A method and device for airspace dynamic planning detection and track-before-track based on a general radar

Abstract

The application provides a space domain dynamic programming detection pre-tracking method and device based on a general radar. The method comprises the following steps: obtaining a multi-beam echo signal model of the general radar, and obtaining a space domain measurement matrix based on the multi-beam echo signal model; performing matrix division on the space domain measurement matrix according to a preset rule to obtain a sub-space domain measurement matrix, and performing coherent accumulation processing in each sub-space domain measurement matrix to obtain a space domain measurement data set and a velocity measurement set; performing non-coherent accumulation on a target in the space domain measurement data set based on the velocity measurement set and a dynamic programming algorithm to obtain a value function; performing threshold judgment on the value function to screen actual targets in the value function that satisfy a threshold value as a target state set; and performing track backtracking processing on the actual targets in the target state set to obtain final track information. The general radar improves the simultaneous detection capability of multiple weak moving targets in the space domain, and achieves a good balance between detection performance and computational complexity.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of radar signal processing, and particularly relates to a space domain dynamic programming detection pre-tracking method and device based on a panoramic radar. BACKGROUND

[0002] The radar of the traditional beam scanning system usually adopts the method of prolonging the observation time to enhance the detection capability of weak targets, but with the increase of the beam residence time, the cross-range abrupt change, cross-Doppler abrupt change and cross-beam abrupt change caused by target maneuverability seriously affect the performance of the coherent accumulation algorithm. In this case, the signals from the same target received by the radar will be scattered in different range cells, Doppler cells and beam cells, so that the range variation in the echo signal is coupled with the high-order variables. The conventional signal processing algorithm is difficult to accumulate enough energy to pass the CFAR threshold, and even if the non-coherent accumulation is performed using the processing results of the echo data of multiple scanning periods, it is also difficult to establish a stable track for the targets with strong maneuverability and high stealth performance, so that the radar of the traditional beam scanning system cannot realize effective tracking of weak targets.

[0003] The panoramic radar is a new system radar which transmits an omnidirectional beam and receives multiple narrow beams at the same time, and is a product of the combination of signal processing and phased array digital beam forming technology. The panoramic radar has no interval in the coverage space and detection time, has the ability to obtain multi-directional target information in space at the same time, can detect all targets and start tracking at an early time, and has good working performance in complex conditions such as strong clutter, low RCS and multiple targets.

[0004] During the working of the panoramic radar, each receiving beam keeps staring at the specified space domain, and the accumulation time is only affected by the system correlation and target motion characteristics, so that long-time accumulation of targets in the whole space domain can be realized without being limited by the beam residence time. However, during the accumulation process, the complex and variable target model and the three-cross problem appearing at any time still cause the energy of the long-distance target with high speed to be dispersed in the space domain, so that the detection probability of the weak moving target is still low. SUMMARY

[0005] In order to solve the above problems in the prior art, the application provides a space domain dynamic programming detection pre-tracking method and device based on a panoramic radar.

[0006] The technical problem to be solved by the application is solved by the following technical scheme.

[0007] In a first aspect, the application provides a space domain dynamic programming detection pre-tracking method based on a panoramic radar, comprising:

[0008] A multi-beam echo signal model of the panoramic radar is obtained, and a spatial measurement matrix is obtained based on the multi-beam echo signal model;

[0009] The spatial measurement matrix is divided into sub-spatial measurement matrices according to a preset rule, and coherent accumulation processing is performed in each sub-spatial measurement matrix to obtain a spatial measurement data set and a velocity measurement set;

[0010] Based on the velocity measurement set and a dynamic programming algorithm, non-coherent accumulation is performed on targets in the spatial measurement data set to obtain a value function;

[0011] The value function is subjected to threshold decision to screen actual targets in the value function that satisfy a threshold value as a target state set;

[0012] Actual targets in the target state set are subjected to track backtracking processing to obtain final track information.

[0013] Optionally, the multi-beam echo signal model of the panoramic radar is obtained, and the spatial measurement matrix is obtained based on the multi-beam echo signal model, including:

[0014] The multi-beam echo signal model of the panoramic radar is obtained;

[0015] The multi-beam echo signal model is subjected to two-dimensional matrix processing in fast time and slow time to obtain the spatial measurement matrix.

[0016] Optionally, the spatial measurement matrix is represented as:

[0017]

[0018] wherein, represents the spatial measurement matrix, tk represents fast time, t m represents slow time, R(t m ) represents a radial distance of a target in an observation region changing with slow time, B represents a bandwidth of a signal transmitted by the panoramic radar, c represents a speed of light, represents a center direction of a bearing dimension beam, A represents an amplitude gain of beam forming, represents an initial angle of bearing of the target, represents an angular velocity of bearing of the target, exp(.) represents a natural exponential function, j represents an imaginary unit, f c is a carrier frequency, and sinc(.) represents a sinc function.

[0019]

[0020] sin(x) represents a sine function, and x represents an independent variable.

[0021]

[0022] R0 represents the initial distance of the target, v represents the radial velocity of the target, and a represents the acceleration of the target.

