Method, device and equipment for fast detection of maneuvering targets by random pri radar

Abstract

The application discloses a method, device and equipment for rapidly detecting a mobile target by using a random PRI radar, and aims at the problem of Doppler ambiguous mobile target detection of an existing coherent radar. The non-uniform sampling scale transformation is used to restore the signal to a uniform sampling signal and simultaneously complete distance correction. The parameter sub-path division search strategy is used to effectively solve the problem that the traditional coherent radar has a large search amount for a non-cooperative target without prior information and has poor real-time processing capability, and the optimal detection performance can be approached with high calculation efficiency.

Description

Technical Field

[0001] This invention belongs to the technical field of radar signal processing, and particularly relates to a method, apparatus and equipment for rapid detection of moving targets by random PRI radar. Background Technology

[0002] Random PRI radar, as a novel radar system, has received continuous attention and research due to its excellent anti-jamming capabilities. Transmitting random PRI signals is an easily implemented anti-jamming technique. By adding random jitter to a fixed pulse repetition interval, it is possible to effectively prevent jammers from intercepting the waveform parameters of the transmitted signal.

[0003] Coherent radar typically improves the output signal-to-noise ratio (SNR) by performing moving target detection (MTD) on the echo pulse train. However, in processing high-speed moving target detection, MTD is limited by the signal's dwell time within a range gate and the target's Doppler frequency broadening. Simply increasing the number of accumulated pulses can effectively suppress random modulation noise power, but the number of pulses that can be effectively accumulated does not increase, thus making it difficult to improve the accumulation gain. For random PRI-based radar, due to the non-uniform sampling of the received signal along the Doppler dimension, traditional Doppler phase compensation or time-frequency distribution algorithms are ineffective.

[0004] In 2015, Chen Qian et al. proposed the random pulse repetition interval Radon Fourier transform (RPRI-RFT) algorithm. This algorithm ignores the distance movement caused by random jitter and uses a non-uniformly discrete Fourier transform (NUDFT) to filter the Doppler frequency along the envelope trajectory. However, this method is difficult to solve the problem of time-varying Doppler frequency center shift of maneuvering targets.

[0005] To address this, Tian Jing et al. proposed the Radon non-uniformly fractional Fourier transform (RNUFrFT) algorithm. This algorithm constructs a target motion parameter space to search for the distance traveled in each pulse and then uses NUFrFT to accumulate the target's energy. While this algorithm excels in low signal-to-noise ratio scenarios, its computationally complex grid search process makes it unsuitable for real-time processing.

[0006] To address the problem of excessive computation, Liu Zhen et al. proposed using compressed sensing (CS) theory to extract motion parameters of target echoes. However, the iterative optimization of CS has high requirements for SNR and poor performance in low SNR scenarios.

[0007] Based on the above analysis, it is necessary to study an algorithm with range correction, Doppler correction and phase jitter elimination capabilities to achieve coherent accumulation and further improve target detection performance. Summary of the Invention

[0008] The purpose of this invention is to provide a method, apparatus, and device for rapid detection of moving targets using a random PRI radar, which effectively resolves the contradiction between the number of search spaces and search accuracy in traditional coherent radar, and achieves a good balance between computational efficiency and target detection performance.

[0009] To solve the above problems, the technical solution of the present invention is as follows:

[0010] A method for rapid detection of moving targets using a random PRI radar includes:

[0011] The sampled baseband echo signal is down-converted and pulse compressed to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information.

[0012] The two-dimensional pulse compression signal is subjected to FFT transformation along fast time to obtain the frequency domain pulse compression signal; the frequency domain pulse compression signal is subjected to non-uniform sampling scale transformation to eliminate the linear distance movement of the target caused by velocity;

[0013] The parameter subpath partitioning search is performed on the signal after non-uniform sampling scale transformation to obtain the estimated values ​​of the target's higher-order motion parameters, and a higher-order phase compensation function is constructed based on the estimated values ​​to eliminate Doppler motion;

[0014] The signal after high-order phase compensation is subjected to MTD detection, and the signal is accumulated in the range-Doppler domain;

[0015] A constant false alarm rate (CFAR) test is performed on the parameter space where the energy accumulation peak in the range-Doppler domain is located. If the peak value of the peak exceeds a given threshold, the existence of a target is determined. The initial radial distance and radial velocity of the detected target are estimated based on the location of the accumulated peak.

