Frequency agile radar distance and speed parameter estimation method

Abstract

The invention discloses a frequency agility radar distance and speed parameter estimation method, and belongs to the technical field of radar signal processing. Comprising the following steps: acquiring a frequency agile radar echo signal reflected by a target; performing pulse compression processing on the frequency agility radar echo signal to obtain a pulse pressure frequency agility radar echo signal; dividing a high-resolution distance unit and a speed resolution unit, and constructing a distance-speed dictionary matrix; sampling a pulse compression peak point of the pulse pressure frequency agility radar echo signal to obtain an observation matrix of the pulse pressure frequency agility radar echo signal; based on a Dice coefficient and a generalized regularization sparseness adaptive matching pursuit algorithm, solving a sparse solution vector corresponding to the observation matrix in the distance-speed dictionary matrix; and reconstructing the sparse solution vector to obtain a distance and speed parameter estimation result of the frequency agile radar. The sparse reconstruction theory is introduced, and the performance of frequency agility radar distance and speed parameter estimation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar signal processing, in particular to a frequency-agile radar range and velocity parameter estimation method. BACKGROUND

[0002] The adjacent pulse carrier frequencies of the frequency-agile radar randomly jump within a certain range, making it difficult for a jammer to obtain the carrier frequency information of the radar pulse, thus having excellent low-interception and anti-jamming performance. However, the phase of the return signal of the frequency-agile radar changes with the target position and the pulse carrier frequency, so that the phase change between the pulses of the return signal is nonlinear, resulting in that the traditional inverse Fourier transform method cannot obtain the range and velocity information of the target.

[0003] Since the target scattering points in the radar observation scene are sparse, a sparse processing algorithm can be used to estimate the range and velocity parameters of the target. When processing the frequency-agile radar using the traditional Generalized Orthogonal Matching Pursuit (GOMP) algorithm, the number of target scattering points needs to be known in advance, and the inner product matching principle is used in each iteration, which may select the wrong atom, resulting in a decrease in the performance of the range and velocity parameter estimation. Although the Sparsity Adaptive Matching Pursuit (SAMP) algorithm can estimate the range and velocity information of multiple target scattering points when the sparsity is unknown, false peaks may occur in the low signal-to-noise ratio case. SUMMARY

[0004] The present application aims to overcome the deficiencies in the prior art and provide a frequency-agile radar range and velocity parameter estimation method, which introduces the sparse reconstruction theory to solve the problems of being difficult to apply to the scene where the number of target scattering points is unknown and the false peaks occurring in the low signal-to-noise ratio case due to the wrong selection of atoms, thereby improving the performance of the frequency-agile radar range and velocity parameter estimation.

[0005] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0006] The present application provides a frequency-agile radar range and velocity parameter estimation method, comprising:

[0007] Obtaining the frequency-agile radar return signal reflected by the target;

[0008] Performing pulse compression processing on the frequency-agile radar return signal to obtain a pulse-compressed frequency-agile radar return signal;

[0009] The coarse resolution range unit and the velocity unambiguous range of the pulse compression frequency-agile radar echo signal are calculated, the coarse resolution range unit is divided into a high resolution range unit according to the frequency hopping point number of the pulse compression frequency-agile radar echo signal, and the velocity unambiguous range is divided into a velocity resolution unit according to the pulse number of the pulse compression frequency-agile radar echo signal;

[0010] A range-velocity dictionary matrix is constructed according to the high resolution range unit and the velocity resolution unit;

[0011] The pulse compression peak point of the pulse compression frequency-agile radar echo signal is sampled to obtain an observation matrix of the pulse compression frequency-agile radar echo signal;

[0012] The sparse solution vector corresponding to the observation matrix in the range-velocity dictionary matrix is solved based on a Dice coefficient and a generalized regularization sparsity adaptive matching pursuit algorithm according to the range-velocity dictionary matrix;

[0013] The sparse solution vector is reconstructed according to the high resolution range unit and the velocity resolution unit to obtain the range and velocity parameter estimation result of the frequency-agile radar.

[0014] Optionally, the obtaining of the target-reflected frequency-agile radar echo signal comprises:

[0015] The frequency-agile radar transmission signal is transmitted to the target, and the target-reflected frequency-agile radar echo signal is received, the frequency-agile radar transmission signal is represented as:

[0016] ;

[0017] ;

[0018] wherein, represents the frequency-agile radar transmission signal at the t th< time; represents the pulse width of the frequency-agile radar transmission signal; represents the linear frequency hopping rate; represents the carrier frequency of the m th< pulse; represents the imaginary unit; represents a standard rectangular window function; represents an exponential function; represents the initial carrier frequency of the radar; represents the frequency hopping point number; represents the minimum frequency hopping interval; represents the pulse number.

