A pure angle target tracking method and system

Abstract

The present invention discloses a pure angle target tracking method suitable for non-uniformly spaced detection equipment. The method mainly includes the following steps: S1, initializing the target tracking system; S2, initiating the target tracking system's track; S3, calculating the target angular velocity information of the established track; S4, associating and maintaining the track; S5, determining candidate targets and updating the track; and S6, outputting the current track. The present invention can adapt to pure angle tracking under different target angle variations.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-target tracking with information fusion, and in particular to a pure angle target tracking processing method and system for non-uniformly spaced detection equipment. Background Art

[0002] Target tracking involves filtering measurements received by a detection device, estimating the target's current state, and predicting its motion state at the next moment. In real-world scenarios, uncertainty exists in both the target model and the measurement information, necessitating target state estimation. Typically, since targets lack specific trajectories, confidence levels cannot be used to model their behavior, leading to inherent uncertainty in the target modeling process. Target motion is also complex, characterized by randomness and uncertainty. Establishing a precise, moment-by-moment motion model is practically unrealistic. However, filtering methods require a defined motion model. If the target's trajectory does not match the assumed motion model, the tracking error can become significant, even leading to divergence in the filtering results. Furthermore, uncertainty arises when receiving measurement data at the receiver. Because the signal source contains clutter and noise, the measurement data received by the sensor contains not only information related to the target's state but also spurious measurements generated by clutter and noise. Using measurements not generated by the target can affect the subsequent state estimation.

[0003] Pure angle target tracking utilizes the target's active radiation, such as electromagnetic, infrared, and acoustic radiation, to obtain angular information about a moving target using a single measurement station or observation station. This time-varying target angle sequence is then used to estimate the target's motion parameters in real time. Due to the limited measurement information, establishing a target motion model is more challenging. Pure angle tracking has always been a hot topic and a challenge in research. However, its widespread application, such as target tracking using infrared sensors and passive sonar sensors, has attracted a large number of researchers to conduct research on pure angle tracking.

[0004] Pure angle target tracking obtains target angle information through passive observation equipment. This passive tracking method is limited by the fact that the sensor cannot obtain target distance information. Its measurement is pure angle in polar coordinates, which often needs to be converted to rectangular coordinates. On the one hand, it suffers from nonlinearity and poor observability. On the other hand, converting the measurement from polar coordinates to rectangular coordinates will cause measurement error bias, which changes the error distribution and becomes correlated with the measured value. This makes the pure angle target tracking system observable and also makes the multi-target tracking algorithm face problems such as prediction and tracking difficulties, slow convergence speed, and poor filter stability. In view of the nonlinear relationship between the measurement value and the target state in pure angle target tracking, there is currently no complete theoretical prediction and tracking theory. The common methods are local linearization approximation, mainly multi-point extrapolation, αβ filtering, wide Kalman filtering, statistical linearization filtering, and iterative filtering. However, these methods also introduce a large number of error terms while performing linearization, thus failing to obtain the optimal prediction and estimation of target information. Summary of the Invention

[0005] The main purpose of the present invention is to propose a pure angle target tracking method suitable for optimal prediction and estimation of target information of a pure angle target tracking system of non-uniformly spaced detection equipment.

[0006] The technical solution adopted in the present invention is:

[0007] A method for tracking an angle-only target is provided, comprising the following steps:

[0008] S1. Target tracking system initialization: The target tracking system sets the target angular velocity demarcation threshold using a non-equally spaced target angle prediction method or a multi-point extrapolation algorithm according to the target angular velocity and its error characteristics, and sets the relevant tracking association threshold of the target tracking system according to conventional tracking gate rules;

[0009] S2, target tracking system track initiation: The target tracking system obtains target measurement information for three consecutive detection moments and completes track initiation;

[0010] S3. Calculation of target angular velocity information for established track: The target tracking system obtains target measurement information at multiple detection moments and calculates the target angular velocity information using angle changes and time changes;

[0011] S4. Tracking association and continued maintenance: The target tracking system uses the target measurement information and calculates the current target angular velocity information, and compares it with the target angular velocity demarcation threshold value set in step S1. If the current target angular velocity is greater than the target angular velocity demarcation threshold value set in step S1, the non-uniformly spaced target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point.