[0016] Preferably, the step of performing parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation to obtain estimated values ​​of the target's higher-order motion parameters further includes:

[0017] Determine the search range and search interval for the first-order and second-order accelerations of the pulse compression signal after non-uniform sampling scale transformation;

[0018] N search paths are extracted from the search parameter domain at equal intervals. On each search path, the search value of the first-order acceleration remains unchanged. N one-dimensional searches are performed along the direction of the second-order acceleration according to the preset higher-order motion parameter estimation formula, and the search results are projected onto the search parameter domain.

[0019] Obtain the local maximum value on each search path and record the location coordinates of the local maximum value. Filter the location coordinates of the local maximum value to obtain the local optimum. Fit the coordinates of the local optimum using the least squares method to form a linear function line in the search parameter domain, which is denoted as the global optimal search path.

[0020] A one-dimensional search is performed along the global optimal search path according to the preset higher-order motion parameter estimation formula to obtain the estimated values ​​of the target higher-order motion parameters.

[0021] Preferably, the step of filtering the location coordinates of the local maximum to obtain the local maximum further includes:

[0022] Calculate the mean gradient change of the coordinates of each local maximum value along the second-order acceleration dimension;

[0023] The algorithm polls and compares the gradient value of the local maximum coordinates of each search path with a preset gradient change threshold. If the gradient value is less than the preset gradient change threshold, the local maximum coordinates are stored in the coordinate matrix. If the gradient value is greater than or equal to the preset gradient change threshold, the polling stops and the remaining local maximums are discarded.

[0024] Preferably, the preset higher-order motion parameter estimation formula is:

[0025]

[0026] in, This is an estimate of the first-order acceleration. This is an estimate of the second-order acceleration. The search value for first-order acceleration. The search value for second-order acceleration. This is a uniformly sampled slow time series that has been recalibrated after a non-uniform sampling scale transformation. The pulse compression signal after non-uniform sampling scale transformation, P(t) n ) is the phase compensation function.

[0027] Ideally, obtain the first-order acceleration estimate. and second-order acceleration estimates Then, the corresponding phase compensation function is:

[0028]

[0029] The phase compensation function is multiplied by the pulse compression signal after non-uniform sampling scale transformation, and an FFT transformation is performed along the slow time to obtain the accumulation of the target in the range-Doppler domain.

[0030] Preferably, the non-uniform sampling scale transformation is defined as:

[0031]

[0032] in, It is a non-uniform slow time series. For random time offsets applied to slow-time pulse trains, the range is typically [missing information]. The uniform distribution, and , m is the slow time series index, f is the carrier frequency, and f is the fast time frequency. This is a uniformly sampled slow time series that has been recalibrated after a non-uniform sampling scale transformation;

[0033] pass The introduction of [a certain technology] solves the phase fluctuation between signal pulse trains.

[0034] A device for rapid detection of moving targets using a random PRI radar, comprising:

[0035] The data preprocessing module is used to perform down-conversion and pulse compression processing on the sampled baseband echo signal to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information.

[0036] The distance correction module is used to perform FFT transformation on the two-dimensional pulse compression signal along fast time to obtain the frequency domain pulse compression signal; and to perform non-uniform sampling scale transformation on the frequency domain pulse compression signal to eliminate the linear distance movement of the target caused by velocity.

[0037] The Doppler correction module is used to perform parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation, obtain the estimated values ​​of the target's higher-order motion parameters, and construct a higher-order phase compensation function based on the estimated values ​​to eliminate Doppler motion.

[0038] The target detection module is used to perform MTD detection on the signal after high-order phase compensation, and accumulate the signal into the range-Doppler domain; it performs constant false alarm detection on the parameter space where the energy accumulation peak in the range-Doppler domain is located, and if the peak value of the peak exceeds a given threshold, it determines that a target exists; and it obtains the estimated initial radial distance and radial velocity of the detected target based on the location of the accumulated peak.

[0039] Preferably, the Doppler correction module is configured to perform the following functions:

[0040] Determine the search range and search interval for the first-order and second-order accelerations of the pulse compression signal after non-uniform sampling scale transformation;

[0041] N search paths are extracted from the search parameter domain at equal intervals. On each search path, the search value of the first-order acceleration remains unchanged. N one-dimensional searches are performed along the direction of the second-order acceleration according to the preset higher-order motion parameter estimation formula, and the search results are projected onto the search parameter domain.

