Motorized target tracking method, device, equipment and storage medium

Abstract

The application provides a method and device for tracking maneuvering targets based on adaptive wave gates, equipment and storage medium, the method comprising: obtaining echo information reflected by each target to be tracked; determining the association relationship between the association tracking gate of each target to be tracked and each measurement point according to the current echo information obtained at the current time and the predicted state information of each target to be tracked; determining the update information of the association tracking gate of each target to be tracked respectively according to the association relationship; updating the parameters of the association tracking gate respectively according to the update information; and tracking each target to be tracked based on the updated association tracking gate. The application aims to improve the accuracy of multi-maneuvering target tracking.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of target tracking, and particularly relates to a maneuvering target tracking method and device based on adaptive wave gates, equipment and a storage medium. BACKGROUND

[0002] In maneuvering target tracking, the prior art obtains independent observation features such as position, speed, signal-to-noise ratio, etc. of each measurement point by using a sensor, and then analyzes the independent observation features in combination with a target motion model. However, in actual application, on the one hand, the observation features that can be obtained are limited due to the performance of the sensor, and the spatiotemporal dimensional data of the observation features are not fully fused, so it is difficult to adapt to the mutation of the state of the target to be tracked, resulting in poor tracking effect; on the other hand, since the maneuvering target is unpredictable, there is a deviation between the process of describing the maneuvering target by using the target motion model and the actual state of the target, so that the tracking error is large. Therefore, how to improve the tracking effect of the maneuvering target is a technical problem to be solved. SUMMARY

[0003] Therefore, the embodiments of the present application provide a maneuvering target tracking method and device based on adaptive wave gates, equipment and a storage medium, which can adapt to the changes of the target maneuvering range and intensity in the process of tracking multiple maneuvering targets, and aims to improve the accuracy of tracking multiple maneuvering targets.

[0004] In a first aspect, the present application provides a maneuvering target tracking method based on adaptive wave gates, which comprises: obtaining echo information reflected by each target to be tracked; determining an association relationship between an association tracking gate of each target to be tracked and each measurement point according to current echo information obtained at a current time and predicted state information of each target to be tracked; determining update information of the association tracking gate of each target to be tracked respectively according to the association relationship; updating parameters of the association tracking gate respectively according to the update information; and tracking each target to be tracked based on the updated association tracking gate.

[0005] In a second aspect, the embodiments of the present application provide a maneuvering target tracking device based on adaptive wave gates, which comprises: an acquisition module configured to obtain echo information reflected by each target to be tracked; a first determination module configured to determine an association relationship between an association tracking gate of each target to be tracked and each measurement point according to current echo information obtained at a current time and predicted state information of each target to be tracked; a second determination module configured to determine update information of the association tracking gate of each target to be tracked respectively according to the association relationship; an update module configured to update parameters of the association tracking gate respectively according to the update information; and a tracking module configured to track each target to be tracked based on the updated association tracking gate.

[0006] Thirdly, this application provides an electronic device, comprising: a memory for storing a maneuvering target tracking program based on an adaptive gate; and a processor for executing the maneuvering target tracking program based on an adaptive gate to implement the steps of the maneuvering target tracking method based on an adaptive gate as described in the first aspect above.

[0007] Fourthly, this application provides a computer-readable storage medium storing a computer program product that, when run on an electronic device, causes the electronic device to perform the steps of the adaptive gate-based maneuvering target tracking method described in the first aspect.

