Self-adaptive radar target tracking parameter determination method and device and electronic equipment

Abstract

The invention provides a self-adaptive radar target tracking parameter determination method and device and electronic equipment, and can be applied to the technical field of radar tracking. The method comprises the steps that historical track points participating in target tracking parameter calculation in multiple modes and historical parameter information of each historical track point are acquired according to preset windows, and the sizes of the preset windows corresponding to different modes are different; first information corresponding to the multiple modes is calculated based on the historical parameter information corresponding to the multiple modes; selecting an optimal mode suitable for target tracking parameter determination at the current moment from a plurality of modes according to the plurality of pieces of first information; determining a target mode for a current target tracking parameter according to the optimal mode information corresponding to the n historical track points; wherein n is a positive integer; and determining a target tracking parameter according to the first information of the target mode.

Description

Technical Field

[0001] The present invention relates to the field of radar tracking technology, and more particularly to an adaptive radar target tracking parameter determination method, device and electronic equipment. Background Art

[0002] Radar target tracking and processing technology mainly consists of target detection technology and target prediction technology.

[0003] Target prediction technology mainly uses the successfully matched target and the target's historical trajectory information to predict the target's state at the next moment. Its core lies in using the target parameters (speed, heading, position) at the current moment and historical moments to predict and update the parameters (speed, heading, position) of the target in the next frame.

[0004] The core of target prediction processing technology lies in the target prediction algorithm, which optimally estimates the target's state based on current and historical target parameters. Traditional least squares target processing technology primarily uses historical points associated with the target to predict the target's state (position, speed, and heading) at the next moment. Because least squares is a linear filtering method, it can stably predict the state of linear motion (straight lines, acceleration), but it produces large errors for nonlinear motion (turns, S-curves), resulting in unstable target tracking and loss. Summary of the Invention

[0005] (1) Technical issues to be resolved The present invention provides an adaptive radar target tracking parameter determination method, device, namely electronic equipment and medium, for at least partially solving one of the above-mentioned technical problems.

[0006] (2) Technical solution According to a first aspect of the present invention, an adaptive radar target tracking parameter determination method is provided, comprising: obtaining historical trajectory points participating in target tracking parameter calculation in multiple modes and historical parameter information of each historical trajectory point according to a preset window, wherein the preset window sizes corresponding to different modes are different; calculating first information corresponding to the multiple modes based on the historical parameter information corresponding to each of the multiple modes; selecting an optimal mode suitable for determining the target tracking parameters at the current moment from the multiple modes according to the multiple first information; determining a target mode for the current target tracking parameters according to the optimal mode information corresponding to n historical trajectory points; wherein n is a positive integer; and determining the target tracking parameters according to the first information of the target mode.

[0007] According to an embodiment of the present invention, the multiple modes include stable mode, standard mode, and maneuvering mode. The sizes of the preset windows are arranged from large to small as stable mode, standard mode, and maneuvering mode. The size of the preset window is positively correlated with the number of historical trajectory points, and the historical parameter information includes at least the historical trajectory time and the historical trajectory position.

[0008] According to an embodiment of the present invention, first information corresponding to multiple modes is determined based on historical parameter information corresponding to each of the multiple modes, including: performing the following operations for each mode: determining the historical trajectory average position and historical trajectory average time corresponding to the mode based on the historical trajectory position and historical trajectory time respectively; determining the slope information and intercept information of the target in the X and Y directions under the mode based on the historical trajectory position, the historical trajectory average position, the historical trajectory time, and the historical trajectory average time respectively, to obtain the first information corresponding to the mode; wherein the slope is used to represent the movement trend of the target, and the intercept is used to represent the position of the target at a certain moment.

[0009] According to an embodiment of the present invention, the first information of each of the plurality of patterns is determined based on a least squares method.