[0042] Obtain the local maximum value on each search path and record the location coordinates of the local maximum value. Filter the location coordinates of the local maximum value to obtain the local optimum. Fit the coordinates of the local optimum using the least squares method to form a linear function line in the search parameter domain, which is denoted as the global optimal search path.

[0043] A one-dimensional search is performed along the global optimal search path according to the preset higher-order motion parameter estimation formula to obtain the estimated values ​​of the target higher-order motion parameters.

[0044] A device for rapid detection of maneuvering targets using random PRI radar includes a memory and a processor. The memory stores computer-readable instructions, which, when executed by the processor, cause the processor to perform steps in a method for rapid detection of maneuvering targets using random PRI radar according to an embodiment of the present invention.

[0045] A storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform steps in a method for rapid detection of maneuvering targets by random PRI radar according to an embodiment of the present invention.

[0046] Because the present invention adopts the above technical solution, it has the following advantages and positive effects compared with the prior art:

[0047] 1) The method for rapid detection of maneuvering targets by random PRI radar in one embodiment of the present invention addresses the problem of Doppler fuzzy maneuvering target detection in existing coherent radars. It restores the signal to a uniform sampling signal by non-uniform sampling scale transformation and completes range correction at the same time. It effectively solves the problem of large search volume and poor real-time processing capability of traditional coherent radar for non-cooperative targets without prior information by using a parameter sub-path partitioning search strategy. It can approach the optimal detection performance with high computational efficiency.

[0048] 2) The method for rapid detection of maneuvering targets by random PRI radar in one embodiment of the present invention is implemented in a software manner, which can realize real-time calculation and correction during signal processing. The method is simple and easy to implement, involves few hardware devices, and has high reliability. Attached Figure Description

[0049] Figure 1 This is a flowchart of a method for rapid detection of maneuvering targets using a random PRI radar according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the timing of the random PRI radar transmission waveform in one embodiment of the present invention;

[0051] Figure 3 This is a flowchart of the parameter sub-path partitioning search process in one embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of a parameter sub-path partitioning search strategy in one embodiment of the present invention;

[0053] Figure 5 This is a flowchart of the local optimum selection process in one embodiment of the present invention;

[0054] Figure 6 This is a block diagram of a device for rapid detection of maneuvering targets using a random PRI radar according to an embodiment of the present invention;

[0055] Figure 7 This is a schematic diagram of a device for rapid detection of moving targets using a random PRI radar according to an embodiment of the present invention. Detailed Implementation

[0056] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method, apparatus, and device for rapid detection of moving targets using a random PRI radar, as proposed in this invention. The advantages and features of this invention will become more apparent from the following description and claims.

[0057] Example 1

[0058] like Figure 1 As shown in the figure, this embodiment provides a method for rapid detection of maneuvering targets using a random PRI radar, including resampling processing of non-uniformly sampled signals and range correction, as well as search for higher-order motion parameters and phase compensation. The specific implementation steps are as follows:

[0059] S1: Perform down-conversion and pulse compression processing on the sampled baseband echo signal to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information;

[0060] S2: Perform FFT transformation on the two-dimensional pulse compression signal along fast time to obtain the frequency domain pulse compression signal; perform non-uniform sampling scale transformation on the frequency domain pulse compression signal to eliminate the linear distance movement of the target caused by velocity;

[0061] S3: Perform parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation to obtain the estimated values ​​of the target's higher-order motion parameters, and construct a higher-order phase compensation function based on the estimated values ​​to eliminate Doppler motion;

[0062] S4: Perform MTD detection on the higher-order phase-compensated signal and accumulate the signal in the range-Doppler domain;

[0063] S5: Perform constant false alarm detection on the parameter space where the energy accumulation peak in the range-Doppler domain is located. If the peak value of the peak exceeds a given threshold, the existence of a target is determined. And obtain the estimated initial radial distance and radial velocity of the detected target based on the location of the accumulated peak.

[0064] Specifically, in step S1, the radar performs pulse compression on the received baseband echo signal to obtain an envelope trajectory data space containing target information.