[0008] The adaptive gate-based maneuvering target tracking method provided in the first aspect of this application firstly acquires the echo information reflected by each target to be tracked; then, based on the current echo information acquired at the current moment and the predicted state information of each target to be tracked, the correlation relationship between the associated tracking gate of each target to be tracked and each measurement point is determined; next, based on the correlation relationship, the update information of the associated tracking gate of each target to be tracked is determined, and the parameters of the associated tracking gate are updated according to the update information; finally, the target to be tracked is tracked based on the updated associated tracking gates. Since the technical solution of this application, based on the maximum likelihood tracking gate estimation algorithm, calculates the correlation relationship between the associated tracking gate of each target to be tracked and each measurement point based on the current echo information acquired at the current moment and the predicted state information of each target to be tracked, and then updates the associated tracking gate of the maneuvering target according to the correlation relationship, it can adaptively adapt to changes in the range and intensity of target maneuvering during multi-maneuvering target tracking, aiming to improve the accuracy of multi-maneuvering target tracking.

[0009] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A flowchart illustrating the adaptive gate-based maneuvering target tracking method provided in the application;

[0012] Figure 2 Provided for an embodiment of this application Figure 1 The detailed implementation flowchart of S102 in the middle;

[0013] Figure 3 A schematic diagram of an adaptive gate based maneuvering target tracking device is provided for the embodiments of the present application.

[0014] Figure 4 A schematic diagram of an electronic device is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0015] In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular architectures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail. It is also noted that the description of the embodiments of the present application is intended to cover all alternatives, modifications, and equivalents thereof. It is also noted that the terms "first", "second", "third", etc. are used herein solely to distinguish one element from another, and do not imply or suggest a relative importance of the elements.

[0016] It is also to be understood that the phraseology "one embodiment" or "the embodiment" as used herein does not necessarily refer to a single embodiment, rather, it is used to describe several embodiments of the application. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present application. Flowever, various implementation of the present application can be practiced without the specific details, which are set forth in the following description, and it is understood that the specification and drawings are not to be considered in a limiting sense in that it is understood that the present application can be practiced in other embodiments that do not include, or can include, all of the features.

[0017] Reference will now be made to Figure 1 , Figure 1 A flowchart of an adaptive gate based maneuvering target tracking method is provided for the embodiments of the present application. It is to be noted that in the present application, the adaptive gate based maneuvering target tracking method can be applied to process the echo data of a maneuvering target detected by a radar or other sensors, to achieve tracking of the maneuvering target, to improve the tracking effect, and to maintain stable tracking when the radar loses detection of the target. The adaptive gate based maneuvering target tracking method can be applied to an electronic device, which includes but is not limited to a robot, a vehicle, an aircraft, a ship, and other mobile devices equipped with a radar or other sensors.

[0018] As Figure 1As shown, the adaptive gate-based maneuvering target tracking method provided in this application includes steps S101 to S105. Details are as follows:

[0019] S101: Obtain echo information reflected by each target to be tracked.

[0020] The target to be tracked is a moving target detected by radar or other sensors. The radar or other sensors collect the echo information reflected in real time from each moving target, and the electronic equipment continuously acquires the echo information collected in real time by the radar or other sensors. For example, using a set... This represents the echo information reflected by each target to be tracked. The information vector representing the observed target to be tracked is denoted as: m represents the number of measurement points currently collected, and k represents the sampling time, such as the initial sampling time being k0.

[0021] It should be noted that after processing the acquired echo information reflected from each target to be tracked through intermediate frequency signal processing and threshold detection methods such as CFAR detection, the currently acquired observation point cloud map can be obtained. The information of each node in this observation point cloud map contains an n-dimensional state vector containing information such as the position and velocity of the target's reflected echo, where n is the observation dimension.

[0022] S102: Based on the current echo information obtained at the current moment and the predicted state information of each target to be tracked, determine the correlation relationship between the associated tracking gate of each target to be tracked and each measurement point.

[0023] Among them, the predicted state information of each target to be tracked

[0024] For example, such as Figure 2 As shown, Figure 2 Provided for an embodiment of this application Figure 1 The detailed implementation flowchart of S102 in the middle. Figure 2 It can be seen that S102 specifically includes S1021 and S1022. Details are as follows:

[0025] S1021, Calculate the observation status information of each target to be tracked at the current moment based on the current echo information.