[0010] According to an embodiment of the present invention, an optimal mode suitable for determining target tracking parameters at the current moment is determined from multiple modes based on multiple first information, including: calculating standard deviation information of each of the multiple modes based on the first information of each of the multiple modes, wherein the standard deviation information is used to reflect the degree of deviation between the target tracking parameters predicted by the mode and the actual trajectory point position; normalizing the standard deviation information of each of the multiple modes and selecting the optimal mode suitable for determining target tracking parameters at the current moment from the multiple modes based on the normalized standard deviation information.

[0011] According to an embodiment of the present invention, the best mode suitable for determining the target tracking parameters at the current moment is selected from multiple modes based on the normalized standard deviation information, including: sorting the normalized standard deviation information; and according to the sorting result, determining the mode corresponding to the minimum standard deviation information after normalization as the best mode.

[0012] According to an embodiment of the present invention, the method further includes: recording the best mode into a mode array, wherein the mode array is used to store the best mode corresponding to each historical trajectory.

[0013] According to an embodiment of the present invention, a target mode for current target tracking parameters is determined based on optimal mode information corresponding to n historical trajectory points, including: traversing a mode array, counting the frequency of occurrence of each mode in the n historical trajectory points; and determining the mode with the highest frequency as the target mode.

[0014] According to a second aspect of the present invention, an adaptive radar target tracking parameter determination device is provided, comprising: an acquisition module for respectively acquiring historical parameter information corresponding to historical trajectory points participating in target tracking parameter calculation in multiple modes according to a preset window, wherein the preset window sizes corresponding to different modes are different; a calculation module for respectively calculating first information corresponding to multiple modes based on the historical parameter information corresponding to each of the multiple modes; a selection module for selecting an optimal mode suitable for determining target tracking parameters at the current moment from multiple modes according to the multiple first information; a first determination module for determining a target mode for current target tracking parameters according to the optimal mode information corresponding to n historical trajectory points, wherein n is a positive integer; and a second determination module for determining the target tracking parameters according to the first information of the target mode.

[0015] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0016] (3) Beneficial effects The adaptive radar target tracking parameter determination method, device, and electronic device provided by the present invention have at least the following beneficial effects: The optimal predicted target tracking parameter method using three modes of target tracking prediction and calculation of the standard deviation of the predicted target parameters and the actual trajectory points can achieve the adaptability of target tracking parameters and improve the accuracy of target (stable target, standard target, high-speed maneuvering target) tracking parameters; the method of calculating the probability of the optimal predicted target tracking parameters multiple times can improve the stability of target tracking parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which: Figure 1 A flowchart of a method for determining adaptive radar target tracking parameters according to an embodiment of the present invention is schematically shown; Figure 2 A schematic diagram illustrating a principle diagram of an adaptive radar target tracking parameter determination method according to an embodiment of the present invention is shown; Figure 3 A flowchart schematically illustrates determining first information corresponding to multiple modes based on historical parameter information corresponding to each of the multiple modes according to an embodiment of the present invention; Figure 4 A flowchart of determining an optimal mode for determining target tracking parameters at a current moment from multiple modes according to multiple first information is schematically shown according to an embodiment of the present invention; Figure 5 Schematically shows a structural block diagram of an adaptive radar target tracking parameter determination device according to an embodiment of the present invention; Figure 6 A block diagram of an electronic device according to an adaptive radar target tracking parameter determination method according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings. It is apparent that the embodiments described are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0019] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the presence of the features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components.

[0020] In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connect," "fixed," etc. should be understood in a broad sense. For example, they may refer to fixed connection, detachable connection, or integration; mechanical connection, electrical connection, or mutual communication; direct connection or indirect connection through an intermediate medium; internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0021] In the description of the present invention, it should be understood that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the subsystem or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0022] Throughout the drawings, identical elements are represented by identical or similar reference numerals. Conventional structures or configurations may be omitted where they may obscure the understanding of the present invention. Furthermore, the shapes, sizes, and positional relationships of the components in the drawings do not reflect actual size, proportion, or actual positional relationships. Furthermore, any reference symbols placed between parentheses should not be construed as limiting.