[0012] S5. Candidate target determination and track update: The target tracking system continues to obtain multiple target angle measurement information and compares it with the target predicted angle value in step S4. Targets within the tracking threshold range are selected as candidate measurements. The candidate measurement information is compared with the target predicted point in step S4. The candidate measurement closest to the target predicted point is selected as the final updated measurement of the target, and the target track data is updated.

[0013] S6. Current track output: The target tracking system manages the track after measurement and update by editing, canceling, etc., and finally obtains the target's current track and outputs it, and enters step S4 for the next track update and output.

[0014] Following the above technical solution, the non-uniformly spaced target angle prediction method in step S1 refers to using the formula

[0015]

[0016] Calculate the target angle prediction, where β1, β2, and β3 are the known observed target azimuths, β4 is the target predicted azimuth, and T 12 、T 23 、T 24 、T 13 、T 14 The time interval corresponding to the corresponding movement distance when the target moves in a uniform straight line.

[0017] Following the above technical solution, setting the target angular velocity demarcation threshold value in step S1 refers to setting the target angular velocity demarcation threshold value to 3 to 4 times the angular velocity error.

[0018] Following the above technical solution, setting the relevant tracking threshold of the target tracking system according to the conventional tracking gate rule in step S1 refers to generating the angle tracking threshold using the elliptical tracking rule.

[0019] Following the above technical solution, the target tracking system in step S2 obtains target measurement information by obtaining the target's azimuth and pitch angle measurement information through a pure angle detection device, and performs system error alignment, outlier elimination, and spatial alignment processing to form the target measurement information.

[0020] Following the above technical solution, the logic method in step S3 is to first assume the starting track of the target within the target initial speed range and then confirm it through the third point.

[0021] Following the above technical solution, the calculation of the target predicted angle value using the non-equally spaced target angle prediction method in step S4 refers to directly calculating the angle value at the current moment using formula (1) according to the corresponding moment of the current target measurement information and the first three detection moments of the track.

[0022] Following the above technical solution, calculating the target predicted angle value using the multi-point extrapolation algorithm in step S4 means directly using the target measurement information at the previous detection moment and the target angular velocity prediction obtained in step S3 to calculate the target angle as the angle prediction value at the current moment.

[0023] The present invention also provides a pure angle target tracking system, comprising:

[0024] An initialization module is used to set the target angular velocity demarcation threshold using a non-equally spaced target angle prediction method or a multi-point extrapolation algorithm according to the target angular velocity and its error characteristics, and to set the relevant tracking association threshold of the target tracking system according to conventional tracking gate rules;

[0025] The track initiation module is used to obtain target measurement information at three consecutive detection moments and complete the track initiation;

[0026] The target angular velocity information calculation module is used to obtain target measurement information at multiple detection moments and calculate the target angular velocity information using angle changes and time changes;

[0027] The tracking association and continuation maintenance module is used to use the current target measurement information and calculate the current target angular velocity information, and compare it with the set target angular velocity demarcation threshold value. If the current target angular velocity is greater than the set target angular velocity demarcation threshold value, the non-uniform interval target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point.

[0028] The candidate target judgment and track update module is used to continue to obtain multiple target angle measurement information and compare it with the target predicted angle value, track the targets within the threshold range as candidate measurements, and use the candidate measurement information to compare with the target predicted point. The candidate measurement closest to the target predicted point is used as the final updated measurement of the target, and the target track data is updated;

[0029] The current track output module is used to manage the track after measurement and update, such as editing and canceling, and finally obtain the target's current track and output it. At the same time, the next track update and output are performed through the tracking association and continuation maintenance module.

[0030] The present invention also provides a computer storage medium, which stores a computer program that can be executed by a processor, and the computer program executes the pure angle target tracking method described in the above technical solution.