[0019] Optionally, the pulse compression frequency-agile radar echo signal is represented as:

[0020] ;

[0021] wherein, represents the pulse-compression radar echo signal of the mth pulse at the tth time; represents the scattering coefficient of the target scattering point; represents the speed of light; represents the linear frequency hopping rate; represents the pulse width of the frequency-agile radar transmitting signal; represents the tth time of the mth pulse; represents the radar pulse repetition period; represents the echo time delay; represents the straight-line distance between the radar and the target; represents the initial carrier frequency of the radar; represents the number of frequency hopping points; represents the minimum frequency hopping interval; represents the radial velocity of the target; represents the noise of the mth pulse at the tth time; represents the imaginary unit; represents the exponential function.

[0022] Optionally, the high-resolution range unit is represented as:

[0023] ;

[0024] The number of high-resolution range units is represented as:

[0025] ;

[0026] wherein, represents the high-resolution range unit; represents the speed of light; represents the total bandwidth covered by the waveform of the frequency-agile radar transmitting signal in the frequency domain; represents the number of frequency hopping points; represents the minimum frequency hopping interval; represents the number of high-resolution range units; represents the baseband transmitting signal bandwidth of the frequency-agile radar.

[0027] Optionally, the velocity resolution unit is represented as:

[0028] ;

[0029] The number of velocity resolution units is represented as:

[0030] ;

[0031] wherein, represents the velocity resolution unit; represents the speed of light; Indicates the initial carrier frequency of the radar; Indicates the number of pulses; Indicates the radar pulse repetition period; Indicates the number of velocity resolution units.

[0032] Optionally, the distance-velocity dictionary matrix is ​​represented as:

[0033] ;

[0034] ;

[0035] in, Represents the distance-velocity dictionary matrix; This represents the high-resolution range unit for the m-th pulse; This represents the velocity resolution unit for the m-th pulse; Indicates the straight-line distance between the radar and the target; Indicates the number of frequency hopping points; Indicates the minimum frequency hopping interval; Represents the speed of light; Indicates the radial velocity of the target; Indicates the initial carrier frequency of the radar; Indicates the radar pulse repetition period; Represents the imaginary unit; This represents an exponential function.

[0036] Optionally, the observation matrix of the pulse-voltage frequency-agile radar echo signal is represented as follows:

[0037] ;

[0038] ;

[0039] in, The observation matrix representing the pulse compression frequency agile radar echo signal; Represents the distance-velocity dictionary matrix; The sparse solution vector in the observation matrix of the pulse-frequency agile radar echo signal on the range-velocity two-dimensional plane; Indicates noise; This represents the scattering coefficient of the target scattering point; Represents the speed of light; Indicates a linear hopping frequency; Indicates the pulse width of the transmitted signal from the frequency agile radar; This represents the time t of the m-th pulse; Indicates the radar pulse repetition period; Indicates echo delay; Indicates the straight-line distance between the radar and the target; Indicates the initial carrier frequency of the radar; Represents the imaginary unit; This represents an exponential function.

[0040] Optionally, based on the distance-velocity dictionary matrix, and using the Dice coefficients and a generalized regularized sparse adaptive matching pursuit algorithm, the sparse solution vector corresponding to the observation matrix in the distance-velocity dictionary matrix is ​​solved, including:

[0041] Initialize residual Index set Support set ;in, Indicates the empty set;

[0042] In the t-th iteration, calculate the distance-velocity dictionary matrix. The residuals of each atom vector in the (t-1)th iteration Dice matching coefficients between ;

[0043] Select Dice matching coefficient The num atom vectors with the largest absolute values ​​are identified, and their indices in the distance-velocity dictionary matrix are recorded to obtain the incremented index set for the t-th iteration. and increase support set ;

[0044] Based on the increase in the index set during the t-th iteration and increase support set The atomic index set and support set are updated to obtain the index set for the t-th iteration. and support set ;in, This represents the index set for the (t-1)th iteration; Let represent the support set for the (t-1)th iteration;

[0045] Calculate the estimated value of the pulse compression frequency agile radar echo signal in the t-th iteration. Based on preset regularization conditions, the estimated value of the pulse compression frequency agile radar echo signal in the t-th iteration is obtained. Grouping is performed to obtain grouped signals;

[0046] Select the group of signals with the maximum energy to obtain the new index set for the t-th iteration. and new support set ;