[0023] Similarly, in order to streamline the present invention and aid in understanding one or more of the various disclosed aspects, in the above description of exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. Descriptions with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" and the like mean that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0024] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features being referred to. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means at least two, such as two or three, unless otherwise specifically defined.

[0025] An embodiment of the present invention provides an adaptive radar target tracking parameter determination method, including: obtaining historical parameter information corresponding to historical trajectory points participating in target tracking parameter calculation in multiple modes according to preset windows, wherein the preset window sizes corresponding to different modes are different; calculating first information corresponding to the multiple modes based on the historical parameter information corresponding to each of the multiple modes; selecting an optimal mode suitable for determining the target tracking parameters at the current moment from the multiple modes according to the multiple first information; determining a target mode for the current target tracking parameters according to the optimal mode information corresponding to n historical trajectory points; and determining the target tracking parameters according to the first information of the target mode.

[0026] Figure 1 The flowchart of the adaptive radar target tracking parameter determination method according to an embodiment of the present invention is schematically shown. Figure 2 The following schematically shows a principle diagram of an adaptive radar target tracking parameter determination method according to an embodiment of the present invention.

[0027] like Figure 1 、 Figure 2 As shown, the adaptive radar target tracking parameter determination method of this embodiment includes operations S110 to S150.

[0028] In operation S110, historical parameter information corresponding to historical trajectory points involved in target tracking parameter calculation in multiple modes is respectively obtained according to preset windows, wherein the preset window sizes corresponding to different modes are different.

[0029] In some embodiments, the modes include stable mode, standard mode, and maneuvering mode. The sizes of the preset windows are arranged from large to small as stable mode, standard mode, and maneuvering mode. The size of the preset window is positively correlated with the number of historical trajectory points. That is, the larger the size of the preset window, the greater the number of historical trajectory points involved in parameter calculation in that mode. Historical parameter information includes at least historical trajectory time and historical trajectory position. The window size can be set based on historical experience and actual conditions. The preset window size is used to limit the number of historical trajectory points involved in parameter calculation in the current mode.

[0030] For example, the preset window size L for stable mode is 45, which means that the number of historical trajectory points involved in parameter calculation in stable mode is 45 points. The preset window size M for standard mode is 15, which means that the number of historical trajectory points involved in parameter calculation in standard mode is 15 points. The preset window size S for maneuvering mode is 5, which means that the number of historical trajectory points involved in parameter calculation in maneuvering mode is 5 points. The historical trajectory points corresponding to each mode and the historical parameter information of each historical trajectory point can be obtained in order from the nearest to the furthest timestamp.

[0031] In operation S120 , first information corresponding to the plurality of modes is calculated based on the historical parameter information corresponding to each of the plurality of modes.

[0032] In some embodiments, for each mode, the corresponding historical trajectory points and the historical parameter information of each historical trajectory point are extracted according to the preset window size. For example, the stable mode extracts the most recent 45 historical trajectory points, and the maneuvering mode extracts the most recent 5 historical trajectory points. In some embodiments, for each mode, the first information in the mode is predicted based on the least square method. The first information may include the slope of the uniform speed straight line model in the X and Y directions. and intercept .

[0033] In operation S130 , an optimal mode suitable for determining target tracking parameters at the current moment is selected from a plurality of modes according to the plurality of first information.

[0034] In some embodiments, the standard deviation between the predicted first information and the actual trajectory point position in each mode is calculated based on the first information predicted in each mode. The optimal mode for determining target tracking parameters at the current moment is determined based on the standard deviation information. The standard deviation information can reflect the degree of deviation between the predicted first information and the actual trajectory point position in the current mode. A smaller standard deviation value indicates a lower deviation between the predicted first information and the actual trajectory point position in the current mode.