[0023] Optionally, the spatial domain measurement matrix is divided into sub-spatial domain measurement matrices according to a preset rule, and coherent accumulation processing is performed in each sub-spatial domain measurement matrix to obtain a spatial domain measurement data set and a velocity measurement set, including:

[0024] According to the pulse signal detection range of the panoramic radar, the spatial domain measurement matrix is divided into sub-spatial domain measurement matrices;

[0025] The echo signals in the sub-spatial domain measurement matrix are subjected to coherent accumulation using the RFT algorithm to obtain sub-section beam echo signals;

[0026] The sub-section beam echo signals are subjected to range gate velocity search, and the peak values of the range gate velocity search constitute the spatial domain measurement data set and the velocity measurement set.

[0027] Optionally, the sub-section beam echo signals are represented as:

[0028]

[0029] wherein, represents the sub-section beam echo signal, represents the search radial distance of the kth sub-section, represents the search radial velocity of the kth sub-section, A rv represents the RFT algorithm amplitude gain corresponding to the radial distance r and the radial velocity v in the kth sub-section, A l represents the signal amplitude of the target received by the lth beam, M sub represents the number of pulses in the kth sub-section, and sinc(.) represents a sinc function.

[0030]

[0031] sin(x) represents a sine function, and x represents an independent variable.

[0032] R k0 represents the initial radial distance of the target in the kth sub-section, v k represents the velocity of the target in the kth sub-section, B represents the bandwidth of the signal transmitted by the panoramic radar, c represents the speed of light, δ represents an impulse function, j represents an imaginary unit, and f c is a carrier frequency; and exp(.) represents a natural exponential function.

[0033] Optionally, based on the velocity measurement set and a dynamic programming algorithm, the targets in the spatial domain measurement data set are subjected to non-coherent accumulation to obtain a value function, including:

[0034] Initialize the accumulation value function and the state transition matrix based on first measurement data in the airspace measurement data set, to obtain an initialized accumulation value function and an initialized state transition matrix; the first measurement data is first frame measurement data in the airspace measurement data set;

[0035] Based on the velocity measurement set, the initialized accumulation value function and the initialized state transition matrix, sequentially perform position search and state transition processing on second measurement data in the airspace measurement data set under the planning processing of the dynamic programming algorithm, to obtain a value function; the second measurement data is measurement data in the airspace measurement data set except the first frame measurement data.

[0036] Optionally, the value function is subjected to threshold decision, to screen actual targets in the value function that meet a threshold value as a target state set, comprising:

[0037] The target corresponding to the value function greater than the threshold value is taken as an actual target;

[0038] All actual targets are taken to form the target state set.

[0039] In a second aspect, the present application provides an airspace dynamic programming detection front tracking device based on a panoramic exploration radar, comprising an acquisition unit, a division unit, an accumulation unit, a decision unit and a state backtracking unit;

[0040] The acquisition unit is used to acquire a multi-beam echo signal model of the panoramic exploration radar, and obtain an airspace measurement matrix based on the multi-beam echo signal model;

[0041] The division unit is used to perform matrix division on the airspace measurement matrix according to a preset rule, to obtain a sub-airspace measurement matrix, and perform coherent accumulation processing in each sub-airspace measurement matrix, to obtain an airspace measurement data set and a velocity measurement set;

[0042] The accumulation unit is used to perform non-coherent accumulation on targets in the airspace measurement data set based on the velocity measurement set and a dynamic programming algorithm, to obtain a value function;

[0043] The decision unit is used to perform threshold decision on the value function, to screen actual targets in the value function that meet a threshold value as a target state set;

[0044] The state backtracking unit is used to perform track backtracking processing on targets in the target state set, to obtain final track information.

[0045] In a third aspect, the present application provides a space domain dynamic programming track-while-scan system based on a panoramic radar, comprising a processor, a storage medium and a bus, the storage medium storing machine readable instructions executable by the processor, the processor communicating with the storage medium through the bus when the space domain dynamic programming track-while-scan system is running, and the processor executing the machine readable instructions to perform the steps of the method of the first aspect.

[0046] In a fourth aspect, the present application provides a storage medium, the storage medium storing a computer program, the computer program being executed by the processor to perform the steps of the method of the first aspect.

[0047] The present application provides a space domain dynamic programming track-while-scan method and device based on a panoramic radar. The space domain dynamic programming track-while-scan method based on a panoramic radar comprises: obtaining a multi-beam echo signal model of the panoramic radar, and obtaining a space domain measurement matrix based on the multi-beam echo signal model; performing matrix division on the space domain measurement matrix according to a preset rule to obtain a sub-space domain measurement matrix, and performing coherent accumulation processing in each sub-space domain measurement matrix to obtain a space domain measurement data set and a velocity measurement set; performing non-coherent accumulation on targets in the space domain measurement data set based on the velocity measurement set and a dynamic programming algorithm to obtain a value function; performing threshold judgment on the value function to screen actual targets in the value function that meet a threshold value as a target state set; and performing track back processing on the actual targets in the target state set to obtain final track information. In the present application, the space domain measurement matrix is divided into several sub-sections, and dynamic programming track-while-scan is performed according to the distribution characteristics of the coherent accumulation results in the sub-sections, thereby converting the originally complex three-dimensional search problem into a plurality of two-dimensional search decision processes, reducing the algorithm operation time, solving the problem of target energy dispersion caused by "three-crossing" in the long-time accumulation process, improving the simultaneous detection capability of the panoramic radar for multiple weak moving targets in the space domain, and achieving a good balance between detection performance and computational complexity.