[0047] Based on the new index set of the t-th iteration and new support set Calculate the estimated value of the reconstructed signal in the t-th iteration. and update the residual of the tth iteration ;

[0048] If or the maximum iteration number G is reached, the iteration is stopped and the reconstructed signal estimate of the tth iteration is outputted, wherein the reconstructed signal estimate of the tth iteration is a sparse solution vector in the observation matrix of the pulse compression frequency-agile radar echo signal; wherein, denotes a preset threshold value; denotes solving norm;

[0049] If , and the maximum iteration number G is not reached, the iteration stage is updated as , the step size is updated as , the support set size is updated as , and the t+1th iteration is updated; wherein, denotes the iteration stage before updating; denotes the step size before updating; denotes the support set size before updating;

[0050] If , and the maximum iteration number G is not reached, the new index set of the tth iteration is updated as , and the t+1th iteration is updated; wherein, denotes the new index set of the t-1th iteration.

[0051] Optionally, the Dice matching coefficient between each atom vector in the range-velocity dictionary matrix and the residual of the t-1th iteration is denoted as:

[0052] ;

[0053] wherein, denotes matrix transposition; denotes calculation of the Dice matching coefficient.

[0054] Optionally, the pulse compression frequency-agile radar echo signal estimate of the tth iteration is denoted as:

[0055] ;

[0056] The preset regularization condition is denoted as:

[0057] ; ​

[0058] the residual of the tth iteration is expressed as:

[0059] ;

[0060] wherein, denotes the index set of the tth iteration the corresponding distance-velocity dictionary matrix; denotes the new index set of the tth iteration the corresponding distance-velocity dictionary matrix; , respectively denote the signal estimation value of the ath element and the bth element in the support set of the tth iteration; denotes the matrix transpose.

[0061] Compared with the prior art, the present application has the beneficial effects that:

[0062] The present application introduces the sparse reconstruction theory, overcomes the difficulties of the traditional inverse Fourier transform method, can accurately obtain the distance and speed information of the target in the scene where the sparsity is unknown, effectively solves the problems that the traditional algorithm is difficult to be applied to the scene where the number of target scattering points is unknown and the pseudo-peak appears in the case of low signal-to-noise ratio due to the wrong selection of atoms, and improves the performance of the frequency agile radar distance and speed parameter estimation. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 Fig. 1 shows a flowchart of the method for estimating the distance and speed parameters of the frequency agile radar in an embodiment of the present application;

[0064] Figure 2 Fig. 2 shows a flowchart of the DC-GRSAMP algorithm-based method in an embodiment of the present application;

[0065] Figure 3 Fig. 3 shows a high-resolution distance and speed detection plane diagram of multiple scattering points based on the GOMP algorithm in an embodiment of the present application;

[0066] Figure 4 Fig. 4 shows a high-resolution distance and speed detection plane diagram of multiple scattering points based on the SAMP algorithm in an embodiment of the present application;

[0067] Figure 5 Fig. 5 shows a high-resolution distance and speed detection plane diagram of multiple scattering points based on the DC-GRSAMP algorithm in an embodiment of the present application;

[0068] Figure 6The figure shows a comparison curve of distance and velocity parameter estimation probability of the GOMP algorithm, the SAMP algorithm and the DC-GRSAMP algorithm of the application in different signal-to-noise ratios in an embodiment.

[0069] Figure 7 The figure shows a comparison curve of distance and velocity parameter estimation probability of the GOMP algorithm, the SAMP algorithm and the DC-GRSAMP algorithm of the application in different target scattering point quantities in an embodiment. DETAILED DESCRIPTION

[0070] The technical solutions of the application will be described in detail below with reference to the drawings and specific embodiments. It should be understood that the embodiments of the application and the specific features in the embodiments are detailed descriptions of the technical solutions of the application, rather than limitations of the technical solutions of the application. In the case of no conflict, the technical features in the embodiments of the application and the embodiments can be combined with each other.

[0071] The term "and / or", only describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / ", generally represents that the associated objects before and after it are in an "or" relationship.

[0072] Embodiment 1

[0073] As Figure 1 shown, the embodiment introduces a frequency-agile radar distance and velocity parameter estimation method, which includes the following steps:

[0074] Step 1: Obtain the frequency-agile radar echo signal reflected by the target, specifically:

[0075] Suppose the radar transmits M pulses in one coherent processing interval, where the carrier frequency of the mth pulse is which can be expressed as:

[0076] ;

[0077] The frequency-agile radar transmission signal can be expressed as:

[0078] ;

[0079] wherein, represents the frequency-agile radar transmission signal at the tth time; represents the pulse width of the frequency-agile radar transmission signal; represents the linear frequency hopping rate; represents the carrier frequency of the mth pulse; represents the imaginary unit; represents the standard rectangular window function; Represents an exponential function; Indicates the initial carrier frequency of the radar; Indicates the number of frequency hopping points; Indicates the minimum frequency hopping interval; Indicates the number of pulses.