[0065] Specifically, the random PRI radar transmits a set of coherent linear frequency modulated signals, the timing diagram of which is shown below. Figure 2 As shown. Assuming a single target exists within the radar detection area, the baseband echo signal received by the radar within one coherent processing interval takes the following form:

[0066] (14)

[0067] in, For complex amplitude values, where c is the pulse width and c is the speed of light. For frequency modulation, B is the signal bandwidth. For carrier frequency, To save time, For non-uniform sampling with slow time, The pulse repetition interval, To satisfy a uniformly distributed random time bias, M is the number of accumulated pulses.

[0068] in, The instantaneous radial distance of the target relative to the radar is expressed in the following form:

[0069] (15)

[0070] In the formula, The initial radial distance to the target. For the target speed, For the target first-order acceleration, The target is the second-order acceleration.

[0071] The baseband echo signal is down-converted and pulse compressed to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information, as follows:

[0072] (16)

[0073] In the formula: Indicates the radar wavelength. The complex amplitude of the signal.

[0074] In step S2, distance correction is performed using a non-uniform sampling scale transformation.

[0075] In the specific implementation process, first perform FFT on equation (16) along the fast time, ignoring higher-order motion components:

[0076] (17)

[0077] In the formula: This represents the distance frequency corresponding to a fast time. .

[0078] In the specific implementation process, a non-uniform sampling scale transformation is performed on equation (17), which is defined as follows:

[0079] (18)

[0080] In the formula, This is a uniformly sampled slow time series that has been recalibrated after a non-uniform sampling scale transformation. The introduction of this technology effectively solved the phase fluctuation problem between pulse trains.

[0081] Substituting equation (18) into equation (17), the pulse compression signal after non-uniform sampling scale transformation can be expressed as:

[0082] (19)

[0083] Using the above method, the linear range travel caused by the target velocity has been eliminated. Performing an IFFT on equation (19) along a fast time frequency, the target energy is concentrated within a single range cell:

[0084] (20)

[0085] In step S3, higher-order motion components are obtained through a search strategy. The search strategy comprises four specific implementation steps, and the filtering part further comprises four specific implementation sub-steps.

[0086] In practical processing, to compensate for the higher-order phase of the target, the following phase compensation function is constructed:

[0087] (twenty one)

[0088] in, and λ represents the search values ​​for the first-order acceleration and the second-order acceleration, respectively, and λ is the radar wavelength.

[0089] Multiplying the above equation by equation (20), when the search parameters are equal to the target true parameters, the higher-order phase terms are compensated, and the accumulated amplitude reaches its maximum value after performing MTD on the compensated signal. Specifically, the parameter estimation process can be as follows:

[0090] (twenty two)

[0091] in, To perform an FFT along the slow time.

[0092] In this embodiment, to improve the computational efficiency of the parameter search process, a parameter sub-path partitioning search strategy is presented. In specific implementation, such as... Figure 3 As shown, it specifically includes:

[0093] S3-1: Determine the search ranges for the first-order acceleration and the second-order acceleration respectively. , The search intervals for first-order acceleration and second-order acceleration are respectively and The number of searches for first-order acceleration and second-order acceleration are respectively and .

[0094] S3-2: By equal intervals ( Extract N search paths from the search parameter domain, such as Figure 3 As shown by the black dashed line in the middle. On each search path, the search value of the first-order acceleration remains unchanged. Along the search direction of the second-order acceleration, N one-dimensional searches are performed according to equation (22), and the search results are projected onto the search parameter domain.

[0095] S3-3: Find the local maximum value on each search path and record its location coordinates, such as Figure 4 As shown by the large circle. By fitting the filtered local optimum coordinates using the least squares method, a linear function line is formed in the search parameter domain, which is the global optimum search path, as shown below. Figure 4 As shown by the thick black solid line.

[0096] S3-4: Perform a one-dimensional search along this globally optimal search path using steps (22). The search sequence for the first-order acceleration remains unchanged from step S1. The search value for the second-order acceleration is calculated by substituting the search values ​​for the first-order acceleration into the fitting function. The globally optimal solution can be obtained through this search, such as... Figure 4 As shown in the middle star shape.

[0097] In actual processing, appropriate filtering is required for the local optima in step S3-3 to remove outliers that deviate significantly from the actual optimal path. The filtering criteria are as follows:

[0098] S3-3-1: First, calculate the mean gradient change of the coordinates of each local optimum in the second-order acceleration dimension:

[0099] (twenty three)

[0100] in, Let be the coordinates of the locally optimal second-order acceleration point on the nth sub-path.