[0035] The mode with the smallest standard deviation information is selected as the optimal mode at the current moment. For example, if the standard deviation information of the stable mode is the smallest, the stable mode is selected as the optimal mode at the current moment.

[0036] By selecting the pattern that best matches the actual trajectory point based on the standard deviation information at the current moment, the instantaneous motion changes of the target can be captured in real time, so as to dynamically adjust the model according to real-time data and thus improve the prediction accuracy.

[0037] In operation S140 , a target mode for current target tracking parameters is determined based on the optimal mode information corresponding to the n historical trajectory points.

[0038] In some embodiments, the number of occurrences of the stable mode, the standard mode, and the maneuvering mode at n moments is counted and their frequencies are calculated. For example, if n=10, and the mode with the highest frequency of occurrence in the most recent 10 moments is the stable mode, the stable mode is selected as the target mode.

[0039] In operation S150, an object tracking parameter is determined according to the first information of the object pattern.

[0040] In some embodiments, first information of the target pattern (such as the slope and intercept of the linear fit) is acquired, and current target tracking parameters (X, Y) are determined based on the first information of the target pattern.

[0041] Taking the target mode as stable mode as an example, the first parameter of the stable mode includes the slopes in the X and Y directions. and intercept , then the current target tracking parameters (X, Y) are:

[0042] Where T is the radar scanning period.

[0043] The adaptive radar target tracking parameter determination method provided by an embodiment of the present invention uses three modes (stable mode, standard mode, and maneuvering mode) for least squares prediction of target tracking parameters. Standard deviations are calculated between the predicted values ​​of the three modes and actual trajectory point data to determine the current optimal mode. Furthermore, the target mode is determined by probabilistically calculating the optimal predicted target tracking parameters n times. The current optimal output target tracking parameters are then determined based on first information about the target mode, effectively improving the accuracy and stability of the target tracking parameters. The current optimal mode is selected based on instantaneous prediction error, enabling rapid response to changes in the target's motion state. The target mode is selected based on historical frequency statistics, providing long-term stable predictions. By determining the optimal and target modes, a balance between real-time performance and stability is achieved, effectively improving the accuracy and stability of the target tracking parameters.

[0044] Figure 3The flowchart of determining first information corresponding to multiple modes based on historical parameter information corresponding to each of the multiple modes according to an embodiment of the present invention is schematically shown.

[0045] like Figure 3 As shown, this embodiment determines first information corresponding to multiple modes based on historical parameter information corresponding to each of the multiple modes, including operations S310 to S320. Operations S310 to S320 are performed for each mode.

[0046] In operation S310 , a historical trajectory average position and a historical trajectory average time corresponding to a mode are determined based on the historical trajectory positions and the historical trajectory time, respectively.

[0047] In some embodiments, the historical track positions of multiple historical track points corresponding to the mode are and historical trajectory time , calculate the average position of the historical trajectory corresponding to the mode and the average time of historical trajectories .

[0048] In operation S320 , the slope information and intercept information of the target in the X and Y directions in the current mode are determined based on the historical trajectory position, the historical trajectory average position, the historical trajectory time, and the historical trajectory average time, respectively, to obtain first information corresponding to the mode.

[0049] In some embodiments, the slope information in the X and Y directions of this mode is predicted based on the least squares method. And the intercept information in the X and Y directions , get the first information corresponding to the mode. Among them, the slope information b in the X direction x It is the velocity component of the target in the x direction, which can reflect the target's movement trend (speed or direction); the slope information b in the y direction y It is the velocity component of the target in the y direction, which can reflect the motion trend (speed or direction) of the target; the intercept a in the x direction x It can reflect the position of the target in the x direction and the intercept a in the y direction y It can reflect the position of the target in the y direction. The slope and intercept can fully describe the target's motion state (position, speed, direction).