[0026] For example, the observation status information of each target to be tracked at the current moment can be calculated based on the current echo information and the historical observation status information of each target at a historical moment.

[0027] For example, assuming there are N targets to be tracked at the current moment, the formula for calculating the observation state information of the i-th target (i = 1, 2, ..., N) at the current moment is as follows:

[0028]

[0029] wherein Φ(t i ) represents a state transition matrix, X i (k-t i ) represents a filtering value of a target state at the k-t i time, t j represents a time, preferably 1, when the number of measurement points in the tracking gate of the i-th target to be tracked at the k-1 time is 0, t i is 2, and so on, with an increment of 1 each time, t i is maximally represents a tracking gate time window of the target i. In particular, when k=k0, k is the time of adoption.

[0030] S1022, determining an association relationship between the tracking gate of each target to be tracked and each measurement point according to the observation state information and the prediction state information.

[0031] wherein the prediction state information can be represented by a state prediction covariance matrix. The state prediction covariance matrix of the i-th target to be tracked can effectively represent the probability density of the measurement points in the tracking gate of the i-th target to be tracked. Exemplarily, the state prediction covariance matrix can be calculated by the following formula:

[0032]

[0033] wherein Q i (k) represents a measurement noise matrix of the i-th target to be tracked, which is in the form of:

[0034]

[0035] wherein um(n) represents the variance of the measurement point located in the tracking gate of the i-th target to be tracked at the n-th observation dimension, which can be represented as: um(n) = (p n max -p n min ) 2 / 4 .

[0036] Then, the residual covariance matrix S i (k) of the state prediction of the i-th target to be tracked can be represented as:

[0037]

[0038] wherein H(k) represents an observation matrix; is the covariance matrix of the prediction state and the observation state of the i-th target to be tracked; Q i(k) is a measurement noise matrix of the observation value. The residual covariance matrix S i (k) can effectively represent the association relationship between the predicted state and the observation state of the i-th target to be tracked.

[0039] Exemplarily, the positional relationship between each target to be tracked and each measurement point can be calculated according to the observation state information and the predicted state information, respectively; and the association relationship between the association tracking gate of each target to be tracked and each measurement point can be determined according to the positional relationship.

[0040] Wherein, the positional relationship between each target to be tracked and each measurement point is calculated according to the observation state information and the predicted state information, respectively, including: for any target to be tracked, the Mahalanobis distance between the target to be tracked and each measurement point is calculated according to the observation state information and the predicted state information of the target to be tracked, respectively, and the Mahalanobis distance is taken as the positional relationship between the target to be tracked and each measurement point.

[0041] Specifically, the Mahalanobis distance between the i-th target to be tracked and the m-th measurement point can be represented by the norm of the filtering residual vector of the i-th target to be tracked and the m-th measurement point. Specifically, the filtering residual vector of the i-th target to be tracked and the m-th measurement point can be represented as:

[0042]

[0043] The norm of the filtering residual vector of the i-th target to be tracked and the m-th measurement point can be represented as:

[0044]

[0045] Wherein, i represents the target to be tracked, m represents the measurement point, and k represents the time.

[0046] S103: Update information of the association tracking gate of each target to be tracked is determined respectively according to the association relationship.

[0047] Wherein, the update information of the association tracking gate of each target to be tracked includes a tracking time window and a scale parameter; and the update information of the association tracking gate of each target to be tracked is determined respectively according to the association relationship, including: for any target to be tracked, the measurement points falling within the tracking gate of the target to be tracked at the current time can be determined according to the association relationship, and the tracking time window of the target to be tracked is determined; and the scale parameter corresponding to the tracking gate of the target to be tracked is determined according to the tracking time window of the target to be tracked.