[0101] S3-3-2: Determine the gradient change threshold:

[0102] (twenty four)

[0103] S3-3-3: Polling the stored local optimum coordinate gradient values ​​of each sub-path .when At that time, the coordinates of the local optima of the path are stored in the coordinate matrix. When exists When the polling stops, subsequent polling attempts are discarded. All local optima.

[0104] S3-3-4: Obtain the new coordinate matrix Then, using The coordinates of the points in the graph are used to perform path fitting, and the optimal path is obtained to complete parameter estimation. It should be noted that in this embodiment, a parameter k of 2 to 3 yields the best filtering effect. The flowchart is as follows: Figure 5 As shown.

[0105] In step S4, higher-order phase compensation is used to eliminate Doppler motion and MTD detection is performed on the signal after higher-order phase compensation, and the signal is accumulated in the range-Doppler domain.

[0106] After obtaining the estimates of the first and second order accelerations and Then, the following phase compensation function is constructed:

[0107] (25)

[0108] Multiplying equation (25) by equation (20) and performing a slow-time FFT, the accumulation of the target in the range-Doppler domain can be completed:

[0109] (26)

[0110] In step S5, target extraction and constant false alarm rate (CFAR) detection are performed.

[0111] After accumulating the target energy into a spike, CFAR detection is performed on the range-Doppler domain detection cell map. The amplitude of the constructed echo signal range-Doppler domain detection cell map is used as the detection statistic and compared with a given false alarm probability adaptive detection threshold.

[0112] (27)

[0113] in, This is the detection threshold.

[0114] If the amplitude exceeds a given detection threshold, the target is determined to exist. Based on the location of the energy peak, the initial radial distance and unambiguous velocity of the target can be estimated.

[0115] By following the above steps, the range correction, random phase jitter correction and Doppler correction of the target signal can be completed, and the coherent accumulation results and the estimated values ​​of the target motion parameters can be obtained.

[0116] In summary, this invention relates to a method for rapid detection of maneuvering targets using a random PRI radar. It proposes a definition of non-uniform sampling scale transformation, employing this transformation to restore the signal to a uniformly sampled signal while simultaneously performing range correction. The proposed parametric subpath partitioning search strategy effectively addresses the problems of traditional coherent radars, such as large search volume and poor real-time processing capability for non-cooperative targets without prior information, achieving near-optimal detection performance with high computational efficiency.

[0117] Example 2

[0118] This embodiment provides a device for rapid detection of maneuvering targets using a random PRI radar, implementing the steps of the method for rapid detection of maneuvering targets using a random PRI radar in Embodiment 1 above. Please refer to... Figure 6 The device for the random PRI radar to quickly detect moving targets includes:

[0119] Data preprocessing module 1 is used to perform down-conversion and pulse compression processing on the sampled baseband echo signal to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information;

[0120] The distance correction module 2 is used to perform FFT transformation on the two-dimensional pulse compression signal along fast time to obtain the frequency domain pulse compression signal; and to perform non-uniform sampling scale transformation on the frequency domain pulse compression signal to eliminate the linear distance movement of the target caused by velocity.

[0121] Doppler correction module 3 is used to perform parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation, obtain the estimated values ​​of the target's higher-order motion parameters, and construct a higher-order phase compensation function based on the estimated values ​​to eliminate Doppler motion;

[0122] The target detection module 4 is used to perform MTD detection on the signal after high-order phase compensation, and accumulate the signal into the range-Doppler domain; perform constant false alarm detection on the parameter space where the energy accumulation peak in the range-Doppler domain is located; if the peak value of the peak exceeds a given threshold, it is determined that a target exists; and obtain the estimated values ​​of the initial radial distance and radial velocity of the detected target based on the location of the accumulated peak.

[0123] Furthermore, the Doppler correction module 3 is configured to perform the following functions:

[0124] Determine the search range and search interval for the first-order and second-order accelerations of the pulse compression signal after non-uniform sampling scale transformation;

[0125] N search paths are extracted from the search parameter domain at equal intervals. On each search path, the search value of the first-order acceleration remains unchanged. N one-dimensional searches are performed along the direction of the second-order acceleration according to the preset higher-order motion parameter estimation formula, and the search results are projected onto the search parameter domain.

[0126] Obtain the local maximum value on each search path and record the location coordinates of the local maximum value. Filter the location coordinates of the local maximum value to obtain the local optimum. Fit the coordinates of the local optimum using the least squares method to form a linear function line in the search parameter domain, which is denoted as the global optimal search path.

