HRRP correlation assisted broadband radar maneuvering target tracking method and device

Abstract

The invention discloses an HRRP correlation assisted broadband radar maneuvering target tracking method and device, and relates to the technical field of radar target tracking, and the method comprises the steps: obtaining the high-resolution range profile correlation of adjacent moments; processing the correlation of the high-resolution range profiles at adjacent moments by adopting a preset auxiliary function to obtain a correlation weighting factor; and weighting the likelihood function of each motion model by adopting a correlation weighting factor so as to quantify the influence of the high-resolution range profile correlation at adjacent moments on the probability estimation of each motion model. The maneuvering target tracking precision can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar target tracking, and in particular relates to a HRRP correlation-assisted wideband radar maneuvering target tracking method and device. Background Art

[0002] In recent years, with the continuous development of radar technology, broadband radar has gradually become an important research direction in the field of radar target tracking and target recognition due to its ability to accurately measure target distance and provide target high-resolution range profile (HRRP).

[0003] The physical meaning of a high-resolution range profile is the superposition of the projected vectors of the composite echoes from the target's scattering points onto the radar beam. Analyzing high-resolution range profiles reveals the spatial distribution of the target's scattering centers along the radar's line of sight. When a target maneuvers around a corner, the relative positions of the target's scattering points within the radar's line of sight change significantly, reflecting a decrease in the correlation of the high-resolution one-dimensional range profile. Leveraging the characteristic changes in the high-resolution one-dimensional range profile during target maneuvers can improve the accuracy of maneuvering target tracking. Traditional maneuvering target tracking algorithms rely solely on target measurement information to estimate the target's motion state, failing to leverage the target's characteristic information contained in broadband radar echoes. This results in high maneuver detection latency and a significant loss in tracking accuracy. Research on combining high-resolution range profiles with maneuvering target tracking algorithms is still in its exploratory stages.

[0004] Therefore, there is an urgent need to provide a HRRP-assisted radar maneuvering target tracking method to improve the maneuvering target tracking accuracy. Summary of the Invention

[0005] To address the above-mentioned problems in the prior art, the present invention provides a method and apparatus for tracking maneuvering targets with a wideband radar using HRRP correlation assistance. The technical problems to be solved by the present invention are achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a HRRP correlation-assisted wideband radar maneuvering target tracking method, comprising:

[0007] Obtain high-resolution range image correlation at adjacent moments;

[0008] The preset auxiliary function is used to process the correlation of high-resolution range images at adjacent moments to obtain the correlation weighting factor;

[0009] The correlation weighting factor is used to weight the likelihood function of each motion model to quantify the impact of the correlation of high-resolution range images at adjacent moments on the probability estimation of each motion model.

[0010] Second aspect, the present invention further provides an HRRP correlation-assisted wideband radar maneuvering target tracking device, including:

[0011] A data acquisition module, configured to acquire the high-resolution range profile correlation at adjacent moments;

[0012] A first data processing module, configured to process the high-resolution range profile correlation at adjacent moments by using a preset auxiliary function to obtain a correlation weighting factor;

[0013] A first data processing module, configured to weight the likelihood function of each motion model by using the correlation weighting factor to quantify the influence of the high-resolution range profile correlation at adjacent moments on the probability estimation of each motion model.

[0014] Advantages of the present invention:

[0015] The HRRP correlation-assisted wideband radar maneuvering target tracking method and device provided by the present invention calculate the probability weighting coefficients of each motion model by designing an auxiliary function with the high-resolution range profile correlation as the independent variable, quantify the influence of the high-resolution range profile correlation on the model probability estimation in the IMM algorithm, and enable the IMM algorithm to jointly judge the target maneuvering state by fusing measurement information and high-resolution range profile feature information, thereby improving the tracking accuracy of maneuvering targets.

