Radar target high-dimensional signal detection valuation method

Abstract

The invention provides a radar target high-dimensional signal detection and estimation method, and relates to the technical field of radar detection, and the method comprises the steps: determining the type of a to-be-estimated high-dimensional signal parameter of a radar target according to a preset precise distance evolution model; detecting the three-dimensional detection spectrum of the to-be-estimated high-dimensional signal parameter according to a pre-calculated first threshold, and determining a region unit containing a radar target in the three-dimensional detection spectrum; and according to a preset second threshold, screening the connected regions of the region unit where the local maximum value of the detection data is located to obtain reference detection data, and calculating the reference detection data to obtain an accurate estimation value of the to-be-estimated high-dimensional signal parameter. According to the scheme, target detection in a high-dimensional signal parameter space can be realized, and a more accurate high-dimensional signal parameter estimation value of a radar target can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of radar detection technology, and in particular to a radar target high-dimensional signal detection and estimation method. Background Art

[0002] High-speed aircraft often take measures such as reducing their size or using stealth materials to reduce the aircraft's radar cross-sectional area to evade radar detection. Such targets have the characteristics of high speed and low echo signal-to-noise ratio. The purpose of modern signal processing is to improve the radar's perception of such targets through various technical means and obtain the estimation results of the target's high-dimensional signal parameters.

[0003] In related technologies, traditional signal processing methods often cannot achieve target detection in high-dimensional signal parameter space, and since there is a certain error between the parameter estimation results obtained by processing the high-dimensional signals of radar targets and the true values ​​of the parameters, the accuracy of high-dimensional signal parameter estimation of radar targets is low.

[0004] Based on this, there is an urgent need for a radar target high-dimensional signal detection and estimation method to solve the above technical problems. Summary of the invention

[0005] The embodiment of the present invention provides a radar target high-dimensional signal detection and estimation method, which can realize target detection in a high-dimensional signal parameter space and improve the estimation accuracy of the radar target high-dimensional signal parameters.

[0006] In a first aspect, an embodiment of the present invention provides a radar target high-dimensional signal detection and estimation method, comprising:

[0007] According to a preset precise distance evolution model, the type of the high-dimensional signal parameters to be estimated of the radar target is determined; wherein the high-dimensional signal parameters to be estimated include the distance between the observation radar and the target, the radial velocity and the ground velocity;

[0008] The three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated is detected according to a pre-calculated first threshold to determine the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by coherently accumulating the precise distance evolution model;

[0009] The connected area of ​​the regional unit where the local maximum value of the detection data is located is screened according to a preset second threshold to obtain reference detection data, and the reference detection data is calculated to obtain an accurate estimation value of the high-dimensional signal parameter to be estimated.

[0010] In a second aspect, an embodiment of the present invention further provides a radar target high-dimensional signal detection and estimation device, comprising:

[0011] A determination module is used to determine the type of high-dimensional signal parameters to be estimated of the radar target according to a preset accurate distance evolution model; wherein the high-dimensional signal parameters to be estimated include the distance between the observation radar and the target, the radial velocity and the ground velocity;

[0012] A detection module is used to detect the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to a pre-calculated first threshold, and determine the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by coherently accumulating the precise distance evolution model;

[0013] The calculation module is used to screen the connected area of ​​the regional unit where the local maximum value of the detection data is located according to a preset second threshold to obtain reference detection data, and calculate the reference detection data to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, enables the computer to execute the method described in any embodiment of this specification.

[0016] The embodiment of the present invention provides a radar target high-dimensional signal detection and estimation method, which determines the type of high-dimensional signal parameters to be estimated of the radar target through an accurate distance evolution model, processes the three-dimensional detection spectrum of the high-dimensional signal parameters obtained by coherent accumulation processing using a constant false alarm detection method, judges whether there is a target within the radar detection range, retrieves the local maximum value corresponding to the target in the accumulation result, sets a threshold and extracts the three-dimensional accumulation result near the local maximum value in the detection data as the estimated value of the high-dimensional signal parameter of the radar target. This method can not only realize target detection in the high-dimensional signal parameter space, but also reduce the error between the signal processing result and the true value, and obtain a more accurate high-dimensional signal parameter estimation value of the radar target, thereby facilitating subsequent track association, tracking filtering and other data processing processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1It is a flow chart of a radar target high-dimensional signal detection and estimation method provided by an embodiment of the present invention;

