximum signal-to-noise ratio: S C (R i ,t m ),S ku (R i ,t m );

[0111] Step S404-4: Perform dual-band joint processing on the echo signals after multi-angle joint processing to obtain the multi-dimensional information fusion processing signal. Here, the weighted addition method is still used to obtain the echo signal with high signal-to-noise ratio and high target information volume: S(R i ,t m ).

[0112] In this embodiment, the main satellite first performs range-direction pulse compression on the echo signals it receives and the echo signals from the slave satellites to improve the echo signal-to-noise ratio. The specific method is the same as that in step S401-1; then, perform dual-polarization joint processing on the echo signals after pulse compression processing. The weighted addition method can be used:

[0113]

[0114] Among them, the subscript a = s represents the echo signal received by the main satellite, a = n (n = 1, 2,..., N) represents the echo signals from each slave satellite, b = C represents the C-band echo signal, b = ku represents the ku-band echo signal, and γ1, γ2 are weight parameters. The weight parameters can be determined by the parameter search method to make have the minimum entropy, so as to obtain the maximum target information volume; furthermore, the echo signals of the C-band and ku-band after dual-polarization joint processing are respectively subjected to multi-angle joint processing, which is realized here by using the spatial region division BP imaging algorithm and the interpolation algorithm to achieve the spatial frequency synchronization of different radar echo signals and obtain the echo signal with the maximum signal-to-noise ratio:

[0115] The method for multi-angle joint processing of the echo signal of the C-band or ku-band is as follows:

[0116] Adopt the spatial region division BP imaging algorithm and the interpolation algorithm to realize the synchronization of the spatial phases of the main satellite echo signal and the slave satellite echo signal, and perform coherent accumulation on the synchronized signals;

[0117] The specific steps are as follows:

[0118] S404-3.1. Divide the detection area into grids. Each grid represents a spatial position of the target. Then, for each spatial grid i, execute steps S404-3.2 to S404-3.6 to obtain the multi-angle joint processing results of the C-band or ku-band target echo signals in the detection area;

[0119] S404-3.2. Calculate the time delay when the spatial grid point i is back-projected into the fast time dimension of the main satellite echo signal R is is the radial distance of the spatial grid i relative to the main satellite;

[0120] S404-3.3. Calculate the time delay when the spatial grid point i is back-projected into the fast time dimension of each slave satellite echo signal R in are the radial distances of the spatial grid point i relative to the nth slave satellite respectively, n ∈ [1, N], and N is the number of slave satellites;

[0121] S404-3.4. According to the calculation results of steps S404-3.2 and S404-3.3, perform interpolation processing on the main satellite echo signal and the slave satellite echo signal respectively, find the projection point positions of the spatial grid i in the fast time dimensions of the main satellite echo signal and the slave satellite echo signal, and obtain the corresponding echo signal values;

[0122] S404-3.5. Based on the signal value corresponding to the spatial grid i in the main satellite echo signal, perform phase compensation on the signal values corresponding to the spatial grid i in the echo signals of each slave satellite, so that the signal values corresponding to the spatial grid i in the echo signals of each slave satellite have the same phase as the signal value corresponding to the spatial grid i in the main satellite echo signal;

[0123] The phase compensation factor of the signal value corresponding to the spatial grid i in the echo signals of each slave satellite relative to the signal value corresponding to the spatial grid i in the main satellite echo signal is:

[0124] where f c is the carrier frequency of the C-band signal;

[0125] S404-3.6. Coherently superimpose the signal values corresponding to the spatial grid i in the echo signals of each slave satellite and the signal value corresponding to the spatial grid i in the main satellite echo signal to obtain the multi-angle joint processing result of a single spatial grid i.

[0126] The BP imaging algorithm is essentially an algorithm for point-by-point coherent imaging in the time domain, which can achieve spatial and frequency synchronization of different radar echo signals. The following takes the multi-angle joint processing of C-band echo signals as an example for illustration.