[0016] The following will further describe the present invention in detail with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flowchart of an HRRP correlation-assisted wideband radar maneuvering target tracking method provided by an embodiment of the present invention;

[0018] Figure 2 is a schematic diagram of a target scattering point model provided by an embodiment of the present invention;

[0019] Figure 3 is a schematic diagram of a target motion trajectory provided by an embodiment of the present invention;

[0020] Figure 4 is a schematic diagram of the HRRP at adjacent moments in the target uniform motion state provided by an embodiment of the present invention;

[0021] Figure 5 is a schematic diagram of the HRRP at adjacent moments in the target uniform turning motion state provided by an embodiment of the present invention;

[0022] Figure 6 is a schematic diagram of the HRRP correlation at adjacent moments during the target motion process provided by an embodiment of the present invention;

[0023] Figure 7 It is a schematic diagram of the root mean square error of the target position provided by an embodiment of the present invention;

[0024] Figure 8 It is a schematic diagram of the probability estimation of the uniform motion model provided by an embodiment of the present invention;

[0025] Figure 9 It is a schematic diagram of the probability estimation of the uniform turning motion model 1 provided by an embodiment of the present invention;

[0026] Figure 10 It is a schematic diagram of the probability estimation of the uniform turning motion model 2 provided by an embodiment of the present invention. Detailed implementation manners

[0027] The following further describes the present invention in detail with reference to specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0028] Please refer to Figure 1 , Figure 1 It is a flowchart of a method for tracking maneuvering targets of a broadband radar assisted by HRRP correlation provided by an embodiment of the present invention. A method for tracking maneuvering targets of a broadband radar assisted by HRRP correlation provided by the present invention includes:

[0029] S101. Obtain the high - resolution range profile correlation at adjacent times.

[0030] Specifically, in this embodiment, the correlation smoothing method is used to calculate the high - resolution range profile correlation at adjacent times. The correlation smoothing method refers to calculating the sliding correlation between two high - resolution range profiles, traversing the high - resolution range profile through a preset window, and selecting the maximum value of the high - resolution range profile correlation as the high - resolution range profile correlation at adjacent times to eliminate the translational sensitivity of the high - resolution range profile and ensure the feature alignment of the high - resolution range profiles at adjacent times; among them, the absolute value of the Pearson correlation coefficient is used to measure the high - resolution range profile correlation, which is expressed as:

[0031]

[0032] Among them, r represents the high - resolution range profile correlation, H 1,i represents the amplitude of the i - th range cell of the high - resolution range profile at the first time, H 2,i represents the amplitude of the i - th range cell of the high - resolution range profile at the second time, H 2,j represents the amplitude of the j - th range cell of the high - resolution range profile at the second time, n represents the length of the range profile, and H1 and H2 represent the high - resolution range profiles at adjacent times.

[0033] It should be noted that the correlation coefficient r of the high-resolution range profile ranges from [0, 1]. The closer r is to 1, the higher the correlation between H1 and H2.

[0034] S102. Process the correlation of the high-resolution range profiles at adjacent times using a preset auxiliary function to obtain a correlation weighting factor.

[0035] Specifically, in this embodiment, the expression of the preset auxiliary function is:

[0036]

[0037] where represents the correlation weighting factor at time k. The larger the value of k ∈[0, 1] represents the correlation of the high-resolution range profiles at time k and time k - 1. t r represents a preset correlation threshold. It is considered that the closer the correlation of the high-resolution range profiles at adjacent times is to the threshold, the smaller the probability that the target makes a turning maneuver. a r represents the rate of change used to control the function, and b r represents to avoid the estimation error caused by excessive correction of the motion model probability when the correlation coefficient r of the high-resolution range profile k is close to t r .

[0038] It should be noted that the auxiliary function constructed in this embodiment combines the dual advantages of the exponential function and the quadratic function, specifically manifested as:

[0039] 1. When |r k -t r | increases, the quadratic term a r (r k -t r ) 2 dominates the decay rate of the function, causing to decrease rapidly, and having a strong response ability to significant maneuvering motions. When |r k -t r | decreases, the function exhibits a smooth change characteristic, avoiding false responses caused by correlation fluctuations;

[0040] 2. The exponential function can constrain the value range of to the interval (0, 1), facilitating subsequent weighting processing and smoothing the calculation results.

[0041] S103. Weight the likelihood functions of each motion model using the correlation weighting factor to quantify the influence of the correlation of the high-resolution range profiles at adjacent times on the probability estimation of each motion model.

[0042] Specifically, in this embodiment, the expression of the likelihood function of each motion model is as follows:

[0043]

[0044] Wherein, represents the likelihood function of each motion model, represents the error vector between the actual measurement information and the predicted measurement information, represents the information covariance matrix, and M represents the dimension of the measurement model.