[0050] For example, for the stable mode L, the first information Lb x , Lb y , La x , La y The calculation formula is as follows:

[0051] For the standard mode M, the first information Mb x 、Mb y 、Ma x 、Ma y The calculation formula is as follows:

[0052] For the maneuvering mode S, the first information Sb x 、Sb y 、Sa x 、Sa y The calculation formula is as follows:

[0053] Figure 4 The flowchart of determining the best mode for determining target tracking parameters at the current moment from multiple modes according to multiple first information according to an embodiment of the present invention is schematically shown.

[0054] like Figure 4 As shown, this embodiment determines the best mode for determining target tracking parameters at the current moment from multiple modes according to multiple first information, including operations S410 to S420.

[0055] In operation S410 , standard deviation information of each of the multiple modes is calculated based on the first information of each of the multiple modes, wherein the standard deviation information is used to reflect the degree of deviation between the target tracking parameters predicted by the mode and the actual trajectory point position.

[0056] In some embodiments, the standard deviation information of each mode is calculated based on the first information of each mode.

[0057] Exemplarily, the calculation formula of the standard deviation information Ldev of the stable mode L is:

[0058] The calculation formula of the standard deviation information Mdev of the standard mode M is:

[0059] The calculation formula of the standard deviation information Sdev of the maneuvering mode S is:

[0060] In operation S420, the standard deviation information of each of the multiple modes is normalized, and the best mode suitable for determining the target tracking parameters at the current moment is selected from the multiple modes according to the normalized standard deviation information.

[0061] In some embodiments, since the window sizes of different modes are different, the numerical ranges of the standard deviations will be different. Therefore, the standard deviation information of multiple modes needs to be normalized so that the standard deviations of different modes can reflect the prediction errors under the unit window length, making the standard deviation information between different modes comparable.

[0062] For example, the standard deviation information of each mode may be multiplied by a normalization factor (such as a window size ratio) to obtain comparable normalized standard deviation information.

[0063] For example, the standard deviation information of the normalized stable mode The expression is:

[0064] Standard deviation information of the normalized standard mode The expression is:

[0065] Normalized standard deviation information of maneuvering mode The expression is:

[0066] In some embodiments, the standard deviation information obtained after normalization is sorted, and the sorting results are sorted, and the mode corresponding to the minimum standard deviation information after normalization is determined as the best mode. , it is determined that the first information in the stable mode is closest to the actual value, and the stable mode is determined as the optimal mode.

[0067] In some embodiments, the optimal mode is recorded in a mode array for storing the optimal modes corresponding to n consecutive historical trajectories. By recording the optimal modes corresponding to multiple consecutive trajectory points, the trend of changes in the motion state of the target over a period of time can be analyzed, and the mode with the highest frequency of occurrence can be finally selected as the current optimal mode.

[0068] In some embodiments, a target mode for current target tracking parameters is determined based on optimal mode information corresponding to n historical trajectory points, including: traversing a mode array, counting the frequency of occurrence of each mode in the n historical trajectory points; and determining the mode with the highest frequency as the target mode.

[0069] For example, taking n=10 as an example, the best pattern corresponding to the 10 consecutive historical trajectory points closest to the current moment is read from the pattern array, and the frequency of each pattern appearing in these 10 historical trajectory points is counted (f L 、f M 、f S), sort the frequencies corresponding to each mode, and determine the mode corresponding to the maximum frequency f as the target mode.

[0070] For example, among the current n trajectory points, f L >f M >f S , the stable mode is determined as the target mode, and the target tracking parameters are determined based on the first information of the stable mode.

[0071] The standard deviation at a single moment may be affected by noise or loss disturbances and cannot fully reflect the long-term motion trend of the target. The embodiment of the present invention analyzes the main motion state of the target over a period of time by calculating the frequency of different patterns at historical trajectory points. The pattern with the highest frequency indicates the motion state that the target is most often in during the current time period.