[0048] According to the association relationship, the measurement point at the current moment falling in the tracking gate of the target to be tracked is determined, and the tracking time window of the target to be tracked is determined, including: according to the association relationship, if any measurement point falls in the tracking gate of the target to be tracked, the tracking time window of the tracking gate of the target to be tracked is increased by a preset amount until the tracking time window of the target to be tracked is increased to a preset maximum value; if no measurement point falls in the tracking gate of the target to be tracked, the tracking time window of the tracking gate of the target to be tracked is reduced by a preset amount until the tracking time window is reduced to a preset minimum value.

[0049] Specifically, according to the residual vector norm g i，m (k) calculated in step 103, the measurement points associated with each target to be tracked are determined, and the specific process is as follows:

[0050] Suppose, for the target to be tracked 1, the residual vector norm g 1，m (k) of each measurement point is looped, where m = 1, 2, …, M, and it is judged whether g 1，m (k) ≤ G1(k-t i ), if yes, the measurement point m falls in the predicted wave gate of the target to be tracked 1, and if no, the measurement point m falls outside the predicted wave gate of the target 1.

[0051] Then for the target 2, the residual vector norm g 2，m (k) of each measurement point is looped, and it is judged whether g 2，m (k) ≤ G2(k-t i ), if yes, the measurement point m falls in the predicted wave gate of the target 2, and if no, the measurement point m falls outside the predicted wave gate of the target 2; and so on, until for the target N, the residual vector norm g N，m (k) of each measurement point is looped, and it is judged whether g N，m (k) ≤ G N (k-t i ), if yes, the measurement point m falls in the predicted wave gate of the target N, and if no, the measurement point m falls outside the predicted wave gate of the target N; until the judgment of whether each measurement point is in or outside the tracking gate of the target to be tracked 1 to the target to be tracked N is completed, and the number of measurement points a(i) falling in the tracking gate of each target to be tracked is counted. Wherein, G i (k) represents the tracking gate scale parameter of target i at the kth sampling moment.

[0052] S104, according to the update information, the parameters of the associated tracking gate are updated respectively.

[0053] It should be noted that by updating the time window of the tracking gate for each target to be tracked, the effective time span of the updated information can be determined, thereby ensuring that the tracking of the target is not interrupted when the measurement is suddenly interrupted; and the historical tracking gate parameters are updated according to the current observation data to adapt to the continuous changes of the maneuvering target, making the tracking results more accurate.

[0054] Among them, the tracking gate time window of target i is updated. The process is as follows: First, assume The initial value is 1; if at the current time, any measurement point falls within the tracking gate of target i, then Add 1, the maximum value is L. max If at the current moment no measurement point falls within the predicted gate of target i, then Decrease by 1, with a minimum value of 1; next, based on the judgment results of the tracking gate for each target to be tracked, adjust the scale parameter G of the tracking gate for each target to be tracked. i (k) is updated, and the specific update method is as follows:

[0055]

[0056] Where PD represents the detection probability, which can be set according to actual needs, such as setting it to PD = 0.8; |S i (k)| denotes the residual covariance matrix S i The determinant of (k); Ψ i (k) represents the tracking gate enhancement operator, which is calculated as follows:

[0057]

[0058] Among them, E(d) m ) represents the magnitude of the residual vector of all measurement points falling within the gate of target i |d i，m The mathematical expectation of (k)|, whose probability distribution is determined by the residual vector norm g. i，m (k) is determined, and the specific calculation method is as follows:

[0059]

[0060] E(d i The expression represents the expected value of the residual vector between the same measurement point m and all targets. The specific calculation method is as follows:

[0061]

[0062] D(d m ) represents E(d m The variance corresponding to ). Additionally, β(k) represents the new source density at time k, calculated as follows:

[0063]

[0064] Wherein, b(k) represents the number of measurement points that pass through the target gate detection at the k th moment and do not fall within any target tracking gate.

[0065] S105, tracking the targets based on the updated correlation tracking gates.

[0066] Scale parameter G of the tracking gate of the target to be tracked i (k) After the update, filtering calculation is performed on the state of the target at the k th moment according to the measurement point decision result of the target, for example, a filtering algorithm such as kalman filtering can be used, and finally the tracking result of all maneuvering targets at the k th moment is obtained.