[0048] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 A flowchart of a space domain dynamic programming track-while-scan method based on a panoramic radar provided for an embodiment of the present application;

[0050] Figure 2 A measurement plane configuration diagram provided for an embodiment of the present application;

[0051] Figure 3 A flowchart of obtaining a value function through non-coherent accumulation provided for an embodiment of the present application;

[0052] Figure 4The target provided by the embodiment of the present application is aimed at detecting the beam steepness graph in the azimuth dimension of the space domain;

[0053] Figure 5 The target provided by the embodiment of the present application is aimed at the result graph of processing the echo signal of the beam by using the moving target detection algorithm when entering and leaving the beam;

[0054] Figure 6 The target provided by the embodiment of the present application is aimed at the result graph of using the RFT algorithm for coherent accumulation when there is a target in the beam subsegment;

[0055] Figure 7 The target provided by the embodiment of the present application is aimed at the value function accumulation result graph of the dynamic programming detection and tracking algorithm;

[0056] Figure 8 The target provided by the embodiment of the present application is aimed at the track backtracking result graph of the space domain target detection;

[0057] Figure 9 The target provided by the embodiment of the present application is aimed at the result graph of using the RFT algorithm for coherent accumulation when there are multiple targets in the beam subsegment;

[0058] Figure 10 The target provided by the embodiment of the present application is aimed at the value function accumulation result graph of the dynamic programming detection and tracking algorithm for multiple targets;

[0059] Figure 11 The target provided by the embodiment of the present application is aimed at the track classification and fusion result graph of the space domain multiple target detection;

[0060] Figure 12 The target provided by the embodiment of the present application is aimed at the structure schematic diagram of the space domain dynamic programming detection and tracking device based on the all-round exploration radar;

[0061] Figure 13 The target provided by the embodiment of the present application is aimed at the schematic diagram of the space domain dynamic programming detection and tracking system based on the all-round exploration radar. DETAILED DESCRIPTION

[0062] The present application will be further described in detail below in combination with specific embodiments, but the embodiments of the present application are not limited thereto.

[0063] In order to improve the simultaneous detection capability of the all-round exploration radar for multiple weak moving targets in the space domain, the embodiment of the present application provides a space domain dynamic programming detection and tracking method based on the all-round exploration radar. Figure 1 The flow schematic diagram of the space domain dynamic programming detection and tracking method based on the all-round exploration radar provided by the embodiment of the present application is shown in FIG. 1. Figure 1 As shown in FIG. 1, it comprises:

[0064] S101, obtaining the multi-beam echo signal model of the all-round exploration radar, and obtaining the space domain measurement matrix based on the multi-beam echo signal model.

[0065] Optionally, step S101 can specifically include:

[0066] obtaining a multi-beam echo signal model of the panoramic radar;

[0067] performing two-dimensional matrix processing of fast time-slow time on the multi-beam echo signal model to obtain a spatial domain measurement matrix.

[0068] Optionally, the spatial domain measurement matrix can be expressed as:

[0069]

[0070] wherein, represents the spatial domain measurement matrix, tk represents fast time, t m represents slow time, R(t m ) represents a radial distance of a target in an observation area varying with slow time, B represents a bandwidth of a signal transmitted by the panoramic radar, c represents a light speed, represents a center direction of a beam in the azimuth dimension, A represents an amplitude gain of beam forming, represents an initial azimuth angle of the target, represents an azimuth angular velocity of the target, exp(.) represents a natural exponential function, j represents an imaginary unit, f c represents a carrier frequency, and sinc(.) represents a sinc function.

[0071]

[0072] sin(x) represents a sine function, and x represents an independent variable.

[0073]

[0074] R0 represents an initial distance of the target, v represents a radial velocity of the target, and a represents an acceleration of the target.

[0075] A multi-beam echo signal model of an existing panoramic radar is generally expressed as:

[0076] It is assumed that a receiving antenna of the panoramic radar is a two-dimensional uniform planar array with X*Y, the receiving directional diagram of which is wide in the elevation dimension and narrow in the azimuth dimension. The panoramic radar works by scanning in the elevation dimension and simultaneously forming multiple beams in the azimuth dimension, and separates targets in the distance by transmitting a frequency-modulated continuous wave. A linear frequency-modulated signal s(t) transmitted by the radar is:

[0077]

[0078] In the formula, the rect function is a rectangular function, and the mathematical expression thereof is t is a radar transmission time, x is an independent variable, T pis the pulse width, j is the imaginary unit, π is the circular constant, and μ = B / T p is the frequency modulation rate, B is the bandwidth of the signal, and f c is the carrier frequency.