[0019] Figure 2 It is a schematic diagram of a radar target uniform speed straight line movement model provided by an embodiment of the present invention;

[0020] Figure 3 It is a schematic diagram of a situation where an actual peak value does not fall within a search grid provided by an embodiment of the present invention;

[0021] Figure 4 is a schematic diagram of the instantaneous distance between a target and a radar within an accumulation time window provided by an embodiment of the present invention;

[0022] Figure 5 1 is a schematic diagram of a pulse compression result of a radar echo signal provided by an embodiment of the present invention;

[0023] Figure 6 is a schematic diagram of a two-dimensional slice of a coherent accumulation result provided by an embodiment of the present invention;

[0024] Figure 7 It is a schematic diagram of detection results of each dimension of a three-dimensional detection spectrum obtained by coherent accumulation and subjected to target detection processing provided by an embodiment of the present invention;

[0025] Figure 8 It is a schematic diagram of the result of integrating the connected area reference data point set into a two-dimensional plane provided by an embodiment of the present invention;

[0026] Fig. 9 is a hardware architecture diagram of an electronic device provided by an embodiment of the present invention;

[0027] Fig.10 It is a structural diagram of a radar target high-dimensional signal detection and estimation device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] As mentioned above, traditional signal processing techniques usually directly output the corresponding parameters of the local maximum in the high-dimensional signal parameter space as the estimation result, or convert the high-dimensional signal parameter estimation problem into a one-dimensional cascade processing. These methods will lead to large errors between the estimation results of the high-dimensional signal parameters and the true values.

[0030] Based on this, the concept of the present invention is to obtain the type of high-dimensional signal parameters to be estimated through an accurate distance evolution model of the moving target, process the coherently accumulated three-dimensional detection spectrum to realize high-dimensional parameter space target detection, and process the reference detection data of the connected area near the target to obtain the accurate estimation result of the high-dimensional signal parameters.

[0031] The specific implementation of the above concept is described below.

[0032] Please refer to Figure 1 The embodiment of the present invention provides a radar target high-dimensional signal detection and estimation method, the method comprising:

[0033] Step 100, determining the type of high-dimensional signal parameters to be estimated of the radar target according to a preset accurate distance evolution model; wherein the high-dimensional signal parameters to be estimated include the distance between the observation radar and the target, the radial velocity and the ground velocity;

[0034] Step 102, detecting the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to a pre-calculated first threshold, and determining the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by performing coherent accumulation processing on the precise distance evolution model;

[0035] Step 104, screening the connected area of ​​the regional unit where the local maximum value of the detection data is located according to a preset second threshold to obtain reference detection data, and calculating the reference detection data to obtain an accurate estimation value of the high-dimensional signal parameter to be estimated.

[0036] In the embodiment of the present invention, the type of high-dimensional signal parameter to be estimated of the radar target is determined by an accurate distance evolution model, the three-dimensional detection spectrum of the high-dimensional signal parameter obtained by coherent accumulation processing is processed by a constant false alarm detection method, it is judged whether there is a target within the radar detection range, the local maximum value corresponding to the target in the accumulation result is retrieved, a threshold is set, and the three-dimensional accumulation result is extracted from the vicinity of the local maximum value in the detection data as the estimated value of the high-dimensional signal parameter of the radar target. This method can not only realize target detection in the high-dimensional signal parameter space, but also reduce the error between the signal processing result and the true value, and obtain a more accurate estimate of the high-dimensional signal parameter of the radar target, thereby facilitating subsequent track association, tracking filtering and other data processing processes.

[0037] Described below Figure 1 How the various steps are performed.

[0038] First, with respect to step 100, the type of the high-dimensional signal parameter to be estimated of the radar target is determined according to a preset accurate distance evolution model.