[0080] Assuming the baseband transmit signal bandwidth of the frequency agile radar is ,but , and The three satisfy each other The relationship. Minimize the frequency hopping interval. At this point, the frequency bands between the pulses do not overlap, so the total bandwidth covered by the waveform of the frequency-agile radar transmitted signal in the frequency domain is... .

[0081] The radar transmits a pulse signal that reaches the target location after a certain period of time, and the radar receiver receives the frequency-agile radar echo signal reflected by the target.

[0082] Step 2: Perform pulse compression processing on the frequency agile radar echo signal, specifically as follows:

[0083] If the frequency-agile radar echo signal is down-converted and pulse-compressed, then the m-th pulse-compressed frequency-agile radar echo signal... It can be represented as:

[0084] ;

[0085] in, The echo delay can be represented as: Then the m-th pulse-speed frequency-agile radar echo signal Rewritten as:

[0086] ;

[0087] in, This represents the scattering coefficient of the target scattering point; Represents the speed of light; This represents the time t of the m-th pulse; Indicates the radar pulse repetition period; Indicates the straight-line distance between the radar and the target; Indicates the radial velocity of the target; This represents the noise of the m-th pulse at time t.

[0088] Step 3: Calculate the coarse-resolution range cell and the unambiguous velocity range of the pulse compression frequency agile radar echo signal.

[0089] Step four: dividing the coarse resolution range cell into high resolution range cells, and dividing the velocity unambiguous range into velocity resolution cells, specifically:

[0090] According to the frequency hopping points of the pulse compression quick frequency change radar echo signal, the coarse resolution range cell is divided into high resolution range cells, the high resolution range cell refers to the range resolution obtained after coherent processing of the radar echo signal, which depends on the synthetic bandwidth of the radar, the high resolution range cell is represented as:

[0091] ;

[0092] The number of high resolution range cells divided in a coarse resolution range cell is:

[0093] ;

[0094] Wherein, represents the number of high resolution range cells.

[0095] According to the number of pulses of the pulse compression quick frequency change radar echo signal, the velocity unambiguous range is divided into velocity resolution cells, the velocity resolution cell depends on the synthetic time width of the radar, and the velocity resolution cell is represented as:

[0096] ;

[0097] The velocity unambiguous range can be represented as The number of velocity resolution cells divided in the unambiguous velocity range is represented as:

[0098] ;

[0099] Wherein, represents the number of velocity resolution cells.

[0100] Therefore, the range and velocity search range of the target is divided according to the number of high resolution range cells contained in the coarse resolution range cell and the number of velocity resolution cells contained in the unambiguous velocity range, that is, the high resolution range cell is , the velocity resolution cell is , the definition is the corresponding range of the th high resolution range cell, wherein ; the definition is the corresponding velocity of the th velocity resolution cell, wherein .

[0101] Step five: constructing a range-velocity dictionary matrix, specifically:

[0102] According to the high-resolution range unit and the velocity resolution unit, a range-velocity dictionary matrix is constructed.

[0103] The mth pulse compression frequency-agile radar echo signal The mathematical expression is defined as follows:

[0104] ;

[0105] Wherein, represents a sparse solution vector in an observation matrix of the pulse compression frequency-agile radar echo signal in the range-velocity two-dimensional plane; represents the high-resolution range unit of the mth pulse; represents the velocity resolution unit of the mth pulse, and the mth pulse compression frequency-agile radar echo signal can be represented as:

[0106] ;

[0107] For the range and the velocity , the mth pulse compression frequency-agile radar echo signal can be represented as:

[0108] ;

[0109] Wherein, represents a sparse solution vector in an observation matrix of the pulse compression frequency-agile radar echo signal in the range-velocity two-dimensional plane. Therefore, a range-velocity dictionary matrix can be constructed, which is represented as:

[0110] ;

[0111] Each atom in the dictionary matrix contains the possible range and velocity information of the target, and the coverage is large enough to cover the possible position and velocity of the detected target. Expanding

[0112] can be obtained:

[0113] ;