[0079] It is assumed that the observation time of the omni-probe radar is T, and the pulse repetition period is T t , M = T / T p pulses are received in the observation time, the coordinates of the array elements are (p x , p y ) (p x , p y are the x and y axis coordinates corresponding to the positions of the array elements) The transformed result s r (t, p x , p y ) of the echo signal received by the array element antenna after digital down conversion and pulse compression is as follows:

[0080]

[0081] R(t) is the radial distance of the target in the observation area with respect to the radar transmission time, θ r0 is the initial pitch angle, ω θ is the pitch angle velocity, is the initial azimuth angle, is the azimuth angle velocity, and c is the speed of light.

[0082] The omni-probe radar scans in the pitch dimension, simultaneously transmits multiple beams at L angles in the azimuth dimension, the width of each beam is , and samples N distance gates, to obtain the multi-beam echo signal model of the target at a certain angle in the pitch dimension as follows:

[0083] The multi-beam echo signal model is processed in the fast-time-slow-time two-dimensional matrix to obtain a spatial measurement matrix.

[0084] S102, the spatial measurement matrix is divided into sub-spatial measurement matrices according to a preset rule, and coherent accumulation processing is performed in each sub-spatial measurement matrix to obtain a spatial measurement data set and a velocity measurement set.

[0085] Optionally, step S102 can specifically include:

[0086] According to the pulse signal detection range of the omni-probe radar, the spatial measurement matrix is divided into sub-spatial measurement matrices;

[0087]

[0088] ​The echo signals in the sub-space measurement matrix are coherently accumulated using the RFT algorithm to obtain sub-beam echo signals.

[0089] The sub-beam echo signals are subjected to range gate velocity search, and the peak values of the range gate velocity search are used to form a space measurement data set and a velocity measurement set.

[0090] In the embodiment, the space measurement matrix is divided into multiple sub-sections according to the detection range of the panoramic radar pulse signal, and the sub-sections satisfy that the target does not cross the beams in the sub-sections. In each sub-section, the RFT algorithm is used for coherent accumulation of each beam. In the RFT algorithm, the peak value of each range cell velocity search is used to form a beam-range data plane, and the peak value corresponding to the velocity is recorded to form a measurement velocity matrix. The above steps are repeated for all sub-sections to obtain a space measurement data set and a velocity measurement set.

[0091] In the embodiment, the sub-space measurement matrix s rl (t,t h ,k) can be expressed as:

[0092]

[0093] wherein t h is the echo delay of the hth=1, 2, …, M sub pulse in the sub-section (M sub represents the number of pulses in the kthsub-section), R k0 , v k , and a k represent the initial radial distance, velocity, and acceleration of the target in the kthsub-section.

[0094] It can be seen from the sub-space measurement matrix that after the segmentation according to the specific constraint condition, the target only has the distance jump and Doppler jump phenomena caused by the radial velocity in each beam of the sub-section, and almost no beam jump phenomenon occurs. Therefore, the RFT algorithm can be used for coherent accumulation of the echo signals of each beam in each sub-section. After the RFT algorithm processing, the echo signal of the lthbeam in the kthsub-section can be approximately expressed as

[0095] Alternatively, the sub-beam echo signal can be expressed as:

[0096]

[0097] wherein, represents the sub-beam echo signal, represents the search radial distance of the kthsub-section, represents the search radial velocity of the kthsub-section, and A rvA represents the amplitude gain of the RFT algorithm corresponding to the radial distance r and radial velocity v in the k-th sub-segment. l M represents the signal amplitude received from the target by the l-th beam. sub This indicates the number of pulses in the k-th sub-segment, and sinc(.) represents the sinc function;

[0098]

[0099] sin(x) represents the sine function, where x represents the independent variable;

[0100] R k0 v represents the initial radial distance of the target within the k-th sub-segment. k Let B represent the velocity of the target in the k-th sub-segment, B represent the bandwidth of the radar signal, c represent the speed of light, δ represent the impulse function, j represent the imaginary unit, and f represent the velocity of the target in the k-th sub-segment. c is the carrier frequency; exp(.) represents the natural exponential function.

[0101] The peak values ​​of the range gate velocity search within each beam are used to construct the beam-range measurement plane Z. k and velocity measurement matrix V k Repeating this operation for all segments yields a spatial measurement dataset of K segments:

[0102] Z 1:K =(Z1,Z2,…,Z K );

[0103] And the velocity measurement set of K segments:

[0104] V 1:K =(V1,V2,…,V K );

[0105] Among them, Z K and V K These represent the airspace measurement data and velocity measurement data of the Kth sub-segment, respectively, where K represents the total number of sub-segments.

[0106] like Figure 2 The diagram shown is a schematic representation of the measurement plane configuration provided in an embodiment of the present invention. Figure 2 As shown, the peak values ​​of the velocity search at each range gate within the beam are taken to form the spatial measurement data Z. k and velocity measurement data V k .

[0107] Specifically, assuming the pan-penetrating radar simultaneously scans L angles with multiple beams, and each beam samples N range gates, then Z k Let L*N be a two-dimensional data matrix, representing the radar measurement data in the k-th sub-segment:

[0108] Z k = {z k (l,n), 1≤l≤L, 1≤n≤N;

[0109] each resolution cell z k (l,n) in the measurement plane is independently and identically distributed, and its statistical property is:

[0110]

[0111] wherein, represents the signal amplitude from the target, w k (l,n) represents the background noise in the resolution cell.