[0031] The present invention provides the following beneficial effects: The present invention utilizes a target tracking system to set a target angular velocity threshold based on the target angular velocity, and employs either a non-uniformly spaced target angle prediction method or a multi-point extrapolation algorithm for pure angle target tracking prediction. This method effectively addresses the problem of large prediction errors and tracking difficulties caused by the nonlinear characteristics of target motion in conventional angle prediction algorithms when the target angle changes significantly. Furthermore, when the target angle changes slightly and the error is significant compared to the angle change, the multi-point extrapolation algorithm is combined with target angle prediction to achieve pure angle tracking suitable for varying target angle changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 is a flow chart of a method for tracking an angle-only target according to an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of a conventional target tracking system of the present invention;

[0035] Figure 3 Schematic diagram of non-uniformly spaced detection of target linear motion according to an embodiment of the present invention;

[0036] Figure 4 2. Schematic diagram of the two-dimensional plane geometric relationship of the cotangent relation theorem according to an embodiment of the present invention;

[0037] Figure 5 Schematic diagram of the logic tracking initiation strategy according to an embodiment of the present invention; (a) is a schematic diagram showing measurement points a and b at the first two detection moments as candidate tracks; (b) is a schematic diagram showing the track initiation completed by measurement points at three detection moments;

[0038] Figure 6 Schematic diagram of a track tracking and maintaining strategy according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0040] The present invention provides a pure angle target tracking method, such as Figure 1 As shown, the following steps are included:

[0041] S1. Target tracking system initialization: The target tracking system sets the target angular velocity demarcation threshold using a non-equally spaced target angle prediction method or a multi-point extrapolation algorithm according to the target angular velocity and its error characteristics, and sets the relevant tracking association threshold of the target tracking system according to conventional tracking gate rules;

[0042] S2, target tracking system track initiation: The target tracking system obtains target measurement information for three consecutive detection moments and completes track initiation;

[0043] S3. Calculation of target angular velocity information for established track: The target tracking system obtains target measurement information at multiple detection moments and calculates the target angular velocity information using angle changes and time changes;

[0044] S4. Tracking association and continued maintenance: The target tracking system uses the current target measurement information and calculates the current target angular velocity information, and compares it with the target angular velocity demarcation threshold value set in step S1. If the current target angular velocity is greater than the target angular velocity demarcation threshold value set in step S1, the non-equally spaced target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point.

[0045] S5. Candidate target determination and track update: The target tracking system continues to obtain multiple target angle measurement information and compares it with the target predicted angle value in step S4. Targets within the tracking threshold range are selected as candidate measurements. The candidate measurement information is compared with the target predicted point in step S4. The candidate measurement closest to the target predicted point is selected as the final updated measurement of the target, and the target track data is updated.

[0046] S6. Current track output: The target tracking system manages the track after measurement and update by editing, canceling, etc., and finally obtains the target's current track and outputs it, and enters step S4 for the next track update and output.

[0047] like Figure 2 As shown in the figure, the conventional target tracking system mainly consists of data acquisition and preprocessing, data association, tracking filtering, tracking gate rules, tracking maintenance, tracking start and end, etc. The main working steps are as follows:

[0048] (1) Measurement data acquisition and preprocessing: The raw echo data received by the sensor undergoes front-end signal processing. The resulting traces are called measurements. Before the measurements are formally processed, a series of correction preprocessing steps are required. Common preprocessing methods include systematic error registration, outlier removal, and spatial registration.

[0049] (2) Data association and tracking gate rule establishment: Data association uses tracking gates to filter out some false measurements caused by clutter and noise, or target traces generated by other targets. In data association, due to the presence of clutter and multiple targets, multiple traces may appear simultaneously within the same tracking gate, and candidate traces need to be screened using thresholds.

[0050] (3) Tracking filter: Tracking starts and ends to establish and cancel the target track. Tracking filter uses appropriate filtering methods to estimate the state of the detected target, and then generates a complete and correct target track, such as Figure 6 shown.

[0051] (4) Multi-target state estimation: After tracking filtering, a multi-target tracking trajectory, i.e., a track, is formed. After the track is formed, multi-target state estimation and other operations can be realized based on information such as track history data.