[0114] Wherein, , , respectively represent the corresponding distance of the 1st high-resolution range unit of the 1st pulse, the corresponding distance of the 1st high-resolution range unit of the 2nd pulse, …, and the corresponding distance of the 1st high-resolution range unit of the Mth pulse. ,​ , …, respectively represent the corresponding speed of the 1st speed resolution unit of the 1st pulse, the corresponding speed of the 1st speed resolution unit of the 2nd pulse, …, the corresponding speed of the 1st speed resolution unit of the Mth pulse; , , …, respectively represent the corresponding distance of the Kth high-resolution distance unit of the 1st pulse, the corresponding distance of the Kth high-resolution distance unit of the 2nd pulse, …, the corresponding distance of the Kth high-resolution distance unit of the Mth pulse; , , …, respectively represent the corresponding speed of the 1st speed resolution unit of the 1st pulse, the corresponding speed of the 1st speed resolution unit of the 2nd pulse, …, the corresponding speed of the 1st speed resolution unit of the Mth pulse;

[0115] Step six: sampling the pulse compression peak points of the pulse compression radar echo signal, specifically:

[0116] Sampling the pulse compression peak points of the pulse compression radar echo signal to obtain an observation matrix of the pulse compression radar echo signal;

[0117] The observation matrix of the pulse compression radar echo signal is represented as:

[0118] ;

[0119] wherein, represents noise.

[0120] Step seven: using the Dice coefficient and the generalized regularized sparsity adaptive matching pursuit (Generalized Regularized Sparsity Adaptive Matching Pursuit Based on Dice Coefficient, DC-GRSAMP) algorithm to solve the corresponding sparse solution vector of the observation matrix in the distance-velocity dictionary matrix, specifically:

[0121] According to the distance-velocity dictionary matrix, based on the Dice coefficient and the generalized regularized sparsity adaptive matching pursuit algorithm, the sparse solution vector corresponding to the observation matrix of the pulse compression radar echo signal in the distance-velocity dictionary matrix is solved;

[0122] ​​​​The residual size represents a difference between the estimated value and the target true information, the support set represents atomic indexes corresponding to selected Dice coefficient matching values, the index set and the support set are updated in sequence, the pulse compression quick-time frequency radar echo signal estimated value is calculated, the support set is screened by using a regularization condition, and the corresponding reconstructed signal and residual are updated, a judgment is made according to the residual size, then a step size is adaptively updated according to a judgment result, the estimated value is gradually approximated to the pulse compression quick-time frequency radar echo signal through multiple iterations, and the iteration is stopped when the residual reaches a threshold value or reaches a maximum iteration number, and the sparse solution vector is output.

[0123] As shown in the following table, the iteration steps based on the DC-GRSAMP algorithm are as follows: Figure 2

[0124] Initialization: initialize the residual , the index set , and the support set ; wherein, represents an empty set;

[0125] At the tth iteration:

[0126] First step: calculate the Dice matching coefficient between each atomic vector in the distance-velocity dictionary matrix and the residual of the (t-1) th iteration, and the Dice matching coefficient is represented as:

[0127] ;

[0128] wherein, represents a matrix transpose; represents calculation of the Dice matching coefficient;

[0129] Second step: select num atomic vectors with the largest absolute value of the Dice matching coefficient, and record their indexes in the distance-velocity dictionary matrix, to obtain the increasing index set and the increasing support set of the tth iteration;

[0130] Third step: update the atomic index set and the support set according to the increasing index set and the increasing support set of the tth iteration, to obtain the index set and the support set of the tth iteration; wherein, represents the index set of the (t-1) th iteration; represents the support set of the (t-1) th iteration;

[0131] Fourth step: calculate the pulse compression quick-time frequency radar echo signal estimated value of the tth iteration​​​ , is denoted as:

[0132] ;

[0133] According to a preset regularization condition, the pulse compression chirp radar echo signal estimation value of the tth iteration is grouped to obtain a grouped signal, and the preset regularization condition is denoted as:

[0134] ;

[0135] wherein, denotes an index set of the tth iteration corresponding to a distance-velocity dictionary matrix; , respectively denote a signal estimation value of an a th element in a support set of the tth iteration and a signal estimation value of a b th element;

[0136] Fifth step: selecting a group of grouped signals with the largest energy to obtain a new index set of the tth iteration and a new support set ;

[0137] Sixth step: according to the new index set of the tth iteration and the new support set , a reconstructed signal estimation value of the tth iteration is calculated, and a residual error of the tth iteration is updated, and is denoted as:

[0138] ;

[0139] wherein, denotes a new index set of the tth iteration corresponding to a distance-velocity dictionary matrix;