[0112] After repeating the operation for all sub-sections, the spatial measurement data set of the Kth section can be obtained:

[0113] Z 1:K = (Z1,Z2,…,Z K );

[0114] and the velocity measurement set:

[0115] V 1:K = (V1,V2,…,V K );

[0116] S103, based on the velocity measurement set and the dynamic programming algorithm, non-coherent accumulation is performed on the target in the spatial measurement data set to obtain a value function.

[0117] Optionally, the step S103 can specifically include:

[0118] based on the first measurement data in the spatial measurement data set, initialization processing is performed on the accumulation value function and the state transition matrix to obtain an initialized accumulation value function and an initialized state transition matrix; the first measurement data is the first frame of measurement data in the spatial measurement data set;

[0119] based on the velocity measurement set, the initialized accumulation value function and the initialized state transition matrix, under the planning processing of the dynamic programming algorithm, position search and state transition processing are sequentially performed on the second measurement data in the spatial measurement data set to obtain the value function; the second measurement data is the measurement data in the spatial measurement data set except the first frame of measurement data.

[0120] In the embodiment, the first frame of measurement data Z1 in the spatial measurement data set is used to initialize the accumulation value function and the state transition trajectory.

[0121] After the initialization, the remaining measurement data Z kThe process involves iterative accumulation of values, where 2 ≤ k ≤ K. During each iteration, the target crosses multiple distance cells due to the influence of radial velocity. To narrow the state search range, the velocity measurement set V is first used. k 2≤k≤K calculate the possible positions of each state in the previous sub-segment, then use a smaller state transition range to search for that position, and finally perform a state transition on the most likely position of the target obtained from the search, and record the historical transition path.

[0122] When k = K, the iteration ends, and the value function I is obtained after accumulating all K sub-segments. K (l,n). Where l represents the l-th beam and n represents the number of observation frames.

[0123] like Figure 3 The diagram shown is a schematic representation of the process for obtaining a value function through incoherent accumulation, as provided in an embodiment of the present invention. Figure 3 As shown, parameter initialization is first performed (including initializing the accumulation function and initializing the state transition matrix), and then the remaining measurement data Z is processed. k The iteration accumulates values ​​for 2 ≤ k ≤ K. Based on the velocity measurement matrix (velocity measurement set), the possible positions of each state in the previous frame or segment are calculated. The optimal transition state is searched within the transition range centered on the predicted position. The optimal transition state is then used for state transition. The iteration ends when k = K, yielding the value function I after accumulating all K segments. K (l,n).

[0124] The specific process includes:

[0125] First, the accumulation function and state transition matrix are initialized using the measurement data Z1:

[0126]

[0127] Among them, I k (l,n) represents the accumulated value function of the algorithm in the k-th sub-segment, located at the l-th azimuth angle and the n-th distance gate. k (l,n) is the value function of the measurement matrix of the k-th sub-segment, ψ k (l,n) stores the state transition trajectory of each frame, which is used to trace the target's movement trajectory.

[0128] Furthermore, after initialization, the non-coherent iterative accumulation of the measurement sequence using a dynamic programming algorithm can specifically include: when 2≤k≤K, for all states Z... k have:

[0129]

[0130] The arg function is used to take the argument τ of the function. k(l, n) represents a state transition range of the target, which is a set of all possible positions of the target when the target is transferred from the k-1th subsegment to the kth subsegment. is the maximum value of the value function in the range of (l, n) of the k-1th subsegment. Ik-1(i, j) is the value function corresponding to the position (i, j) in the range of (l, n) in the k-1th subsegment. k (l, n) range. Ik-1(i, j) is the value function corresponding to the position (i, j) in the range of (l, n) in the k-1th subsegment. k (l, n) range. Specifically, although the target can cross at most one beam unit between two adjacent subsegments, the radial velocity can cause the target to cross more distance units, and a larger state transition range can cause the computational complexity to increase exponentially. Therefore, in the search process, the velocity measurement set V 1:K is used to calculate the possible positions of each state in the previous subsegment, and a smaller state transition range is used to search the positions.

[0131] When k = K, the iteration ends, and the value function I K (l, n) of all K subsegments is obtained.

[0132] S104, threshold decision is performed on the value function to screen actual targets in the value function that satisfy a threshold value as a target state set.

[0133] Optionally, step S104 can specifically include:

[0134] targets corresponding to the value function greater than the threshold value as actual targets;

[0135] all actual targets form a target state set.

[0136] S105, track back processing is performed on the actual targets in the target state set to obtain final track information.

[0137] It should be noted that in this embodiment, the historical transition trajectories of all actual targets are recursively calculated in reverse order and stored in a track set T. The states in the track set T that have K s more identical points are merged into a class, and the state with the maximum accumulated value function is taken as the optimal state of the class and stored in a set F. The set F is the final track information of the actual targets detected finally.