[0067] Through the above analysis, it can be known that the maneuvering target tracking method based on the adaptive gate provided in the embodiments of the present application first acquires the echo information reflected by each target to be tracked; then determines the correlation relationship between the correlation tracking gate of each target to be tracked and each measurement point according to the current echo information acquired at the current moment and the predicted state information of each target to be tracked; then updates the parameters of the correlation tracking gate of each target to be tracked according to the update information of the correlation tracking gate of each target to be tracked respectively according to the correlation relationship; and finally tracks each target to be tracked based on the updated correlation tracking gate. Since the technical solution of the present application is based on the maximum likelihood tracking gate estimation algorithm, the correlation relationship between the correlation tracking gate of each target to be tracked and each measurement point is calculated based on the current echo information acquired at the current moment and the predicted state information of each target to be tracked, and the correlation tracking gate of the maneuvering target is updated according to the correlation relationship, which can adaptively change the target maneuvering range and intensity in the process of tracking multiple maneuvering targets, and aims to improve the accuracy of tracking multiple maneuvering targets.

[0068] Based on the method provided in the above embodiments, the embodiments of the present application further provide a device embodiment for implementing the method embodiments.

[0069] As Figure 3 shown, Figure 3 a schematic diagram of the maneuvering target tracking device based on the adaptive gate provided in the embodiments of the present application. Each module included is used to execute Figure 1 the steps in the corresponding embodiments. For details, please refer to Figure 1 the related description in the corresponding embodiments. For the sake of illustration, only the parts related to the present embodiment are shown. Please refer to Figure 3 , the maneuvering target tracking device based on the adaptive gate 300 comprises:

[0070] The acquisition module 301 is configured to acquire the echo information reflected by each target to be tracked.

[0071] The first determining module 302 is configured to determine, according to current echo information acquired at a current moment and predicted state information of each target to be tracked, an association relationship between an association tracking gate of each target to be tracked and each measurement point.

[0072] The second determining module 303 is configured to determine, according to the association relationship, update information of the association tracking gate of each target to be tracked, respectively.

[0073] The updating module 304 is configured to update parameters of the association tracking gate according to the update information, respectively.

[0074] The tracking module 305 is configured to track each target to be tracked based on the updated association tracking gate.

[0075] In an embodiment, the first determining module 302 comprises:

[0076] The calculating unit is configured to calculate observation state information of each target to be tracked at the current moment according to the current echo information.

[0077] The first determining unit is configured to determine, according to the observation state information and the predicted state information, an association relationship between an association tracking gate of each target to be tracked and each measurement point.

[0078] In an embodiment, the calculating unit is specifically configured to:

[0079] calculate the observation state information of each target to be tracked at the current moment according to the current echo information and historical observation state information of each target to be tracked at a historical moment.

[0080] In an embodiment, the first determining unit comprises:

[0081] The first calculating subunit is configured to calculate, according to the observation state information and the predicted state information, a positional relationship between each target to be tracked and each measurement point, respectively.

[0082] The first determining subunit is configured to determine, according to the positional relationship, an association relationship between an association tracking gate of each target to be tracked and each measurement point.

[0083] In an embodiment, the first calculating subunit is specifically configured to:

[0084] For any target to be tracked, calculate Mahalanobis distances between the target to be tracked and each measurement point according to the observation state information and the predicted state information of the target to be tracked, and take the Mahalanobis distances as the positional relationship between the target to be tracked and each measurement point.

[0085] In one embodiment, the updated information includes a tracking time window and scale parameters; the second determining module 303 includes:

[0086] The second determining unit is used to determine, based on the correlation relationship, the measurement point that falls within the tracking gate of the target at the current time and the tracking time window of the target, for any target to be tracked.