[0140] Seventh step: if or a maximum iteration number G is reached, the iteration is stopped and a reconstructed signal estimation value of the tth iteration is output, and the reconstructed signal estimation value of the tth iteration is a sparse solution vector in an observation matrix of a pulse compression chirp radar echo signal; wherein, denotes a preset threshold; denotes a solution norm;

[0141] Eighth step: if , and the maximum iteration number G is not reached, an iteration stage is updated as , a step size is updated as , and a support set size is updated as​ , the t+1th iteration update is performed; wherein, denotes the iteration stage before the update; denotes the step size before the update; denotes the support set size before the update;

[0142] Step nine: if , and the maximum iteration number G is not reached, the new index set of the tth iteration is updated as , the t+1th iteration update is performed; wherein, denotes the new index set of the t-1th iteration.

[0143] Thus, the sparse solution vector of the pulse compression radar echo signal is obtained as the reconstructed signal estimation value of the tth iteration .

[0144] Step eight: reconstruct the sparse solution vector, specifically:

[0145] According to the high-resolution range unit and the velocity resolution unit, the sparse solution vector is reconstructed to obtain the range and velocity parameter estimation results of the frequency agile radar.

[0146] Embodiment 2

[0147] Based on embodiment 1, this embodiment introduces a test example of a frequency agile radar range and velocity parameter estimation method, including:

[0148] Set the radar simulation parameters, as shown in Table 1.

[0149] Table 1 Radar simulation parameters

[0150]

[0151] According to the parameters in Table 1, the width of the radar coarse resolution range unit is , the size of the synthetic bandwidth can be calculated as , the width of one high-resolution range unit is , the velocity unambiguous range is [0, 75m / s], and the velocity resolution unit . When constructing the range-velocity dictionary matrix, the range dimension is divided into 60 high-resolution range units within one coarse resolution range unit, and the velocity is divided into 60 velocity resolution units within the unambiguous velocity range.

[0152] In order to compare the distance and velocity parameter estimation performance of the Generalized Orthogonal Matching Pursuit (GOMP) algorithm, the Sparsity Adaptive Matching Pursuit (SAMP) algorithm and the DC-GRSAMP algorithm in the case of unknown number of target scattering points, three scattering points are set in the radar observation scene, the distance of scattering point 1 is 8000.25 m, the velocity is 40 m / s, the distance of scattering point 2 is 8000.75 m, the velocity is 41.25 m / s, and the distance of scattering point 3 is 8001.25 m, and the velocity is 42.5 m / s.

[0153] Since the number of target scattering points in the actual scene is an unknown number, the number of iterations of the GOMP algorithm is set to 2, the SAMP algorithm and the DC-GRSAMP algorithm do not need to obtain the number of target scattering points, the initial step size is set to 1, and the signal-to-noise ratio is set to 10 dB.

[0154] Figure 3 In order to draw the distance-velocity detection plane under the coarse resolution distance unit after sparse reconstruction by the GOMP algorithm, the distance-velocity detection plane under the coarse resolution distance unit is drawn from Figure 3 It can be seen that the detection plane obtained by the GOMP algorithm only has two peaks, and the distance and velocity information of all scattering points cannot be reconstructed.

[0155] Figure 4 In order to draw the distance-velocity detection plane under the coarse resolution distance unit after sparse reconstruction by the SAMP algorithm, the distance-velocity detection plane under the coarse resolution distance unit is drawn from Figure 4 It can be seen that the detection plane obtained by the SAMP algorithm has multiple pseudo-peaks in addition to the target scattering points.

[0156] Figure 5 In order to draw the distance-velocity detection plane under the coarse resolution distance unit after sparse reconstruction by the DC-GRSAMP algorithm, the distance-velocity detection plane under the coarse resolution distance unit is drawn from Figure 5 It can be seen that the target scattering point information detected by the DC-GRSAMP algorithm is correct, and the distance and velocity information of all targets can be accurately reconstructed.

[0157] In order to compare the distance and velocity parameter estimation performance of the DC-GRSAMP algorithm, the SAMP algorithm and the GOMP algorithm under different signal-to-noise ratios, the distance and velocity parameter estimation probability curves corresponding to the three sparse processing algorithms under different signal-to-noise ratios are calculated and drawn, as shown in Figure 6 It can be seen from Figure 6It can be seen that, when the signal-to-noise ratio is 10 dB, the distance and velocity parameter estimation probabilities of the DC-GRSAMP algorithm are 20% and 24% higher than those of the SAMP algorithm and the GOMP algorithm, respectively. Therefore, the DC-GRSAMP algorithm has higher distance and velocity parameter estimation probabilities than the SAMP algorithm and the GOMP algorithm in the case of low signal-to-noise ratio.