[0138] The embodiment of the present application provides a kind of airspace dynamic programming detection pre-tracking method based on generic radar, comprising: obtaining the multi-beam echo signal model of generic radar, and obtaining airspace measurement matrix based on multi-beam echo signal model;According to preset rule, matrix division is carried out to airspace measurement matrix, and sub-airspace measurement matrix is obtained, and coherent accumulation processing is carried out in each sub-airspace measurement matrix, and airspace measurement data set and velocity measurement set are obtained;Based on velocity measurement set and dynamic programming algorithm, non-coherent accumulation is carried out to target in airspace measurement data set, and value function is obtained;Threshold decision is carried out to value function, to filter actual target meeting threshold threshold in value function as target state set;Actual target in target state set is processed by track backtracking, and final track information is obtained.In the embodiment of the present application, airspace measurement matrix is divided into several sub-sections, and dynamic programming detection pre-tracking is carried out according to the distribution characteristics of coherent accumulation result in sub-section, the originally complex three-dimensional search problem is converted into multiple two-dimensional search decision process, the algorithm operation time is reduced, the problem of target energy dispersion caused by "three cross" in long time accumulation process is solved, and the simultaneous detection capability of generic radar to multiple weak moving targets in airspace is improved, and good balance is achieved between detection performance and computational complexity.

[0139] In order to illustrate the effectiveness of the airspace dynamic programming detection pre-tracking method based on generic radar provided by the embodiment of the present application, simulation verification is also carried out in the embodiment of the present application.

[0140] (I) Simulation experiment condition

[0141] The number of array elements of the embodiment is 24*24, the radar transmitting signal carrier frequency f c =1.2GHz, the pulse repetition frequency PRF=1000Hz, the observation time T=2s, the total pulse number M=2000, the azimuth detection range of generic radar is 0°-60°, L=30 angles are simultaneously multi-beam, and the beam width The number of sampling points N=256 in each beam, and the signal-to-noise ratio SNR=-40dB.

[0142] The parameter setting of target 1 includes: the initial radial distance R0 of target=30km, the radial velocity v of target=620m / s, the radial acceleration a of target=100m / s 2 , the initial azimuth angle The azimuth angle velocity The parameter setting of target 2 includes: the initial radial distance R0 of target 2=30km, the radial velocity v=620m / s, the radial acceleration a=100m / s 2 , the initial azimuth angle The azimuth angle velocity The parameter setting of target 3 includes: initial radial distance R0 of target 3 = 30 km, radial velocity v = 620 m / s, and radial acceleration a = 100 m / s 2 , initial azimuth angle Azimuth angle velocity The parameter setting of target 2 includes: initial radial distance R0 of target 4 = 30 km, radial velocity v = 620 m / s, and radial acceleration a = 100 m / s 2 , initial azimuth angle Azimuth angle velocity

[0143] (ii) Simulation experiment content and result analysis

[0144] The embodiment of the application constructs simultaneous multi-beam echo data according to a signal model. When a radar scans a certain elevation angle, the simultaneous multi-beam forming result is obtained at the elevation angle, please refer to Figure 4 , Figure 5 , wherein, Figure 4 is a target in the detection space azimuth provided by the embodiment of the application. The beam steep motion chart occurs, Figure 5 is a result chart of the echo signal of the target entering and leaving the beam processed by the moving target detection algorithm (MTD) provided by the embodiment of the application. From Figure 4 , Figure 5 It can be seen that, within the beam residence time of a single elevation scan of the all-aspect radar, the target has obvious cross-beam unit steep motion, cross-range unit steep motion and cross-Doppler unit steep motion, which causes the energy to be dispersed in each beam unit, range unit and Doppler unit, and it is difficult to directly accumulate. Therefore, based on the shortcomings of the moving target detection algorithm, the RFT algorithm is used for coherent accumulation in the application.

[0145] Figure 6 is a result chart of using the RFT algorithm for coherent accumulation when there is a target in the beam sub-section provided by the embodiment of the application. From Figure 6 It can be seen that only when the beam in the sub-section receives the echo signal from the target, a relatively obvious peak value appears in the corresponding range and velocity search result.

[0146] Figure 7 is a value function accumulation result chart of the dynamic programming detection and tracking algorithm provided by the embodiment of the application, Figure 8 is a space target detection track backtracking result chart provided by the embodiment of the application, from Figure 8 It can be seen that after the non-coherent algorithm processing, the energy of the target is effectively accumulated along its moving path.

[0147] Please refer to Figures 9-11 , wherein, Figure 9is a coherent accumulation result graph of the RFT algorithm used when multiple targets exist in a beam subsection, provided by the embodiment of the present application, Figure 10 is a value function accumulation result graph of a multi-target dynamic programming detection pre-tracking algorithm, provided by the embodiment of the present application, Figure 11 is a track classification fusion result graph of a spatial multi-target detection, from Figures 9-11 It can be seen that the energy of each target is accumulated along the respective path and is distinguished and matched through the track classification fusion algorithm processing.