[0087] The third determining subunit is used to determine the scale parameters corresponding to the tracking gate of the target to be tracked based on the tracking time window.

[0088] In one embodiment, the second determining unit includes:

[0089] The second determining subunit is used to determine, based on the correlation, that if any measurement point falls within the tracking gate of the target to be tracked at the current moment, the tracking time window of the tracking gate of the target to be tracked will be increased by a preset amount until the tracking time window is increased to the preset maximum value.

[0090] The third determining subunit is used to determine the tracking time window of the tracking gate of the target to be tracked to decrease by a preset amount if no measurement point falls within the tracking gate of the target to be tracked, until the tracking time window is reduced to a preset minimum value.

[0091] It should be noted that the information interaction and execution process between the above modules are related to this application. Figure 1 The method embodiments shown are based on the same concept. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0092] Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 4 of this embodiment, in addition to including radar or other sensors (wherein, radar or sensors are not shown in the figure), also includes: a processor 400, a memory 401, and a computer program 402 stored in the memory 401 and executable on the processor 400, such as a maneuvering target tracking program based on an adaptive gate. The processor 400 executes the computer program 402 to implement the above-described... Figure 1 The steps in the embodiment of the adaptive gate-based maneuvering target tracking method are shown. Alternatively, the processor 400 may implement the above when executing computer program 402. Figure 3 The functions of each module / unit in the embodiment.

[0093] For example, the computer program 402 can be divided into one or more modules / units, which are stored in the memory 401 and executed by the processor 400 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 402 in the electronic device 4. For example, the computer program 402 can be divided into an acquisition module, a first determination module, a second determination module, an update module, and a tracking module, and the specific functions of each module will be described in detail below. Figure 3 Corresponding to the related description in the embodiments, details are not repeated here.

[0094] The electronic device 4 can include but is not limited to the processor 400 and the memory 401. Those skilled in the art can understand that the electronic device 4 can further include other components, for example, the electronic device 4 can further include an input / output device, a network access device, a bus, etc. Figure 4 The electronic device 4 is only an example and does not constitute a limitation on the electronic device 4, and can include more or fewer components than the illustration, or combine certain components, or different components, for example, the electronic device 4 can also include an input / output device, a network access device, a bus, etc.

[0095] The processor 400 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0096] The memory 401 can be an internal storage unit of the electronic device 4, for example, a hard disk or a memory of the electronic device 4. The memory 401 can also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. Further, the memory 401 can include both the internal storage unit and the external storage device of the electronic device 4. The memory 401 is used to store the computer program 402 and other programs and data supported by the electronic device 4. The memory 401 can also be used to temporarily store data that has been output or will be output.

[0097] The embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, when the computer program product runs on the electronic device, causes the electronic device to execute the above-mentioned Figure 1 The steps of the adaptive gate-based maneuvering target tracking method.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit, and the integrated unit can be realized in the form of hardware or based on adaptive gate-based maneuvering target tracking software functional unit. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0099] The embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, when the computer program product runs on the electronic device, causes the electronic device to execute the above-mentioned Figure 1 The steps of the adaptive gate-based maneuvering target tracking method.

[0100] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit, and the integrated unit can be realized in the form of hardware or based on adaptive gate-based maneuvering target tracking software functional unit. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0101] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in a certain embodiment can be referred to the relevant description of other embodiments.