[0127] Specifically, by dividing the detection area into grids and projecting them point by point in reverse onto each echo signal: In and the fast time dimension of, where n = 1, 2,..., N, N is the number of slave satellites, the size of the spatial grid is about 5 - 10m, and each grid represents a spatial position of the target; Exemplarily, see Figure 5 , the distribution of each satellite in space and the corresponding rectangular coordinate system o-xyz, the radial distance of the spatial grid i relative to the main satellite is: R is , and the radial distances relative to each slave satellite are: R i1 , R i2 ,..., R iN , according to the radar target detection theory, the spatial grid i is projected in reverse onto the main satellite echo signal: The corresponding time delay is:

[0128]

[0129] That is, the projection point position of the spatial grid i in the fast time dimension is: τ is -t s , where t s is the difference between the start time of the main satellite signal reception and the start time of the signal transmission, c is the propagation speed of electromagnetic waves in vacuum, and the spatial grid i is projected in reverse onto the slave satellite echo signal: Among them, the corresponding time delay is:

[0130]

[0131] That is, the projection point position of the spatial grid i in the fast time dimension is: τ in -t n , where t n is the difference between the signal reception start time and the signal transmission start time of the nth slave satellite. Here, R is , R in , t s , t n can be obtained through the time-frequency and spatial information synchronization between the master satellite and the slave satellite. Thus, the projection point positions of the spatial grid i in each echo signal and in the fast time dimension can be found, and the echo signal values at the corresponding projection points are determined: S s,C (τ is -t s , t m ) and S n,C (τ in -t n , t m );Since in actual processing, the echo signals and are discrete values, and there may be no corresponding values at the corresponding times: τ is -t s and τ in -t n . Therefore, interpolation processing is required. The interpolation here can use the sinc interpolation algorithm, that is, reconstruct the signal through convolution, where the convolution kernel is the sinc function: h(x) = sinc(x) = sin(πx) / (πx). Then the interpolation signal:

[0132]

[0133] is the weighted superposition of all input samples, and g d (i) is the sampling signal; after interpolation, the corresponding values of the corresponding times τ is -t s and τ in -t n can be obtained: S s,C (τ is -t s , t m ) and S n,C (τ in -t n , t m ).

[0134] Further, after determining the projection positions and corresponding signal values of the spatial grid i in the detection area in the fast time dimension of each echo signal and , before performing coherent superposition of the signals at each projection point, phase compensation is required; here, taking the main satellite echo signal as a reference, the echo signals of each slave satellite are phase-compensated so that they have the same phase as the main satellite echo signal. The phase compensation factor of the nth slave satellite relative to the main satellite is:

[0135]

[0136] where f c is the carrier frequency of the C-band signal. Furthermore, for the main satellite echo signal: S s,C (τ is -t s ,t m ) and the echo signals of each slave satellite: S n,C (τ in -t n ,t m ) are coherently superposed:

[0137]

[0138] where S C (τ is -t s ,t m ) is the result of coherent superposition of the back-projected signals of a single spatial grid i. By coherently superposing the back-projected signals of all spatial grids i, the coherent accumulation result of the target echo signal in the detection area is obtained:

[0139]

[0140] where I is the number of spatial grids in the detection area, and S C (R i ,t m ) is the result of multi-polarization and multi-angle multi-dimensional fusion processing of the C-band echo signal.

[0141] Finally, the echo signals after multi-angle joint processing: S C (R i ,t m ) and S ku (R i ,t m ) are subjected to dual-band joint processing. Here, the weighted addition method is still used, and the processing method is similar to the dual-polarization joint processing method in step S404-2, which will not be elaborated here. Finally, an echo signal with high signal-to-noise ratio and high target information content: S(R i ,t m ) is obtained.