[0148] In summary, the spatial dynamic programming detection pre-tracking method based on a general exploration radar adopted by the present application, compared with the traditional three-dimensional search compensation algorithm, does not need to design a large number of compensation factors, but first segments the multi-beam echo signal according to the accumulation time, and then uses the dynamic programming multi-frame joint processing to make non-coherent accumulation on the coherent processing result in the segment, so as to obtain more detailed state information of the target and establish a stable and continuous tracking track. The present application improves the simultaneous detection capability of the general exploration radar for multiple weak moving targets in the airspace, and reduces the operation complexity of the algorithm. Through the above simulation, the effectiveness of the present application is verified.

[0149] The method provided by the embodiment of the present application can be applied to an electronic device. Specifically, the electronic device can be a desktop computer, a portable computer, a smart mobile terminal, a server, etc. Herein, it is not limited, and any electronic device that can implement the present application belongs to the protection scope of the present application.

[0150] Based on the same inventive concept, the embodiment of the present application also provides a spatial dynamic programming detection pre-tracking device based on a general exploration radar. Figure 12 A structural schematic diagram of a spatial dynamic programming detection pre-tracking device based on a general exploration radar provided by the embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, it includes an acquisition unit 601, a division unit 602, an accumulation unit 603, a decision unit 604 and a state backtracking unit 605. Figure 6

[0151] The acquisition unit 601 is used to acquire a multi-beam echo signal model of the general exploration radar, and obtain a spatial measurement matrix based on the multi-beam echo signal model.

[0152] The division unit 602 is used to perform matrix division on the spatial measurement matrix according to a preset rule, to obtain a sub-spatial measurement matrix, and perform coherent accumulation processing in each sub-spatial measurement matrix, to obtain a spatial measurement data set and a velocity measurement set.

[0153] The accumulation unit 603 is used to perform non-coherent accumulation on the target in the spatial measurement data set based on the velocity measurement set and a dynamic programming algorithm, to obtain a value function.

[0154] ​The decision unit 604 is configured to perform threshold decision on the value function to screen actual targets in the value function that satisfy a threshold as the target state set.

[0155] The state backtracking unit 605 is configured to perform track back processing on the targets in the target state set to obtain final track information.

[0156] Based on the same inventive concept, the embodiment of the present application further provides a space dynamic programming detection front tracking system based on a general exploration radar. Figure 13 A schematic diagram of a space dynamic programming detection front tracking system based on a general exploration radar provided by the embodiment of the present application comprises a processor 710, a storage medium 720 and a bus 730. The storage medium 720 stores machine readable instructions executable by the processor 710. When the space dynamic programming detection front tracking system based on a general exploration radar is running, the processor 710 and the storage medium 720 communicate through the bus 730. The processor 710 executes the machine readable instructions to perform the steps of the above-mentioned method embodiment. The specific implementation manner and technical effects are similar, and will not be described here again.

[0157] The storage medium can comprise a random access memory (RAM) and can also comprise a non-volatile memory (NVM), for example at least one disk memory. Optionally, the storage medium can also be at least one storage device located away from the aforementioned processor.

[0158] The processor mentioned above can be a general processor, including a central processing unit (CPU), a network processor (NP) and the like; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0159] The present application further provides a computer readable storage medium. The computer readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of any one of the above-mentioned space dynamic programming detection front tracking methods based on a general exploration radar are implemented.

[0160] It should be noted that the terms "first", "second", and so on are used herein to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with the present disclosure. Rather, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0161] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Also, the specific features or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in the present specification.

[0162] Although the present invention is described herein in conjunction with various embodiments, those skilled in the art, by viewing the drawings and the disclosure, can understand and implement other variations of the disclosed embodiments in the implementation of the claimed invention. In the description of the present invention, the word "comprising" does not exclude other components or steps, "one" or "an" does not exclude a plurality, and "plurality" means two or more, unless otherwise explicitly specified. In addition, some measures are described in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0163] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and cannot be considered as limiting the specific implementation of the present invention to these descriptions. For those skilled in the art, without departing from the concept of the present invention, a number of simple deductions or replacements can be made, which should be considered as falling within the scope of protection of the present invention.

Claims

1. A pre-detection tracking method for airspace dynamic planning based on generalized radar, characterized in that, include: Obtain the multi-beam echo signal model of the pan-penetrating radar, and obtain the spatial measurement matrix based on the multi-beam echo signal model; The spatial measurement matrix is ​​divided into sub-spatial measurement matrices according to preset rules, and coherent accumulation processing is performed in each sub-spatial measurement matrix to obtain a spatial measurement dataset and a velocity measurement dataset. Based on the velocity measurement set and the dynamic programming algorithm, incoherent accumulation is performed on the targets in the spatial measurement dataset to obtain the value function; A threshold decision is made on the value function to select actual targets that meet the threshold from the value function as the target state set; The actual targets in the target state set are subjected to trajectory backtracking processing to obtain the final trajectory information.

2. The airspace dynamic planning pre-detection tracking method based on generalized radar according to claim 1, characterized in that, The process of acquiring the multi-beam echo signal model of the pan-penetrating radar and obtaining the spatial measurement matrix based on the multi-beam echo signal model includes: Obtain the multi-beam echo signal model of the probe radar; The spatial measurement matrix is ​​obtained by performing fast-time-slow-time two-dimensional matrix processing on the multibeam echo signal model.