[0039] In practical applications, the target to be measured is usually in motion. During a long radar observation time, the target motion may cause serious cross-range unit and cross-Doppler unit situations, which will cause the signal echo envelope and phase to change with the number of pulses, and the target energy is distributed in different distance units. If the established motion model fails to accurately describe the target motion, the model mismatch problem will cause a huge accumulation loss as the accumulation time increases, resulting in the failure of the accumulation algorithm. In theory, by significantly increasing the order of the polynomial model, the deviation between it and the actual target motion model can be reduced, and the impact of model mismatch during the observation time can be alleviated to a certain extent. However, this will lead to the dimensionality disaster, and the high-order polynomial coefficients usually do not have specific physical meanings, and their coefficients cannot accurately reflect the parameter types that affect the target motion.

[0040] Therefore, in an embodiment of the present invention, it is proposed to determine the type of parameters that affect the target motion according to a preset precise evolution model.

[0041] Specifically, the precise distance evolution model needs to be determined based on the initial motion data of the radar target. The initial motion data includes the initial position coordinates and the initial ground speed of the radar target. The initial position coordinates are determined by a Cartesian coordinate system established with the observation radar as the coordinate origin.

[0042] Assume that the target moves in a uniform linear motion in the Cartesian coordinate system, and the radar is located at the origin of the coordinate system to observe the target, such as Figure 2 As shown, the target moves from point A to point B in a uniform straight line. is the target motion parameter at the initial moment, θ 0 is the angle between the target motion direction and the radar sight line direction at the initial moment, r(t m ) is the instantaneous distance between the target and the radar within the accumulation time window.

[0043] The spatial position coordinates of the target at each pulse time are:

[0044]

[0045] In the formula, (p x0 ,p y0 ) is the target position coordinate at the initial moment, (v x0 ,v y0 ) is the target ground speed at the initial moment.

[0046] The distance between the radar and the target is:

[0047]

[0048] Since when converting from Cartesian coordinate system to polar coordinate system, there exists:

[0049]

[0050] in, are the target distance, radial velocity and speed at the initial moment. The radial velocity is the projection of the ground velocity in the direction of the radar line of sight.

[0051] Therefore, by converting the coordinate system of the distance calculation formula between the radar and the target, we can get an accurate distance evolution model:

[0052]

[0053] Where r(t) is the instantaneous distance between the radar and the target at any time.

[0054] It can be determined from this model that, for a target in uniform linear motion, its motion process can be determined by only estimating its initial distance, radial velocity and speed.

[0055] Then, with respect to step 102, the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated is detected according to the pre-calculated first threshold to determine the area unit containing the radar target in the three-dimensional detection spectrum.

[0056] It can be seen from the above steps that the precise distance between the radar and the target is only affected by the three motion parameters of distance, radial velocity and ground velocity. Therefore, the embodiment of the present invention can determine the three-dimensional detection spectrum by coherently accumulating the precise distance evolution model, that is, using the GRFT (generalized Radon Fourier transform) coherent accumulation algorithm to establish a search for the target motion parameters, and accumulating energy along the search distance trajectory between the radar and the target to obtain the three-dimensional detection spectrum.

[0057] Specifically, GRFT coherent accumulation uses the search distance trajectory established based on the accurate distance evolution model to extract the pulse pressure data and perform phase compensation. After superposition, the coherent accumulation output is obtained, that is, the detection data of the three-dimensional detection spectrum can be expressed as:

[0058]

[0059] In the formula, is the detection data of the three-dimensional detection spectrum; is the motion parameter in the coherent accumulation process corresponding to the detection data, namely the search parameter, which includes the distance, radial velocity and ground velocity in sequence; s PC is the data after pulse compression; T r is the pulse repetition period; A 1 is the pulse pressure data amplitude; B is the signal bandwidth; M is the number of pulses; m is the pulse sequence number.

[0060] From the above formula, we can know that when the search parameters are completely consistent with the motion parameters of the target at the initial moment, that is:

[0061] r s=r 0

[0062]

[0063] v s =v 0

[0064] At this time, the search distance trajectory r s (m) is strictly matched with the actual distance trajectory of the target, and the coherent accumulation output reaches the maximum:

[0065]

[0066] In the formula, The maximum value of the coherent accumulation output.