[0127] A one-dimensional search is performed along the global optimal search path according to the preset higher-order motion parameter estimation formula to obtain the estimated values ​​of the target higher-order motion parameters.

[0128] The functions and implementation methods of the data preprocessing module 1, distance correction module 2, Doppler correction module 3, and target detection module 4 are as described in the above embodiments, and will not be repeated here.

[0129] Example 3

[0130] This embodiment provides a device for rapid detection of moving targets using a random PRI radar. Please refer to [link / reference]. Figure 7The device 500 for rapid detection of moving targets by the random PRI radar can vary considerably depending on its configuration or performance. It may include one or more central processing units (CPUs) 510 (e.g., x86, ARM architecture processors, or FPGAs) and memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) for storing application programs 533 or data 532. The memory 520 and storage media 530 can be temporary or persistent storage. The program stored in the storage media 530 may include one or more modules (not shown in the figure), each module including a series of instruction operations on the device 500 for rapid detection of moving targets by the random PRI radar.

[0131] Furthermore, the processor 510 can be configured to communicate with the storage medium 530 and execute a series of instructions stored in the storage medium 530 on the device 500 for rapid detection of moving targets by the random PRI radar.

[0132] The device 500 for rapid detection of moving targets by random PRI radar may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input / output interfaces 560, and / or one or more operating systems 531, such as Windows Server, Vista, etc.

[0133] Those skilled in the art will understand that Figure 7 The structure of the device for rapid detection of maneuvering targets by random PRI radar shown does not constitute a limitation on the device for rapid detection of maneuvering targets by random PRI radar. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0134] Another embodiment of the present invention also provides a computer-readable storage medium.

[0135] The computer-readable storage medium can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the device method for rapid detection of moving targets by random PRI radar in Embodiment 1.

[0136] If the method for rapid detection of moving targets by random PRI radar is implemented in the form of program instructions and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in software. This computer software is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific identification content executed by the system and device described above can be referred to the corresponding process in the foregoing method embodiments.

[0138] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, if these changes fall within the scope of the claims of the present invention and their equivalents, they shall still fall within the protection scope of the present invention.

Claims

1. A method for rapid detection of moving targets using a random PRI radar, characterized in that, include: The sampled baseband echo signal is down-converted and pulse compressed to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information. The two-dimensional pulse compression signal is subjected to FFT transformation along fast time to obtain the frequency domain pulse compression signal; the frequency domain pulse compression signal is subjected to non-uniform sampling scale transformation to eliminate the linear distance movement of the target caused by velocity; The parameter subpath partitioning search is performed on the signal after non-uniform sampling scale transformation to obtain the estimated values ​​of the target's higher-order motion parameters, and a higher-order phase compensation function is constructed based on the estimated values ​​to eliminate Doppler motion; The signal after high-order phase compensation is subjected to MTD detection, and the signal is accumulated in the range-Doppler domain; A constant false alarm rate (CFAR) test is performed on the parameter space where the energy accumulation peak in the range-Doppler domain is located. If the peak value of the peak exceeds a given threshold, the existence of a target is determined. The initial radial distance and radial velocity of the detected target are estimated based on the location of the accumulated peak. The step of performing parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation to obtain estimated values ​​of the target's higher-order motion parameters further includes: Determine the search range and search interval for the first-order and second-order accelerations of the pulse compression signal after non-uniform sampling scale transformation; N search paths are extracted from the search parameter domain at equal intervals. On each search path, the search value of the first-order acceleration remains unchanged. N one-dimensional searches are performed along the direction of the second-order acceleration according to the preset higher-order motion parameter estimation formula, and the search results are projected onto the search parameter domain. Obtain the local maximum value on each search path and record the location coordinates of the local maximum value. Filter the location coordinates of the local maximum value to obtain the local optimum. Fit the coordinates of the local optimum using the least squares method to form a linear function line in the search parameter domain, which is denoted as the global optimal search path. A one-dimensional search is performed along the global optimal search path according to the preset higher-order motion parameter estimation formula to obtain the estimated values ​​of the target higher-order motion parameters.