[0142] Performing target fine detection on the echo signal after multi-dimensional information fusion processing described in step S405 to obtain accurate target information, the specific implementation is as follows: According to the CFAR target detection algorithm, first, for the echo signal after multi-dimensional information fusion processing: S(R i ,t m ), clutter estimation is performed, and the false alarm rate is set: P fa . According to: , the detection threshold T is calculated. Finally, target detection is performed on S(R i ,t m ) to determine the target position information.

[0143] The master satellite described in step S406 distributes the target information and beam pointing information to each slave satellite. Each satellite realizes target tracking through beam reconstruction and estimates the target speed and trajectory information. The specific implementation is as follows: The master satellite realizes high-performance space target detection and accurate estimation of the spatial position information of the target through multi-dimensional information fusion processing and CFAR target detection. Then, it distributes the position information of the target to each slave satellite. Each satellite adjusts the beam pointing according to the motion information of the target to realize target tracking, and further estimates the target speed and trajectory information.

[0144] Although the present invention has been disclosed above with preferred embodiments, it is not used to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modification, equivalent change, and modification made to the above embodiments according to the technical essence of the present invention without departing from the technical solution of the present invention all fall within the protection scope of the technical solution of the present invention.

Claims

1. A nano-satellite networking radar system for space target detection, characterized in that It includes a main satellite and multiple slave satellites, and the main satellite and the slave satellites are time-frequency synchronized. The main satellite is equipped with a dual-band radar, which simultaneously transmits and receives electromagnetic waves in the C-band and Ku-band. The polarization mode of the transmitted signal is vertical polarization, and it receives vertical polarization and horizontal polarization signals, constituting a single-station, dual-band, dual-polarization radar system. The slave satellites are equipped with dual-band radar receivers, which receive vertical polarization and horizontal polarization signals in the C-band and Ku-band, constituting multiple bistatic, dual-band, dual-polarization radar systems. Each slave satellite performs joint processing of dual polarization and dual bands on the received echo signals to obtain distributed joint processing echo signals. Based on the distributed joint processing echo signals, rough target detection is completed, the suspicious target signal segments in the echo are intercepted, and the suspicious target signal segments are transmitted to the main satellite after BAQ data compression. The main satellite performs joint processing of dual polarization, dual bands, and multiple angles on the echo signals received by itself and the target echoes from the slave satellites to obtain multi-dimensional information fusion processing signals. Based on the multi-dimensional information fusion processing signals, precise target detection is completed, so as to obtain accurate target spatial position information. According to the target spatial position information, the beam pointing information is calculated and the target position information and beam pointing information are distributed to the slave satellites in real time. Each satellite performs beam reconstruction according to the received beam pointing information to complete the tracking of the target and estimate the target speed and trajectory information.

2. The micro-nano satellite networking radar system for space target detection according to claim 1, characterized in that The main satellite and the slave satellites use a two-way single-frequency pseudo-code time synchronization method to achieve time synchronization; a two-way radio frequency link is used for frequency synchronization.

3. The microsatellite networking radar system for space target detection according to claim 1, characterized in that The method for the slave satellite to perform joint processing of dual polarization and dual bands on the received echo signals and then perform rough target detection is as follows: S401-1. Perform range-direction pulse compression on the received dual-band, dual-polarization echo signals respectively. S401-2. Use the method of weighted summation to perform joint processing of dual polarization and dual bands on the echo signals after pulse compression processing; specifically: Among them, for distributed joint processing of echo signals, w1, w2, w3, w4, w5, w6 are distributed joint processing weight parameters, and satisfy the constraint conditions: w1 + w2 = 1, w3 + w4 = 1, w5 + w6 = 1, n ∈ [1, N], where n is the serial number of the slave satellite, and N is the number of slave satellites.

4. The micro-nano satellite networking radar system for space target detection according to claim 3, wherein The particle swarm optimization algorithm is used to obtain the optimal values of the distributed joint processing weight parameters, so as to minimize the entropy of the distributed joint processing echo signal where \(n\in[1,N]\) and \(N\) is the number of slave satellites.