[0067] Since the search parameter space is artificially set, there is no guarantee that the true value of the target parameter is exactly contained in the discrete search parameter sequence. In actual processing, the maximum value of the coherent accumulation output cannot reach the theoretical value, and there is a deviation between the motion parameter corresponding to the maximum value position and its true value.

[0068] like Figure 3 As shown, the accumulated actual peak value will appear at the true value position of the target motion parameter. In the schematic diagram, there is a large deviation between the maximum value of the accumulated result and the actual peak position. It is inaccurate to directly output the parameter corresponding to the maximum value as the parameter estimation result. Therefore, in the parameter estimation process, it is necessary to use the information such as continuity and symmetry near the actual peak value of the target to process the high-dimensional spectrum near the accumulated maximum value, solve the actual peak position of the target, and obtain a more accurate high-dimensional signal parameter estimation result. This embodiment specifically adopts the number of reference units and the number of protection units in the three dimensions of distance, radial velocity and ground velocity, and uses constant false alarm detection technology to realize target detection in the high-dimensional signal parameter space.

[0069] In an embodiment of the present invention, determining the area unit containing the radar target in the three-dimensional detection spectrum includes the following steps: calculating the first threshold according to a preset false alarm probability and the number of reference units and the number of protection units of each of the high-dimensional signal parameters; determining whether the detection data of each area unit to be inspected in the three-dimensional detection spectrum is not less than the first threshold; if so, determining that the radar target exists in the area unit to be inspected, otherwise determining that the radar target does not exist in the area unit to be inspected.

[0070] Among them, the first threshold is calculated by the following steps: according to the preset false alarm probability and the number of protection units, the threshold factor of the unit in the area to be inspected in each parameter dimension is calculated; the sample detection data of each parameter dimension of the reference unit is weighted averaged to obtain the noise power of the unit in the area to be inspected; the product of the threshold factor and the noise power is calculated to obtain the first threshold.

[0071] Specifically, the threshold factor is calculated by the following formula:

[0072]

[0073] In the formula, α r , and α v They are the threshold factors for distance, radial velocity and ground velocity, respectively; and The reference unit numbers for range, radial velocity, and ground velocity, respectively; and The number of protection units is the distance, radial speed and ground speed respectively; P fa is the false alarm probability.

[0074] Assuming that the noise in the parameter space is stationary white noise, the noise power of the unit in the area to be inspected is calculated by the following formula:

[0075]

[0076] Where i is the number of distance parameters; j is the number of radial velocity parameters; q is the number of searches for ground velocity; and The number of protection units is the distance, radial velocity and ground velocity respectively; where noise r is the background noise power at distance dimension; is the background noise power in the radial velocity dimension; noise v is the background noise power in the ground speed dimension.

[0077] The detection threshold of each motion parameter is calculated by the following formula:

[0078]

[0079] It is worth noting that in actual processing, different detection threshold strategies can be selected according to different technical requirements.

[0080] If it is necessary to detect all targets as much as possible and a higher false alarm rate is acceptable, the detection condition is relatively loose, and the first threshold of the unit to be detected can be set to:

[0081]

[0082] If false alarms need to be avoided as much as possible in the detection results, the detection conditions are relatively strict. In this case, the first threshold is set to:

[0083]

[0084] Furthermore, according to the square law detection criterion, when the detection data of the unit to be tested is not less than the detection threshold, the target can be detected, that is:

[0085]

[0086] In the formula, H 1 Indicates that the target exists, H 0 Indicates that the target does not exist.

[0087] For step 104, the connected area of ​​the regional unit where the local maximum value of the detection data is located is screened according to the preset second threshold to obtain reference detection data, and the reference detection data is calculated to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

[0088] First, by traversing each unit in the parameter space, the target detection of the entire high-dimensional signal parameter space is completed, the local maximum value of the detection data of the regional unit containing the radar target is obtained, and the motion parameter corresponding to the unit is determined:

[0089]

[0090] In the formula, is the motion parameter corresponding to the unit.