2. The method for rapid detection of moving targets using a random PRI radar as described in claim 1, characterized in that, The filtering of the location coordinates of the local maximum to obtain the local maximum point further includes: Calculate the mean gradient change of the coordinates of each local maximum value along the second-order acceleration dimension; The algorithm polls and compares the gradient value of the local maximum coordinates of each search path with a preset gradient change threshold. If the gradient value is less than the preset gradient change threshold, the local maximum coordinates are stored in the coordinate matrix. If the gradient value is greater than or equal to the preset gradient change threshold, the polling stops and the remaining local maximums are discarded.

3. The method for rapid detection of moving targets using a random PRI radar as described in claim 1, characterized in that, The preset high-order motion parameter estimation formula is: in, This is an estimate of the first-order acceleration. This is an estimate of the second-order acceleration. The search value for first-order acceleration. The search value for second-order acceleration. S is a uniformly sampled slow time series that has been recalibrated after a non-uniform sampling scaling transformation. KT (t n P(t) represents the pulse compression signal after non-uniform sampling scale transformation, where τ is the fast time; n ) is the phase compensation function.

4. The method for rapid detection of moving targets using a random PRI radar as described in claim 3, characterized in that, Obtain first-order acceleration estimates and second-order acceleration estimates Then, the corresponding phase compensation function is: in, The phase compensation function is multiplied by the pulse compression signal after non-uniform sampling scale transformation, and an FFT transformation is performed along the slow time to obtain the target accumulation in the range-Doppler domain.

5. The method for rapid detection of moving targets using a random PRI radar as described in claim 1, characterized in that, The non-uniform sampling scale transformation is defined as: in, It is a non-uniform slow time series. For a random time offset applied to a slow-time pulse train, following the range of The uniform distribution, and , m is the slow time series index, f is the carrier frequency, and f is the fast time frequency. This is a uniformly sampled slow time series that has been recalibrated after a non-uniform sampling scale transformation; pass The introduction of [a certain technology] solves the phase fluctuation between signal pulse trains.

6. A device for rapid detection of moving targets using a random PRI radar, characterized in that, include: The data preprocessing module is used to perform down-conversion and pulse compression processing on the sampled baseband echo signal to obtain a fast-time-slow-time two-dimensional pulse compression signal containing target information. The distance correction module is used to perform FFT transformation on the two-dimensional pulse compression signal along fast time to obtain the frequency domain pulse compression signal; and to perform non-uniform sampling scale transformation on the frequency domain pulse compression signal to eliminate the linear distance movement of the target caused by velocity. The Doppler correction module is used to perform parameter sub-path partitioning search on the signal after non-uniform sampling scale transformation, obtain the estimated values ​​of the target's higher-order motion parameters, and construct a higher-order phase compensation function based on the estimated values ​​to eliminate Doppler motion. The target detection module is used to perform MTD detection on the high-order phase-compensated signal and accumulate the signal in the range-Doppler domain. A constant false alarm rate (CFAR) test is performed on the parameter space where the energy accumulation peak in the range-Doppler domain is located. If the peak value of the peak exceeds a given threshold, the existence of a target is determined. The initial radial distance and radial velocity of the detected target are estimated based on the location of the accumulated peak. The Doppler correction module is configured to perform the following functions: Determine the search range and search interval for the first-order and second-order accelerations of the pulse compression signal after non-uniform sampling scale transformation; N search paths are extracted from the search parameter domain at equal intervals. On each search path, the search value of the first-order acceleration remains unchanged. N one-dimensional searches are performed along the direction of the second-order acceleration according to the preset higher-order motion parameter estimation formula, and the search results are projected onto the search parameter domain. Obtain the local maximum value on each search path and record the location coordinates of the local maximum value. Filter the location coordinates of the local maximum value to obtain the local optimum. Fit the coordinates of the local optimum using the least squares method to form a linear function line in the search parameter domain, which is denoted as the global optimal search path. A one-dimensional search is performed along the global optimal search path according to the preset higher-order motion parameter estimation formula to obtain the estimated values ​​of the target higher-order motion parameters.

7. A device for rapid detection of moving targets using a random PRI radar, characterized in that, include: A memory and a processor, wherein the memory stores computer-readable instructions that, when executed by the processor, cause the processor to perform the steps of the method for rapid detection of moving targets by random PRI radar as described in any one of claims 1 to 5.

8. A storage medium storing computer-readable instructions, characterized in that, When the computer-readable instructions are executed by one or more processors, the one or more processors perform the steps of the method for rapid detection of maneuvering targets by random PRI radar as described in any one of claims 1 to 5.

Images