[0052] Compared to conventional target tracking systems, the present invention uses a target tracking system to set a target angular velocity threshold based on the target angular velocity, and employs a non-uniformly spaced target angle prediction method or a multi-point extrapolation method to perform pure angle target tracking prediction. This method effectively addresses the problem of large prediction errors and tracking difficulties caused by the nonlinear characteristics of target motion in conventional angle prediction algorithms when the target angle changes significantly. Furthermore, when the target angle changes slightly and the error is significant compared to the angle change, the multi-point extrapolation method is combined with target angle prediction to achieve pure angle tracking suitable for different target angle change conditions.

[0053] Among them, such as Figure 5 As shown in the figure, the track initiation is mainly completed by obtaining the target measurement information of three consecutive detection moments and then using the logic method. The logic method track initiation first satisfies Figure 5 The measurement points a and b at the first two detection moments in the range of (a) are used as candidate tracks. The predicted point c at the third detection moment is obtained through candidate track prediction. If there is a measurement point within the prediction point threshold at the third detection moment, the track start is completed by the measurement points at the three detection moments, as shown in Figure 5 As shown in (b) in .

[0054] As a preferred embodiment, Figure 3 As shown, the non-uniformly spaced target angle prediction method in step S1 refers to using the formula

[0055]

[0056] Calculate the target angle, where β1, β2, and β3 are the known observed target azimuths, β4 is the target predicted azimuth, and T 12 、T 23 、T 24 、T 13 、T14 The time interval corresponding to the corresponding movement distance when the target moves in a uniform straight line.

[0057] Based on the cotangent relationship theorem, the formula for the non-equally spaced target angle prediction method will be derived below.

[0058] like Figure 4 As shown, the cotangent relation theorem is described as the relationship between point P and ABC on the plane as follows Figure 1 The cotangent relation is satisfied:

[0059] l2cotα C -(l1+l2)cotα B +l1α A =0 (2)

[0060] The following is an example of the prediction derivation of the azimuth angle. The derivation of the elevation angle can also be done in the same way. Assume that the relationship between the observation station and the target is as follows: Figure 3 As shown:

[0061] From the known cotangent relation theorem formula (2), we can get the following relation:

[0062]

[0063] Among them, l 13 =l 12 +l 23 ,l 14 =l 12 +l 24 , we can also get the relationship in the figure:

[0064]

[0065] Where β1, β2, β3, and β4 are the observed target azimuths. Substituting the above formula (4) into formula (3) and performing the transformation, we can obtain:

[0066]

[0067] After another series of operations, we can get:

[0068]

[0069] Thus, the following relationship is obtained:

[0070]

[0071] Then we can get the following relationship:

[0072]

[0073] When the target moves in a straight line at a constant speed, the corresponding movement distance is only related to the time interval between each other. Assume that l 12 、l 23 、l 24 、l 13 、l 14 The corresponding time intervals are T 12 、T 23 、T 24 、T 13 、T 14 , we can get formula (1).

[0074] Based on formula (1), when the target is moving in a straight line at a uniform speed and β1, β2, β3 and their corresponding detection intervals are known, the target azimuth angle β4 can be predicted. Using the time information of the first three detection moments and the target angle detected at the corresponding moments, the target angle at the next moment can be predicted in the case of non-uniform intervals, thus providing a new method for target angle prediction in pure angle target tracking systems.

[0075] As a preferred embodiment, the setting of the target angular velocity demarcation threshold value in step S1 refers to setting the target angular velocity demarcation threshold value to 3 to 4 times of the angle error according to the standard error characteristics.

[0076] As a preferred embodiment, setting the target angular velocity demarcation threshold value in step S1 refers to setting the target angular velocity demarcation threshold value to 3 to 4 times the angular velocity error.

[0077] As a preferred embodiment, setting the relevant tracking threshold of the target tracking system according to the conventional tracking gate rule in step S1 refers to generating the angle tracking threshold using the elliptical tracking rule.

[0078] As a preferred embodiment, the target tracking system in step S2 obtains target measurement information by obtaining the target's azimuth and pitch angle measurement information through a pure angle detection device, and performs system error alignment, outlier elimination, and spatial alignment processing to form the target measurement information.

[0079] As a preferred embodiment, the logic method in step S3 is to assume that the target within the target initial speed range starts and then confirms it through the third point.