[0091] In an embodiment of the present invention, the screening and valuation process includes: determining whether the three-dimensional detection data in the connected area is greater than a second threshold; if so, extracting the detection data greater than the second threshold as reference detection data for weighted average calculation to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

[0092] Specifically, after the regional unit where the local maximum value is located is determined through the above process, the second threshold η is preset and the extraction The detection data exceeding the second threshold in the nearby connected area is used as the reference detection data:

[0093]

[0094] Due to the discrete search process of coherent accumulation, the actual peak position of the target will appear near the local maximum. By utilizing the continuity and symmetry of the accumulation results in the high-dimensional signal parameter space, the reference detection data is weighted averaged to obtain the center of the three-dimensional connected area, thereby achieving accurate estimation of the high-dimensional signal parameters.

[0095] The precise estimation value of the high-dimensional signal parameters is calculated by the following formula:

[0096]

[0097] In the formula, is the precise estimation value of the high-dimensional signal parameter; N is the total number of reference detection data; is the nth reference detection data, n = 1, 2, ..., N; r s,n is the distance corresponding to the nth reference detection data; is the radial velocity corresponding to the nth reference detection data; v s,n is the ground speed corresponding to the nth reference detection data.

[0098] In order to demonstrate the performance of the present invention, this section sets up corresponding simulation scenarios to verify the performance of the present invention. The radar system parameters are set as follows: signal carrier frequency f c =7.5MHz, signal bandwidth B = 50kHz, pulse duration T p =0.3ms, pulse repetition period T r =3.48ms, sampling frequency 400kHz, accumulated pulse number PulseNum = 5000. The target motion parameters are set as follows: the target distance at the initial moment is r 0 =70km, radial velocity is Speed 0 =600m / s. The signal-to-noise ratio SNR after pulse compression = -20dB, and the false alarm probability is set to P fa =10 -4 The protection unit of each dimension is 5, and the reference unit is 15.

[0099] Figure 4 The instantaneous distance between the target and the radar within the accumulation time window is given. Figure 5 The pulse compression results of radar echo signals are given. Figure 6 The three-dimensional detection spectrum obtained by coherent accumulation of pulse compression data is given, which are the distance-radial velocity two-dimensional slices of the coherent accumulation results when the velocity is the positioning parameter, the distance-ground velocity two-dimensional slices of the coherent accumulation results when the radial velocity is the positioning parameter, and the radial velocity-ground velocity two-dimensional slices of the coherent accumulation results when the distance is the positioning parameter. The positioning parameter is the parameter corresponding to the maximum value of the accumulation result. It can be seen that when the true value of the target parameter does not appear exactly in the preset discrete search parameter sequence, the accumulation effect is poor, and the peak position in the accumulation result is greatly different from the true value of the target motion.

[0100] Figure 7 The detection results of each dimension of the three-dimensional detection spectrum obtained by coherent accumulation after target detection processing are given, which are the detection results of the distance dimension, the radial velocity dimension, and the ground velocity dimension. The positioning parameter is the parameter corresponding to the maximum value of the accumulation result. It can be seen that the method given in the embodiment of the present invention can realize target detection in high-dimensional signal parameter space.

[0101] Figure 8The results of integrating the reference data point set of the three-dimensional connected area into the two-dimensional plane are respectively the results of integrating the reference point set into the distance-radial velocity plane, the results of integrating the reference point set into the distance-ground velocity plane, and the results of integrating the reference point set into the radial velocity-ground velocity plane. It can be seen that the reference point set has a certain symmetry in the parameter space. Table 1 shows the parameter estimation results calculated by the local maximum method and the method of the present invention and the true value of the target motion parameter.

[0102] Table 1 Target parameter estimation results

[0103]

[0104] It can be seen that compared with the method of using the local maximum result as the parameter estimation output, the method proposed in the embodiment of the present invention uses the three-dimensional distribution of the accumulated results to extract the parameter center, and the error between the obtained three-dimensional parameter joint estimation result and the true value is smaller, and the estimation is more accurate.