[0045] Weighting the likelihood function of each motion model by using a correlation weighting factor includes:

[0046] When the motion model is a constant velocity model, weighting the likelihood function of the constant velocity model by using a correlation weighting factor is expressed as:

[0047]

[0048] Wherein, represents the result of weighting the likelihood function of the constant velocity model by using a correlation weighting factor, represents the likelihood function of the constant velocity model, represents the correlation weighting factor at time k.

[0049] Weighting the likelihood function of each motion model by using a correlation weighting factor further includes:

[0050] When the motion model is a constant velocity turning model, weighting the likelihood function of the constant velocity turning model by using a correlation weighting factor is expressed as:

[0051]

[0052] Wherein, represents the result of weighting the likelihood function of the constant velocity turning model by using a correlation weighting factor, represents the likelihood function of the constant velocity turning model, represents the correlation weighting factor at time k.

[0053] It should be noted that in this embodiment, the obtained correlation weighting factor is applied to the influence of the probability estimation of each motion model in the IMM algorithm. Among them, the IMM algorithm mainly includes input interaction, filter filtering, model probability update, and state estimation fusion. The correlation weighting factor is applied in the model probability update to realize the final state estimation of the target.

[0054] In summary, the broadband radar maneuvering target tracking method assisted by HRRP correlation provided by the present invention calculates the probability weighting coefficients of each motion model by designing an auxiliary function with the high-resolution range image correlation as the independent variable, quantifies the influence of the high-resolution range image correlation on the model probability estimation in the IMM algorithm, enables the IMM algorithm to jointly judge the target maneuvering state by fusing measurement information and high-resolution range image feature information, and improves the tracking accuracy of maneuvering targets.

[0055] Based on the same inventive concept, the present invention also provides a broadband radar maneuvering target tracking device assisted by HRRP correlation, which is used to implement the broadband radar maneuvering target tracking method assisted by HRRP correlation provided in the above embodiments of the present invention. For the embodiments of the method, please refer to the above, and details will not be described herein again; the device includes:

[0056] A data acquisition module, configured to acquire the high-resolution range image correlation at adjacent time instants;

[0057] A first data processing module, configured to process the high-resolution range image correlation at adjacent time instants by using a preset auxiliary function to obtain a correlation weighting factor;

[0058] A second data processing module, configured to weight the likelihood functions of each motion model by using the correlation weighting factor to quantify the influence of the high-resolution range image correlation at adjacent time instants on the probability estimation of each motion model.

[0059] In an optional embodiment of the present invention, the effect of the broadband radar maneuvering target tracking method assisted by HRRP correlation provided in the above embodiments is verified through a simulation experiment, specifically:

[0060] I. Simulation Conditions

[0061] In the simulation experiment of this embodiment, some scattering points of the Yak aircraft model are selected as the extended target model for tracking. Specifically, refer to Figure 2 , Figure 2 which is a schematic diagram of the target scattering point model provided in the embodiment of the present invention. It is assumed that the radar is located at the origin [0m, 0m], the initial polar coordinate position of the target is [100km, 10.5°], the angle is the angle between the line connecting the target and the radar and the y-axis, the target moves towards the radar direction, and the speed is v = 200m / s. The target moves in a uniform straight line from 1 to 20s, makes a uniform turning motion with an angular velocity ω = 0.05π rad / s from 21 to 40s, and makes a uniform straight line motion from 41 to 60s. The target motion trajectory is shown in Figure 3 , Figure 3It is a schematic diagram of the target motion trajectory provided by an embodiment of the present invention. The HRRP of the target is obtained by simulating broadband echo signals. Other simulation-related parameters are shown in Table 1. The IMM algorithm assisted by HRRP correlation is abbreviated as the HRRP_IMM algorithm.

[0062] Table 1 Simulation Parameter Settings

[0063]

[0064]

[0065] II. Simulation Content and Result Analysis

[0066] Please refer to Figure 4 and Figure 5 , Figure 4 which is a schematic diagram of the HRRP at adjacent moments in the target's uniform motion state provided by an embodiment of the present invention. Figure 5 which is a schematic diagram of the HRRP at adjacent moments in the target's uniform turning motion state provided by an embodiment of the present invention. In order to include as much target scatterer structure information as possible, the distance unit interval length between the left and right two endpoints within the range where the amplitude is not more than 15 dB lower than the peak amplitude is used as the window size to intercept the HRRP. Figure 4 is the HRRP at adjacent moments during the target's uniform motion. Comparing Figure 4 (a) and (b) in it, it can be seen that the HRRP does not change significantly. Figure 5 is the HRRP at adjacent moments during the target's uniform turning motion. Comparing Figure 5 (a) and (b) in it, it can be seen that the HRRP changes significantly, verifying that the HRRP has attitude sensitivity.