[0080] As a preferred embodiment, the calculation of the target predicted angle value using the non-equally spaced target angle prediction method in step S4 means that step S4 obtains the current target measurement information corresponding to the time and the aforementioned three detection times of the track and directly calculates the angle value at the current time using formula (1).

[0081] By using the time information of the first three detection moments and the target angle detected at the corresponding moments, the target angle at the next moment can be predicted under non-uniform intervals, thus providing a new means of target angle prediction for pure angle target tracking systems.

[0082] As a preferred embodiment, calculating the target predicted angle value using a multi-point extrapolation algorithm in step S4 means directly using the target measurement information at the previous detection moment and the target angular velocity prediction obtained in step S3 to calculate the target angle as the angle prediction value at the current moment.

[0083] Considering that when the target is far away, the angle change in the non-uniform interval period for pure angle passive detection equipment is small. When the angle change is less than the error fluctuation or is equivalent to the error fluctuation, the cotangent function used in factor (1) will make the prediction value error larger. Therefore, for targets that are far away and have small angle changes, the traditional multi-point extrapolation method can be combined to predict the target angle.

[0084] The angle-only target tracking system of the embodiment of the present invention is mainly used to implement the above method embodiment. The angle-only target tracking system mainly includes the following modules:

[0085] An initialization module is used to set the target angular velocity demarcation threshold using a non-equally spaced target angle prediction method or a multi-point extrapolation algorithm according to the target angular velocity and its error characteristics, and to set the relevant tracking association threshold of the target tracking system according to conventional tracking gate rules;

[0086] The track initiation module is used to obtain target measurement information at three consecutive detection moments and complete the track initiation;

[0087] The target angular velocity information calculation module is used to obtain target measurement information at multiple detection moments and calculate the target angular velocity information using angle changes and time changes;

[0088] The tracking association and continuation maintenance module is used to use the current target measurement information and calculate the current target angular velocity information, and compare it with the set target angular velocity demarcation threshold value. If the current target angular velocity is greater than the set target angular velocity demarcation threshold value, the non-uniform interval target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point.

[0089] The candidate target judgment and track update module is used to continue to obtain multiple target angle measurement information and compare it with the target predicted angle value, track the targets within the threshold range as candidate measurements, and use the candidate measurement information to compare with the target predicted point. The candidate measurement closest to the target predicted point is used as the final updated measurement of the target, and the target track data is updated;

[0090] The current track output module is used to manage the track after measurement and update, such as editing and canceling, and finally obtain the target's current track and output it. At the same time, the next track update and output are performed through the tracking association and continuation maintenance module.

[0091] In the preferred embodiment of the system, each module is specifically used to implement the above preferred method embodiment, which will not be described in detail here.

[0092] The present application also provides a non-transitory computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, and when the program is executed by a processor, the corresponding function is implemented. The computer-readable storage medium of this embodiment is used to implement the pure angle target tracking method of the method embodiment when executed by the processor.

[0093] In summary, the pure angle prediction and tracking method under non-uniform interval conditions of the present invention can realize pure angle prediction of the pure angle tracking system for non-uniform interval detection, and effectively solves the problem that the conventional angle prediction algorithm has large prediction errors and tracking difficulties due to the nonlinear characteristics of the target motion under the condition of large target angle changes; at the same time, when the target angle changes slightly and the error is significant compared with the angle change, resulting in inaccurate prediction of formula (1), the target angle prediction is realized by combining the traditional algorithm of multi-point extrapolation, thereby establishing a relatively complete solution to the pure angle tracking problem suitable for non-uniform interval passive detection equipment to adapt to different target angle change conditions.