[0105] like Fig. 9 , Fig.10 As shown, an embodiment of the present invention provides a radar target high-dimensional signal detection and estimation device. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Fig. 9 As shown, it is a hardware architecture diagram of an electronic device in which a radar target high-dimensional signal detection and estimation device provided by an embodiment of the present invention is located. Fig. 9 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Fig.10 As shown, as a device in a logical sense, the CPU of the electronic device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it. A radar target high-dimensional signal detection and estimation device provided in this embodiment includes:

[0106] The determination module 200 is used to determine the type of the high-dimensional signal parameter to be estimated of the radar target according to a preset accurate distance evolution model; wherein the high-dimensional signal parameter to be estimated includes the distance between the observation radar and the target, the radial velocity and the ground velocity;

[0107] A detection module 202 is used to detect the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to a pre-calculated first threshold, and determine the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by performing coherent accumulation processing on the precise distance evolution model;

[0108] The calculation module 204 is used to screen the connected area of ​​the regional unit where the local maximum value of the detection data is located according to a preset second threshold to obtain reference detection data, and calculate the reference detection data to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

[0109] In an embodiment of the present invention, when the detection module 202 detects the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to the pre-calculated first threshold and determines the area unit containing the radar target in the three-dimensional detection spectrum, it is specifically used to perform the following operations: calculate the first threshold according to the preset false alarm probability and the number of reference units and the number of protection units of each of the high-dimensional signal parameters; determine whether the detection data of each area unit to be detected in the three-dimensional detection spectrum is not less than the first threshold; if so, determine that the radar target exists in the area unit to be detected, otherwise, determine that the radar target does not exist in the area unit to be detected.

[0110] In an embodiment of the present invention, the first threshold is calculated based on a preset false alarm probability and the number of reference units and the number of protection units of each of the high-dimensional signal parameters, including: calculating the threshold factor of the unit in the area to be inspected in each parameter dimension based on the preset false alarm probability and the number of protection units; performing weighted average calculation on the sample detection data of each parameter dimension of the reference unit to obtain the noise power of the unit in the area to be inspected; and calculating the product of the threshold factor and the noise power to obtain the first threshold.

[0111] In the embodiment of the present invention, the threshold factor is calculated by the following formula:

[0112]

[0113] In the formula, α r , and α v They are the threshold factors for distance, radial velocity and ground velocity, respectively; and are the reference unit numbers of distance, radial velocity and ground velocity respectively; P fa is the false alarm probability.

[0114] In the embodiment of the present invention, the noise power is calculated by the following formula:

[0115]

[0116] Where i is the number of distance parameters; j is the number of radial velocity parameters; q is the number of searches for ground velocity; and The number of protection units is the distance, radial velocity and ground velocity respectively; where noise r is the background noise power at distance dimension; is the background noise power in the radial velocity dimension; noise v is the background noise power in the ground speed dimension.

[0117] In an embodiment of the present invention, when the calculation module 204 performs screening of the connected area of ​​the area unit where the local maximum value of the detection data is located according to a preset second threshold to obtain reference detection data, and calculates the reference detection data to obtain an accurate estimate of the high-dimensional signal parameter to be estimated, it is specifically used to perform the following operations: determine whether the three-dimensional detection data in the connected area is greater than the second threshold; if so, extract the detection data greater than the second threshold as the reference detection data for weighted average calculation to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

[0118] In the embodiment of the present invention, the precise estimated value is calculated by the following formula:

[0119]

[0120] In the formula, is the precise estimated value of the high-dimensional signal parameter to be estimated; N is the total number of reference detection data; is the nth reference detection data, n = 1, 2, ..., N; r s,n is the distance corresponding to the nth reference detection data; is the radial velocity corresponding to the nth reference detection data; v s,n is the ground speed corresponding to the nth reference detection data.

[0121] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on a radar target high-dimensional signal detection and estimation device. In other embodiments of the present invention, a radar target high-dimensional signal detection and estimation device may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0122] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For the specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0123] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a radar target high-dimensional signal detection and estimation method in any embodiment of the present invention is implemented.

[0124] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a radar target high-dimensional signal detection and estimation method in any embodiment of the present invention.

[0125] Specifically, a system or device equipped with a storage medium can be provided, on which software program code that implements the functions of any of the above-mentioned embodiments is stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program code stored in the storage medium.

[0126] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0127] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.

[0128] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0129] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0130] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical factors in the process, method, article or device including the elements.