5. The microsatellite networking radar system for space target detection according to claim 1, characterized in that The slave satellite uses the CFAR target detection algorithm to perform rough target detection based on the signals after distributed joint processing.

6. The microsatellite networking radar system for space target detection according to claim 1, characterized in that The steps for the main satellite to perform multi-dimensional information fusion processing are as follows: S404-1. The main satellite performs range-direction pulse compression on the echo signals it receives and the echo signals from the slave satellites. S404-2. Use the method of weighted summation to perform joint dual-polarization processing on the echo signals after pulse compression processing. S404-3. Perform joint multi-angle processing on the echo signals of the C-band and Ku-band after joint dual-polarization processing respectively. S404-4. Perform joint dual-band processing on the echo signals after multi-angle joint processing to obtain multi-dimensional information fusion processing signals.

7. The micro-nano satellite networking radar system for space target detection according to claim 1, characterized in that The method for performing joint multi-angle processing on the echo signals of the C-band or Ku-band is: Use the spatial region division BP imaging algorithm and the interpolation algorithm to achieve the synchronization of the spatial phases of the main satellite echo signals and the slave satellite echo signals, and perform coherent accumulation on the synchronized signals. The specific steps are as follows: S404-3.

1. Divide the detection area into grids, where each grid represents a spatial position of the target. Then, for each spatial grid i, perform steps S404-3.2 to S404-3.6 to obtain the multi-angle joint processing result of the target echo signals in the C-band or Ku-band within the detection area; S404-3.

2. Calculate the time delay when the spatial grid point i is back-projected onto the fast time dimension of the main star echo signal R is is the radial distance of the spatial grid i relative to the main star; S404 - 3.

3. Calculate the time delay when the spatial grid point i is back - projected onto the fast - time dimension of the echo signals of each slave satellite R in They are respectively the radial distances of the spatial grid point i relative to the n - th slave satellite, where n ∈ [1, N] and N is the number of slave satellites; S404-3.

4. According to the calculation results of step S404-3.3, perform interpolation processing on the main satellite echo signal and the slave satellite echo signal respectively to find the projection point positions of the spatial grid i in the fast time dimension of the main satellite echo signal and the slave satellite echo signal, and obtain the corresponding echo signal values; S404-3.

5. Based on the signal value corresponding to the spatial grid i in the main satellite echo signal, perform phase compensation on the signal values corresponding to the spatial grid i in the slave satellite echo signals, so that the signal values corresponding to the spatial grid i in the slave satellite echo signals have the same phase as the signal value corresponding to the spatial grid i in the main satellite echo signal; The phase compensation factor of the signal value corresponding to the spatial grid i in each slave satellite echo signal relative to the signal value corresponding to the spatial grid i in the master satellite echo signal is: Among them, f c is the carrier frequency of the C-band signal; S404-3.

6. Perform coherent superposition on the signal values corresponding to the spatial grid i in the slave satellite echo signals and the signal value corresponding to the spatial grid i in the main satellite echo signal to obtain the multi-angle joint processing result of a single spatial grid i.

8. The micro-nano satellite networking radar system for space target detection according to claim 6, characterized in that The dual-polarization joint processing method in step S404-2 is as follows: Among them, the subscript a = s represents the echo signal received by the main satellite, a = n represents the echo signal from the slave satellite, b = C represents the C-band echo signal, b = ku represents the Ku-band echo signal, γ1, γ2 are dual-polarization weight parameters, n ∈ [1, N], and N is the number of slave satellites.

9. The microsatellite networking radar system for space target detection according to claim 8, characterized in that Use the parallel search method to determine the dual-polarization weight parameters to minimize the entropy of the echo signal after dual-polarization processing.

10. The microsatellite networking radar system for space target detection according to claim 1, characterized in that: The main satellite processes the signal based on multi-dimensional information fusion and completes the target fine detection using the CFAR target detection algorithm.

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