[0072] This embodiment of the present invention records the mode with the smallest standard deviation (i.e., the optimal mode) and selects the mode closest to the actual motion in real time, providing a basis for subsequent trajectory prediction. It also calculates the frequency of different modes in historical trajectory points and analyzes the target's long-term motion trends to select the most stable motion mode. By combining short-term and long-term information about the target's motion, it more accurately describes the target's motion state, improving the robustness and accuracy of the prediction. Based on the above-mentioned adaptive radar target tracking parameter determination method, the present invention also provides an adaptive radar target tracking parameter determination device. Figure 5 The device is described in detail.

[0073] Figure 5 The following schematically shows a structural block diagram of an adaptive radar target tracking parameter determination device according to an embodiment of the present invention.

[0074] like Figure 5 As shown, the adaptive radar target tracking parameter determination device 500 of this embodiment includes an acquisition module 510 , a calculation module 520 , a selection module 530 , a first determination module 540 and a second determination module 550 .

[0075] Acquisition module 510 is used to obtain historical parameter information corresponding to historical trajectory points involved in target tracking parameter calculation in multiple modes according to preset windows, where the preset window sizes corresponding to different modes are different. In one embodiment, acquisition module 510 can be used to perform operation S110 described above, and will not be repeated here.

[0076] The calculation module 520 is used to calculate the first information corresponding to the multiple modes based on the historical parameter information corresponding to the multiple modes. In one embodiment, the calculation module 520 can be used to perform the operation S120 described above, which will not be repeated here.

[0077] The selection module 530 is used to select the best mode suitable for determining the target tracking parameters at the current moment from multiple modes according to the multiple first information. In one embodiment, the selection module 530 can be used to perform the operation S130 described above, which will not be repeated here.

[0078] The first determination module 540 is configured to determine a target mode for the current target tracking parameters based on the optimal mode information corresponding to n historical trajectory points; wherein n is a positive integer. In one embodiment, the first determination module 540 can be configured to perform the operation S140 described above, which will not be further described here.

[0079] The second determining module 550 is configured to determine the target tracking parameter according to the first information of the target mode. In one embodiment, the second determining module 550 may be configured to perform the operation S150 described above, which will not be described in detail herein.

[0080] According to embodiments of the present invention, any multiple of the acquisition module 510, calculation module 520, selection module 530, first determination module 540, and second determination module 550 may be combined into a single module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in a single module. According to embodiments of the present invention, at least one of the acquisition module 510, calculation module 520, selection module 530, first determination module 540, and second determination module 550 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented in hardware or firmware through any other reasonable means of circuit integration or packaging, or implemented in any one of software, hardware, and firmware, or any appropriate combination of these. Alternatively, at least one of the acquisition module 510 , the calculation module 520 , the selection module 530 , the first determination module 540 , and the second determination module 550 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0081] Figure 6 A block diagram of an electronic device according to an adaptive radar target tracking parameter determination method according to an embodiment of the present invention is schematically shown.

[0082] like Figure 6As shown, an electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 602 or programs loaded from a storage unit 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or related chipsets and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0083] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 executes the programs in ROM 602 and / or RAM 603 to perform various operations according to the method flow of the embodiment of the present invention. It should be noted that the programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also execute the programs stored in one or more memories to perform various operations according to the method flow of the embodiment of the present invention.

[0084] According to an embodiment of the present invention, electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to bus 604. Electronic device 600 may also include one or more of the following components connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or modem. Communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. Removable media 611, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 610 as needed, so that computer programs read from the removable media can be installed into storage section 608 as needed.

[0085] The above describes embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although each embodiment has been described separately, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Those skilled in the art may make various substitutions and modifications without departing from the scope of the present invention, and such substitutions and modifications are intended to be included within the scope of protection of the present invention.