[0067] Please refer to Figure 6 , Figure 6 which is a schematic diagram of the correlation of the HRRP at adjacent moments during the target's motion process provided by an embodiment of the present invention. Since the size and position of the intercepted window are not fixed, in order to align the HRRP features and ensure the rationality of the correlation comparison, the sliding correlation of the HRRP at adjacent moments is calculated and the maximum value is taken as the result for comparison. It can be seen from Figure 6 that during the uniform motion stages of the target from 1 s to 20 s and 41 s to 60 s, the HRRP correlation is relatively high, basically remaining above 0.9 with small fluctuations. It should be noted that the HRRP correlation in the 1 s to 20 s stage is more stable than that in the 41 s to 60 s stage because the target motion direction is consistent with the radar line-of-sight direction in the 1 s to 20 s stage, while there is an angle between the target motion speed and the radar line-of-sight direction in the 41 s to 60 s stage, resulting in larger fluctuations in the HRRP correlation. During the uniform turning motion stage from 21 s to 40 s, the HRRP correlation drops significantly, and the fluctuations are large with obvious changes.

[0068] For the parameter t in the HRRP correlation function r , b r , a r , the value ranges are analyzed as follows: First, t r , as the correlation threshold, it is considered that when the HRRP correlation is around t r , the target does not perform maneuvering motion. Therefore, the value of t r can be a relatively large decimal number, and the value range can be [0.8, 1). In this experiment, t r = 0.9 is selected. Second, the role of b r is to avoid large estimation errors caused by excessive correction of the model probability when the HRRP correlation r k approaches t r . Therefore, when r k = t r , should have a value range of [0.8, 0.9]. Being greater than 0.5 is to make have a positive gain for the non-maneuvering model, and being less than 0.9 is to avoid over-correcting the model probability. Then, the value range of b r can be calculated to be approximately [0.1, 0.6]. In this simulation experiment, b r = 0.4 is taken. Finally, the role of a r is to control the change rate of the function. When the target makes a turning maneuver and the HRRP correlation decreases, taking Figure 6 when the target changes from non-maneuvering to turning maneuvering and r k ≈ 0.5 as an example, then should have a value range of [0.1, 0.5]. Being less than 0.5 is to make have a positive gain for the maneuvering model, and being greater than 0.1 is also to avoid over-correcting the model probability. Then, the value range of a r is [1.8, 11.8]. In this experiment, a r = 6 is taken. In summary, the values of the parameters in the HRRP correlation function are t r = 0.9, b r = 0.4, a r = 6.

[0069] Please refer to Figure 7 , Figure 7It is a schematic diagram of the root mean square error of the target position provided by an embodiment of the present invention. Overall, compared with the IMM algorithm, the HRRP_IMM algorithm has a smaller distance error. At the moments when the target maneuvers (21s, 41s), due to the probability transfer of different motion models, the IMM algorithm generates an error mutation. With the assistance of HRRP correlation, the HRRP_IMM algorithm speeds up the probability transfer of the motion model, making the error mutation smaller during the target's maneuvering motion and enabling faster convergence.

[0070] Please refer to Figure 8 , Figure 9 and Figure 10 , Figure 8 It is a schematic diagram of the probability estimation of the uniform motion model provided by an embodiment of the present invention. Figure 9 It is a schematic diagram of the probability estimation of the uniform turning motion model 1 provided by an embodiment of the present invention. Figure 10 It is a schematic diagram of the probability estimation of the uniform turning motion model 2 provided by an embodiment of the present invention. Compared with the IMM algorithm, the HRRP_IMM algorithm has a faster change in the probability estimation of the motion model during target maneuvering and a closer probability estimation of each model to the true value. This shows that the HRRP_IMM algorithm can speed up the probability conversion speed between different motion models in the interaction stage of the IMM algorithm, reduce the position error caused by the change in the motion mode due to target maneuvering, and make the model probability estimation of the target in each motion stage closer to the true value, reducing the distance error. Therefore, it can be concluded that the method proposed in the present invention has higher tracking accuracy compared with the IMM algorithm that only uses measurement information.