[0131] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A radar target high-dimensional signal detection and estimation method, characterized in that: include: According to a preset precise distance evolution model, the type of the high-dimensional signal parameters to be estimated of the radar target is determined; wherein the high-dimensional signal parameters to be estimated include the distance between the observation radar and the target, the radial velocity and the ground velocity; The three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated is detected according to a pre-calculated first threshold to determine the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by coherently accumulating the precise distance evolution model; The connected area of ​​the regional unit where the local maximum value of the detection data is located is screened according to a preset second threshold to obtain reference detection data, and the reference detection data is calculated to obtain an accurate estimation value of the high-dimensional signal parameter to be estimated.

2. The method according to claim 1, characterized in that The method of detecting the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to the pre-calculated first threshold to determine the area unit containing the radar target in the three-dimensional detection spectrum comprises: The first threshold is calculated according to a preset false alarm probability and the number of reference units and the number of protection units of each of the high-dimensional signal parameters; Determine whether the detection data of each unit of the area to be inspected in the three-dimensional detection spectrum is not less than the first threshold; If so, it is determined that there is a radar target in the area unit to be inspected; otherwise, it is determined that there is no radar target in the area unit to be inspected.

3. The method according to claim 2, characterized in that The first threshold is calculated according to a preset false alarm probability and the number of reference units and the number of protection units of each of the high-dimensional signal parameters, including: According to the preset false alarm probability and the number of protection units, the threshold factors of the units in the area to be inspected in each parameter dimension are calculated; The sample detection data of each parameter dimension of the reference unit is weighted averaged to obtain the noise power of the unit in the area to be inspected; The product of the threshold factor and the noise power is calculated to obtain the first threshold.

4. The method according to claim 3, characterized in that The threshold factor is calculated by the following formula: In the formula, α r , and α v They are the threshold factors for distance, radial velocity and ground velocity, respectively; and are the reference unit numbers of distance, radial velocity and ground velocity respectively; P fa is the false alarm probability.

5. The method according to claim 4, characterized in that The noise power is calculated by the following formula: Where i is the number of distance parameters; j is the number of radial velocity parameters; q is the number of searches for ground velocity; and The number of protection units is the distance, radial velocity and ground velocity respectively; where noise r is the background noise power from the dimension; is the background noise power in the radial velocity dimension; noise v is the background noise power in the ground speed dimension.

6. The method according to claim 1, characterized in that The method further comprises: screening the connected area of ​​the regional unit where the local maximum value of the detection data is located according to the preset second threshold to obtain reference detection data, and calculating the reference detection data to obtain an accurate estimation value of the high-dimensional signal parameter to be estimated, including: Determine whether the three-dimensional detection data in the connected area is greater than a second threshold; If so, the detection data greater than the second threshold is extracted as reference detection data for weighted average calculation to obtain an accurate estimation value of the high-dimensional signal parameter to be estimated.

7. The method according to claim 6, characterized in that The precise estimated value is calculated by the following formula: In the formula, is the precise estimated value of the high-dimensional signal parameter to be estimated; N is the total number of reference detection data; is the nth reference detection data, n = 1, 2, ..., N; r s,n is the distance corresponding to the nth reference detection data; is the radial velocity corresponding to the nth reference detection data; v s,n is the ground speed corresponding to the nth reference detection data.

8. A radar target high-dimensional signal detection and estimation device, characterized in that: include: A determination module is used to determine the type of high-dimensional signal parameters to be estimated of the radar target according to a preset accurate distance evolution model; wherein the high-dimensional signal parameters to be estimated include the distance between the observation radar and the target, the radial velocity and the ground velocity; A detection module is used to detect the three-dimensional detection spectrum of the high-dimensional signal parameter to be estimated according to a pre-calculated first threshold, and determine the area unit containing the radar target in the three-dimensional detection spectrum; wherein the three-dimensional detection spectrum is determined by coherently accumulating the precise distance evolution model; The calculation module is used to screen the connected area of ​​the regional unit where the local maximum value of the detection data is located according to a preset second threshold to obtain reference detection data, and calculate the reference detection data to obtain an accurate estimate of the high-dimensional signal parameter to be estimated.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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