3. A pre-detection tracking method for airspace dynamic planning based on generalized radar according to claim 1 or 2, characterized in that, The spatial measurement matrix is ​​represented as follows: in, Let tk represent the spatial measurement matrix, and tk represent the fast time. m Representing slow time, R(t) m () represents the radial distance of the target within the observation area as a function of slow time, B represents the bandwidth of the radar's transmitted signal, and c represents the speed of light. A represents the center direction of the azimuth beam, and A represents the amplitude gain of the beamforming. Indicates the initial azimuth angle of the target. Let f be the azimuth angular velocity of the target, exp(.) denotes the natural exponential function, j denotes the imaginary unit, and f c For the carrier frequency, sinc(.) represents the sinc function; sin(x) represents the sine function, where x represents the independent variable; R0 represents the initial distance to the target, v represents the radial velocity of the target, and a represents the acceleration of the target.

4. The airspace dynamic planning pre-detection tracking method based on generalized radar according to claim 1, characterized in that, The spatial measurement matrix is ​​partitioned according to a preset rule to obtain sub-spatial measurement matrices, and coherent accumulation processing is performed within each sub-spatial measurement matrix to obtain a spatial measurement dataset and a velocity measurement set, including: Based on the pulse signal detection range of the general-purpose radar, the spatial measurement matrix is ​​divided into sub-spatial measurement matrices. The echo signal within the sub-spatial measurement matrix is ​​coherently accumulated using the RFT algorithm to obtain the sub-segment beam echo signal. A range-gate velocity search is performed on the sub-segment beam echo signal, and the peak values ​​of the range-gate velocity search are used to form the spatial measurement dataset and the velocity measurement set.

5. The airspace dynamic planning pre-detection tracking method based on generalized radar according to claim 4, characterized in that, The sub-segment beam echo signal is represented as follows: in, Indicates the sub-beam echo signal. This represents the radial distance of the search for the k-th sub-segment. A represents the radial velocity of the k-th sub-segment during the search. rv A represents the amplitude gain of the RFT algorithm corresponding to the radial distance r and radial velocity v in the k-th sub-segment. l M represents the signal amplitude received from the target by the l-th beam. sub This indicates the number of pulses in the k-th sub-segment, and sinc(.) represents the sinc function; sin(x) represents the sine function, where x represents the independent variable; R k0 v represents the initial radial distance of the target within the k-th sub-segment. k Let B represent the velocity of the target in the k-th sub-segment, B represent the bandwidth of the radar signal, c represent the speed of light, δ represent the impulse function, j represent the imaginary unit, and f represent the velocity of the target in the k-th sub-segment. c is the carrier frequency; exp(.) represents the natural exponential function.

6. The airspace dynamic planning pre-detection tracking method based on generalized radar according to claim 1, characterized in that, The step of performing incoherent accumulation of targets in the spatial measurement dataset based on the velocity measurement set and dynamic programming algorithm to obtain a value function includes: The accumulation function and the state transition matrix are initialized based on the first measurement data in the spatial domain measurement dataset to obtain the initialized accumulation function and the initialized state transition matrix; the first measurement data is the first frame of measurement data in the spatial domain measurement dataset. Based on the velocity measurement set, the initialization accumulation value function, and the initialization state transition matrix, the second measurement data in the spatial measurement dataset is sequentially subjected to position search and state transition processing under the planning processing of the dynamic programming algorithm to obtain the value function; the second measurement data is the measurement data in the spatial measurement dataset other than the measurement data of the first frame.

7. The airspace dynamic planning pre-detection tracking method based on generalized radar according to claim 1, characterized in that, The step of performing a threshold decision on the value function to select actual targets that meet the threshold threshold from the value function as the target state set includes: The target corresponding to the value function that is greater than the threshold is taken as the actual target; All the actual targets constitute the target state set.

8. A pre-detection tracking device for airspace dynamic planning based on general-purpose radar, characterized in that, include: Acquisition unit, partitioning unit, accumulation unit, decision unit, and state backtracking unit; The acquisition unit is used to acquire the multi-beam echo signal model of the pan-penetrating radar and obtain the spatial measurement matrix based on the multi-beam echo signal model. The partitioning unit is used to partition the spatial measurement matrix according to a preset rule to obtain sub-spatial measurement matrices, and to perform coherent accumulation processing within each sub-spatial measurement matrix to obtain a spatial measurement dataset and a velocity measurement dataset. The accumulation unit is used to perform incoherent accumulation of targets in the spatial measurement dataset based on the velocity measurement set and the dynamic programming algorithm to obtain the value function. The decision unit is used to perform threshold decision on the value function to select actual targets that meet the threshold threshold in the value function as the target state set; The state backtracking unit is used to perform track backtracking processing on the targets in the target state set to obtain the final track information.

9. A pre-detection tracking system based on general-purpose radar for airspace dynamic planning, characterized in that, include: The system includes a processor, a storage medium, and a bus. The storage medium stores machine-readable instructions executable by the processor. When the airspace dynamic planning detection-tracking system based on the panoptic radar is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the method as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, performs the steps of the method as described in any one of claims 1-7.

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