Claims

1. An adaptive radar target tracking parameter determination method, characterized in that: include: According to the preset window, historical trajectory points involved in target tracking parameter calculation in multiple modes and historical parameter information of each historical trajectory point are obtained respectively, wherein the preset window size corresponding to different modes is different; Calculating first information corresponding to the multiple modes based on the historical parameter information corresponding to each of the multiple modes; Selecting an optimal mode suitable for determining target tracking parameters at a current moment from the multiple modes according to the multiple first information; Determine a target mode for current target tracking parameters based on optimal mode information corresponding to n historical trajectory points; wherein n is a positive integer; The target tracking parameter is determined according to the first information of the target mode.

2. The radar target tracking parameter determination method according to claim 1, wherein: The multiple modes include stable mode, standard mode, and maneuvering mode. The sizes of the preset windows are arranged from large to small as stable mode, standard mode, and maneuvering mode. The size of the preset window is positively correlated with the number of historical trajectory points. The historical parameter information includes at least historical trajectory time and historical trajectory position.

3. The radar target tracking parameter determination method according to claim 1, wherein: The determining the first information corresponding to the multiple modes based on the historical parameter information corresponding to each of the multiple modes includes: For each mode, do the following: Determining an average historical trajectory position and an average historical trajectory time corresponding to the mode based on the historical trajectory position and the historical trajectory time respectively; Determine the slope information and intercept information of the target in the X and Y directions in this mode based on the historical trajectory position, the historical trajectory average position, the historical trajectory time, and the historical trajectory average time, respectively, to obtain first information corresponding to the mode; The slope is used to represent the movement trend of the target, and the intercept is used to represent the position of the target at a certain moment. 4 . The radar target tracking parameter determination method according to claim 3 , wherein the first information of each of the multiple modes is determined based on a least squares method.

5. The radar target tracking parameter determination method according to claim 1, characterized in that: The determining, from the multiple modes according to the multiple first information, the best mode applicable to determining the target tracking parameters at the current moment comprises: Calculating standard deviation information of each of the multiple modes based on the first information of each of the multiple modes, wherein the standard deviation information is used to reflect the degree of deviation between the target tracking parameter predicted by the mode and the actual trajectory point position; Normalization processing is performed on the standard deviation information of each of the multiple modes, and an optimal mode suitable for determining the target tracking parameters at the current moment is selected from the multiple modes based on the normalized standard deviation information.

6. The radar target tracking parameter determination method according to claim 5, characterized in that: Selecting an optimal mode suitable for determining target tracking parameters at the current moment from the multiple modes according to the normalized standard deviation information, including: sorting the normalized standard deviation information; According to the sorting result, the mode corresponding to the minimum standard deviation information after the normalization process is determined as the optimal mode.

7. The radar target tracking parameter determination method according to claim 5, characterized in that: Also includes: The optimal mode is recorded in a mode array, wherein the mode array is used to store the optimal mode corresponding to each historical trajectory.

8. The radar target tracking parameter determination method according to claim 1 or 7, characterized in that: The determining of the target mode for the current target tracking parameters according to the optimal mode information corresponding to the n historical trajectory points includes: Traversing the pattern array, counting the frequency of each pattern in n historical trajectory points; The pattern with the highest frequency is determined as the target pattern.

9. An adaptive radar target tracking parameter determination device, characterized in that: The device comprises: An acquisition module is used to obtain historical parameter information corresponding to historical trajectory points involved in target tracking parameter calculation in multiple modes according to preset windows, wherein the preset window sizes corresponding to different modes are different; a calculation module, configured to calculate first information corresponding to the plurality of modes based on historical parameter information corresponding to each of the plurality of modes; A selection module, configured to select an optimal mode suitable for determining target tracking parameters at a current moment from the multiple modes according to the multiple first information; A first determination module is configured to determine a target mode for current target tracking parameters based on optimal mode information corresponding to n historical trajectory points; wherein n is a positive integer; The second determining module is configured to determine the target tracking parameter according to the first information of the target mode.

10. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

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