[0158] The signal-to-noise ratio is set to 20 dB, and the distance and velocity parameter estimation performances of the DC-GRSAMP algorithm, the SAMP algorithm, and the GOMP algorithm in the case of different target scattering point quantities are compared. The distance and velocity parameter estimation probability curves corresponding to the three sparse processing algorithms in the case of different target scattering point quantities are calculated and plotted by experiments, as shown in FIG. 4. Figure 7 Figure 7 It can be seen that, in the case of a large number of target scattering points, the distance and velocity parameter estimation probabilities of the DC-GRSAMP algorithm are higher than those of the SAMP algorithm and the GOMP algorithm.

[0159] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0160] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The functions specified in one or more flows and / or blocks.

[0161] These computer program instructions can also be stored in a computer readable storage medium that can guide the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer readable storage medium produce a manufactured product including instruction devices that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The functions specified in one or more flows and / or blocks. ​

[0162] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate computer-implemented processes, so that the instructions executed on the computer or other programmable devices provide operational steps for implementing the functions specified in the flowchart Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0163] The embodiments of the present application are described above with reference to the accompanying drawings, but the present application is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative, but not restrictive, and those of ordinary skill in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which are all within the protection of the present application.

Claims

1. A method of estimating range and velocity parameters for a frequency-agile radar, characterized by, The method comprises the following steps: acquiring a frequency-agile radar echo signal reflected by a target; performing pulse compression processing on the frequency-agile radar echo signal to obtain a pulse-compressed frequency-agile radar echo signal; calculating a coarse resolution range cell and a velocity unambiguous range of the pulse-compressed frequency-agile radar echo signal, dividing the coarse resolution range cell into a high-resolution range cell according to a frequency hopping point number of the pulse-compressed frequency-agile radar echo signal, and dividing the velocity unambiguous range into a velocity resolution cell according to a pulse number of the pulse-compressed frequency-agile radar echo signal; constructing a range-velocity dictionary matrix according to the high-resolution range cell and the velocity resolution cell; sampling a pulse compression peak point of the pulse-compressed frequency-agile radar echo signal to obtain an observation matrix of the pulse-compressed frequency-agile radar echo signal; solving a sparse solution vector corresponding to the observation matrix in the range-velocity dictionary matrix based on a Dice coefficient and a generalized regularization sparsity adaptive matching pursuit algorithm according to the range-velocity dictionary matrix; and reconstructing the sparse solution vector according to the high-resolution range cell and the velocity resolution cell to obtain a range and velocity parameter estimation result of the frequency-agile radar.

2. The method of claim 1, wherein, The acquiring of the frequency-agile radar echo signal reflected by the target comprises the following steps: transmitting a frequency-agile radar transmission signal to a target and receiving a frequency-agile radar echo signal reflected by the target, wherein the frequency-agile radar transmission signal is represented as: ； ； wherein, represents a frequency-modulated radar transmission signal at the tth time; represents a pulse width of the frequency-modulated radar transmission signal; represents a linear frequency hopping rate; represents a carrier frequency of the mth pulse; represents an imaginary unit; represents a standard rectangular window function; represents an exponential function; represents a radar initial carrier frequency; represents a frequency hopping point number; represents a minimum frequency hopping interval; represents a pulse number.

3. The method of claim 1, wherein, The pulse-compressed frequency-agile radar echo signal is represented as: ； wherein, represents the pulse pressure variable frequency radar echo signal of the mth pulse at the tth moment; represents the scattering coefficient of the target scattering point; represents the speed of light; represents the linear frequency hopping rate; represents the pulse width of the variable frequency radar transmitting signal; represents the tth moment of the mth pulse; represents the radar pulse repetition period; represents the echo time delay; represents the straight line distance between the radar and the target; represents the radar initial carrier frequency; represents the frequency hopping point number; represents the minimum frequency hopping interval; represents the radial velocity of the target; represents the noise of the mth pulse at the tth moment; represents the imaginary unit; represents the exponential function.

4. The method of claim 1, wherein, The high-resolution range cell is represented as: ； The number of the high-resolution range cells is represented as: ； wherein, represents a high-resolution range cell; represents the speed of light; represents the total bandwidth covered by the waveform of the agile frequency radar transmit signal in the frequency domain; represents the number of frequency hopping points; represents the minimum frequency hopping interval; represents the number of high-resolution range cells; represents the baseband transmit signal bandwidth of the agile frequency radar.