[0071] In summary, the present invention provides a method for tracking maneuvering targets of wideband radar assisted by HRRP correlation. By designing an auxiliary function with HRRP correlation as the independent variable, the influence of HRRP feature information on the model probability estimation of the IMM algorithm is quantified, improving the tracking accuracy of maneuvering targets. The present invention takes into account the characteristic that HRRP can represent the distribution of target scattering points, enabling the IMM algorithm to jointly judge the target maneuvering state by fusing measurement information and HRRP feature information, and improving the tracking accuracy of maneuvering targets. The present invention has strong compatibility with the existing technology, retaining the advantages of the existing technology while making up for the deficiencies of the existing technology.

[0072] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant are intended to cover non-exclusive inclusion, so that an article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the article or device including the said element. Words such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The orientation or positional relationship indicated by "above", "below", "left", "right", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation on the present invention.

[0073] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification.

[0074] The above content is a further detailed description of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can still be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for tracking maneuvering targets of a broadband radar assisted by HRRP correlation, characterized in that Including: Obtaining the high - resolution range image correlation at adjacent moments; Processing the high - resolution range image correlation at the adjacent moments by using a preset auxiliary function to obtain a correlation weighting factor; Using the correlation weighting factor to weight the likelihood function of each motion model to quantify the influence of the high - resolution range image correlation at the adjacent moments on the probability estimation of each motion model.

2. The HRRP correlation-assisted wideband radar maneuvering target tracking method according to claim 1, characterized in that, The expression of the preset auxiliary function is: Among them, represents the correlation weighting factor at time k, r k ∈[0, 1] represents the correlation between the high-resolution range image at time k and that at time k - 1, t r represents a preset correlation threshold, a r represents the change rate for controlling the function, b r represents to avoid the estimation error caused by the over-correction of the motion model probability when the correlation r k of the high-resolution range image approaches t r at that time.

3. The HRRP correlation-assisted wideband radar maneuvering target tracking method according to claim 1, characterized in that The obtaining of the high - resolution range image correlation at the adjacent moments includes: Measuring the high - resolution range image correlation by using the absolute value of the Pearson correlation coefficient, expressed as: Among them, r represents the high-resolution range profile correlation, and H 1,i represents the amplitude of the i-th range cell of the high-resolution range profile at the first moment, and H 2,i represents the amplitude of the i-th range cell of the high-resolution range profile at the second moment, and H 2,j represents the amplitude of the j-th range cell of the high-resolution range profile at the second moment. n represents the length of the range profile, and H1 and H2 represent the high-resolution range profiles at adjacent moments.

4. The HRRP correlation-assisted wideband radar maneuvering target tracking method according to claim 1, wherein The expression of the likelihood function of each motion model is: Among them, represents the likelihood function of each motion model, represents the error vector between the actual measurement information and the predicted measurement information, represents the information covariance matrix, and M represents the dimension of the measurement model.

5. The HRRP correlation-assisted wideband radar maneuvering target tracking method according to claim 4, wherein The using of the correlation weighting factor to weight the likelihood function of each motion model includes: When the motion model is a uniform motion model, using the correlation weighting factor to weight the likelihood function of the uniform motion model, expressed as: Among them, represents the result of weighting the likelihood function of the uniform motion model using the said correlation weighting factor, represents the likelihood function of the uniform motion model, represents the correlation weighting factor at the k-th moment.

6. The HRRP correlation-assisted wideband radar maneuvering target tracking method according to claim 4, wherein, The using of the correlation weighting factor to weight the likelihood function of each motion model includes: When the motion model is a uniform turning motion model, using the correlation weighting factor to weight the likelihood function of the uniform turning motion model, expressed as: Among them, represents the result of weighting the likelihood function of the uniform turning model using the said correlation weighting factor, represents the likelihood function of the uniform turning model, represents the correlation weighting factor at the k-th moment.

7. A broadband radar maneuvering target tracking device assisted by HRRP correlation, characterized in that Including: A data acquisition module for obtaining the high - resolution range image correlation at adjacent moments; A first data processing module for processing the high - resolution range image correlation at the adjacent moments by using a preset auxiliary function to obtain a correlation weighting factor; A first data processing module for using the correlation weighting factor to weight the likelihood function of each motion model to quantify the influence of the high - resolution range image correlation at the adjacent moments on the probability estimation of each motion model.

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