[0094] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A pure angle target tracking method, characterized in that: The following steps are involved: S1. Target tracking system initialization: According to the target angular velocity and its error characteristics, the target angular velocity demarcation threshold value using the non-uniformly spaced target angle prediction method or the multi-point extrapolation algorithm is set, and the relevant tracking association threshold of the target tracking system is set according to the conventional tracking gate rules; S2, target tracking system track initiation: obtain target measurement information for three consecutive detection moments and complete track initiation; S3. Calculation of target angular velocity information for established track: Obtain target measurement information at multiple detection moments and calculate the target angular velocity information using angle change and time change; S4. Tracking association and continued maintenance: The current target angular velocity information calculated using the current target measurement information is compared with the set target angular velocity demarcation threshold value. If the current target angular velocity is greater than the set target angular velocity demarcation threshold value, the non-uniformly spaced target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point. S5. Candidate target determination and track update: Continue to obtain multiple target angle measurement information and compare it with the target predicted angle value. Track targets within the threshold range as candidate measurements, and use the candidate measurement information to compare with the target predicted point in step S4. The candidate measurement closest to the target predicted point is used as the final updated measurement of the target, and the target track data is updated. S6. Output of the current track: edit and cancel the track management after the measurement update, and finally obtain the target's current track and output it, and enter step S4 for the next track update and output.

2. The angle-only target tracking method according to claim 1, characterized in that: The non-uniformly spaced target angle prediction method in step S1 is to use the formula （1） Perform target angle prediction calculation, where: is the known observed target azimuth, is the target predicted azimuth, The time interval corresponding to the corresponding movement distance when the target moves in a uniform straight line.

3. The angle-only target tracking method according to claim 1, characterized in that: Setting the target angular velocity demarcation threshold value in step S1 refers to setting the target angular velocity demarcation threshold value to 3 to 4 times the angular velocity error.

4. The angle-only target tracking method according to claim 1, wherein: Setting the relevant tracking threshold of the target tracking system according to the conventional tracking gate rule in step S1 refers to generating the angle tracking threshold using the elliptical tracking rule.

5. The angle-only target tracking method according to claim 1, characterized in that: Acquiring target measurement information in step S2 refers to obtaining the azimuth and pitch angle measurement information of the target through a pure angle detection device, and performing system error registration, outlier elimination, and spatial registration processing to form the target measurement information.

6. The angle-only target tracking method according to claim 1, characterized in that: The logic method in step S3 is to first assume the initial track of the target within the target initial speed range and then confirm it through the third point.

7. The angle-only target tracking method according to claim 2, characterized in that: The calculation of the target predicted angle value using the non-equally spaced target angle prediction method in step S4 means: obtaining the corresponding time of the current target measurement information and the first three detection times of the track and directly calculating the angle value at the current time using formula (1).

8. The angle-only target tracking method according to claim 1, characterized in that: Calculating the target predicted angle value using the multi-point extrapolation algorithm in step S4 means directly using the target measurement information at the previous detection moment and the target angular velocity prediction calculated in step S3 as the angle prediction value at the current moment.

9. A pure angle target tracking system, characterized in that: include: An initialization module is used to set the target angular velocity demarcation threshold using a non-equally spaced target angle prediction method or a multi-point extrapolation algorithm according to the target angular velocity and its error characteristics, and to set the relevant tracking association threshold of the target tracking system according to conventional tracking gate rules; The track initiation module is used to obtain target measurement information at three consecutive detection moments and complete the track initiation; The target angular velocity information calculation module is used to obtain target measurement information at multiple detection moments and calculate the target angular velocity information using angle changes and time changes; The tracking association and continuation maintenance module is used to use the current target measurement information and calculate the current target angular velocity information, and compare it with the set target angular velocity demarcation threshold value. If the current target angular velocity is greater than the set target angular velocity demarcation threshold value, the non-uniform interval target angle prediction method is used to calculate the target prediction angle value and determine the target prediction point. Otherwise, the multi-point extrapolation algorithm is used to calculate the target prediction angle value and determine the target prediction point. The candidate target judgment and track update module is used to continue to obtain multiple target angle measurement information and compare it with the target predicted angle value, track the target within the threshold range as a candidate measurement, and use the candidate measurement information to compare with the target predicted point. The candidate measurement closest to the target predicted point is used as the final updated measurement of the target, and the target track data is updated; The current track output module is used to edit and cancel the track management after measurement update, and finally obtain the target's current track and output it. At the same time, the next track update and output are performed through the tracking association and continuation maintenance module.

10. A computer storage medium, characterized in that A computer program executable by a processor is stored therein, and the computer program executes the angle-only target tracking method according to any one of claims 1 to 8.

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