5. The method of claim 1, wherein, The velocity resolution cell is represented as: ； The number of the velocity resolution cells is represented as: ； wherein, denotes a velocity resolution unit; denotes the speed of light; denotes a radar initial carrier frequency; denotes a number of pulses; denotes a radar pulse repetition period; denotes a number of velocity resolution units.

6. The method of claim 1, wherein, The range-velocity dictionary matrix is represented as: ； ； wherein, denotes a range-velocity dictionary matrix; denotes a high-resolution range cell of the mth pulse; denotes a velocity resolution cell of the mth pulse; denotes a straight-line range between the radar and the target; denotes a number of frequency hops; denotes a minimum frequency hop interval; denotes the speed of light; denotes a radial velocity of the target; denotes a radar initial carrier frequency; denotes a radar pulse repetition period; denotes the imaginary unit; denotes the exponential function.

7. The method of claim 1, wherein, The observation matrix of the pulse-compressed frequency-agile radar echo signal is represented as: ； ； wherein, represents an observation matrix of the pulse compression frequency-agile radar echo signal; represents a range-velocity dictionary matrix; represents a sparse solution vector in the observation matrix of the pulse compression frequency-agile radar echo signal on the range-velocity two-dimensional plane; represents noise; represents a scattering coefficient of a target scattering point; represents the speed of light; represents a linear frequency hopping rate; represents a pulse width of the frequency-agile radar transmitting signal; represents the t-th moment of the m-th pulse; represents a radar pulse repetition period; represents an echo time delay; represents a straight-line distance between the radar and the target; represents an initial carrier frequency of the radar; represents an imaginary unit; represents an exponential function.

8. The method of claim 1, wherein, The solving of the sparse solution vector corresponding to the observation matrix in the range-velocity dictionary matrix based on the Dice coefficient and the generalized regularization sparsity adaptive matching pursuit algorithm according to the range-velocity dictionary matrix comprises the following steps: Initialization residual , index set , support set ; wherein denotes the empty set; At the tth iteration, compute the Dice matching coefficient between each atom vector in the distance-velocity dictionary matrix and the residual from the t-1th iteration ;​ Selecting the Dice matching coefficient The num atom vectors with the largest absolute values are selected, and their indices in the distance-velocity dictionary matrix are recorded to obtain an increasing index set of the tth iteration And the increasing support set ; an augmented index set according to the tth iteration and an augmented support set updating the atomic index set and the support set to obtain an index set and a support set of the tth iteration; wherein denotes the index set of the (t-1)th iteration; denotes the support set of the (t-1)th iteration; Calculate the estimated value of the pulse compression frequency agile radar echo signal in the t-th iteration. Based on preset regularization conditions, the estimated value of the pulse compression frequency agile radar echo signal in the t-th iteration is obtained. Grouping is performed to obtain grouped signals; selecting a set of packet signals having the largest energy to obtain a new index set of the tth iteration and a new support set ; new index set according to the tth iteration and new support set , compute a reconstructed signal estimate value for the tth iteration and update the residual for the tth iteration ; If or the maximum number of iterations G is reached, the iteration is stopped and the reconstructed signal estimate of the tth iteration is output , the reconstructed signal estimate of the tth iteration is a sparse solution vector in the observation matrix of the pulse compression radar echo signal; wherein, denotes a preset threshold value; denotes solving the norm; If , and the maximum number of iterations G is not reached, the iteration stage is updated as , the step size is updated as , the support set size is updated as , and the t+1th iteration is updated; wherein denotes the iteration stage before the update; denotes the step size before the update; denotes the support set size before the update. If , and the maximum number of iterations G is not reached, the new index set of the tth iteration is updated as and the t+1th iteration is updated; where denotes the new index set of the t-1th iteration.

9. The method of claim 8, wherein, each atom vector in the distance-velocity dictionary matrix and the residual of the t-1th iteration the Dice matching coefficient between is represented as: ； wherein, denotes matrix transpose; denotes the computation of the Dice match coefficient.

10. The method of claim 8, wherein, the pulse compression radar return signal estimate of the tth iteration is represented as: ； The preset regularization condition is represented as: ； the residual of the tth iteration is represented as: ； wherein, denotes the index set of the t-th iteration denotes the corresponding distance-velocity dictionary matrix; denotes the new index set of the t-th iteration denotes the corresponding distance-velocity dictionary matrix; , denote the signal estimate value of the a-th element, the signal estimate value of the b-th element of the support set of the t-th iteration, respectively; denotes the matrix transpose.

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