[0102] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0103] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for tracking maneuvering targets based on adaptive gates, characterized in that, The method includes: Acquire the echo information reflected by each target to be tracked; Based on the current echo information obtained at the current moment and the predicted state information of each target to be tracked, the correlation relationship between the associated tracking gate of each target to be tracked and each measurement point is determined. Based on the aforementioned correlation, the update information of the associated tracking gate for each target to be tracked is determined. Based on the updated information, update the parameters of the associated tracking gates respectively; The targets to be tracked are tracked based on the updated associated tracking gates; The update information includes a tracking time window and scale parameters; the step of determining the update information of the associated tracking gate for each target to be tracked based on the correlation includes: For any target to be tracked, based on the correlation, determine the measurement point that falls within the tracking gate of the target at the current time, and determine the tracking time window of the target; The scale parameter is determined based on the tracking time window; The step of determining the measurement point that falls within the tracking gate of the target to be tracked at the current time based on the correlation relationship, and determining the tracking time window of the target to be tracked, includes: Based on the aforementioned correlation, if any measurement point falls within the tracking gate of the target to be tracked at the current moment, then the tracking time window of the tracking gate of the target to be tracked is increased by a preset amount until the tracking time window increases to a preset maximum value. If no measurement point falls within the tracking gate of the target to be tracked, the tracking time window of the tracking gate of the target to be tracked is reduced by a preset amount until the tracking time window is reduced to a preset minimum value.

2. The method according to claim 1, characterized in that, The step of determining the correlation between the associated tracking gate of each target and each measurement point based on the current echo information acquired at the current time and the predicted state information of each target to be tracked includes: Based on the current echo information, calculate the observation status information of each target to be tracked at the current moment; Based on the observation status information and the prediction status information, the correlation between the associated tracking gate of each target to be tracked and each measurement point is determined.

3. The method according to claim 2, characterized in that, The step of calculating the observation status information of each target to be tracked at the current moment based on the current echo information includes: Based on the current echo information and the historical observation status information of each target to be tracked at a historical time, the observation status information of each target to be tracked at the current time is calculated.

4. The method according to claim 2, characterized in that, The step of determining the correlation relationship between the associated tracking gate of each target to be tracked and each measurement point based on the observation state information and the prediction state information includes: Based on the observation status information and the prediction status information, the positional relationship between each target to be tracked and each measurement point is calculated respectively. Based on the positional relationship, the correlation between the associated tracking gate of each target to be tracked and each measurement point is determined.

5. The method according to claim 4, characterized in that, The step of calculating the positional relationship between each target to be tracked and each measurement point based on the observation state information and the prediction state information includes: For any of the targets to be tracked, the Mahalanobis distance between the target and each measurement point is calculated based on the observed state information and the predicted state information of the target, and the Mahalanobis distance is used as the positional relationship between the target and each measurement point.

6. A maneuvering target tracking device based on an adaptive gate, characterized in that, The device includes: The acquisition module is used to acquire the echo information reflected by each target to be tracked; The first determining module is used to determine the association relationship between the associated tracking gate of each target and each measurement point based on the current echo information obtained at the current time and the predicted state information of each target to be tracked. The second determining module is used to determine the update information of the associated tracking gate of each target to be tracked according to the association relationship; An update module is used to update the parameters of the associated tracking gates according to the update information. The tracking module is used to track each target to be tracked based on the updated associated tracking gates; The updated information includes the tracking time window and scale parameters; the second determining module includes: The second determining unit is used to determine, based on the correlation relationship, the measurement point that falls within the tracking gate of the target at the current time and the tracking time window of the target, for any target to be tracked. The third determining subunit is used to determine the scale parameters corresponding to the tracking gate of the target to be tracked based on the tracking time window; The second determining unit includes: The second determining subunit is used to determine, based on the correlation, that if any measurement point falls within the tracking gate of the target to be tracked at the current moment, the tracking time window of the tracking gate of the target to be tracked will be increased by a preset amount until the tracking time window is increased to the preset maximum value. The third determining subunit is used to determine the tracking time window of the tracking gate of the target to be tracked to decrease by a preset amount if no measurement point falls within the tracking gate of the target to be tracked, until the tracking time window is reduced to a preset minimum value.

7. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the steps of the adaptive gate-based maneuvering target tracking method as described in any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium storing a computer program product, characterized in that, When the computer program product is run on an electronic device, it causes the electronic device to perform the steps of the adaptive gate-based maneuvering target tracking method as described in any one of claims 1 to 5.

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