A Tracking Method for the Scanning Position of a Mechanical Scanning Radar Antenna

Abstract

The present invention discloses a tracking method for the scanning position of a mechanical scanning radar antenna, which specifically includes the following steps: S1, deploying a jammer; S2, collecting radar signals and processing them using a channelized receiver; S3, using a signal sorter to screen out target radar signals and draw a time-amplitude diagram; S4, performing a smoothing filter process on the amplitude AMP data set of the target radar signals; S5, extracting local peak features and training a clustering algorithm model; S6, using the trained clustering algorithm model to output the local peak feature categories of the target radar signals; S7, calculating the scanning period T of the mechanical scanning radar antenna according to the arrival time TOA difference between two adjacent local peak points. In the case of strong interference, the jammer can accurately measure the scanning period according to the present invention; in addition, in the case of a change in the scanning period, it is ensured that the jammer can achieve real-time tracking of the scanning position of the mechanical radar antenna.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar detection, and specifically relates to a method for tracking the scanning position of a mechanical scanning radar antenna. Background Art

[0002] A radar is an electronic device that uses radio methods to detect targets and determine their spatial positions. A track refers to the navigation track formed by a moving target measured by a radar on the radar screen. Track deception is a means of deception interference in the field of radar electronic countermeasures. It can form realistic false targets on the radar screen, display information such as azimuth, distance, and speed, and can be batch-coded by the radar to form tracks. The prerequisite for forming a stable track is that the jammer can accurately track and predict the scanning position of the radar antenna.

[0003] In the prior art, the conventional maximum amplitude method is generally used to track and predict the scanning position of a mechanical radar antenna, but it has the following deficiencies: 1) In the case of strong interference, the jammer cannot accurately measure the scanning period: when there are other interference sources around the radar against which the jammer is operating or other radars are turned on simultaneously and the maximum amplitudes are close, it is difficult to obtain an accurate antenna scanning period when measuring the scanning period by the conventional maximum amplitude method; 2) In the case of a change in the scanning period, the jammer cannot achieve real-time tracking of the scanning position of the mechanical radar antenna: when the radar suddenly changes the antenna scanning period, if the jammer cannot track the antenna scanning position, a large position deviation will occur in the formed track, resulting in the inability to form a track. Therefore, it is urgent to solve the problems of the accuracy of the jammer in measuring the radar antenna scanning period and the real-time tracking of its scanning period change. Summary of the Invention

[0004] The present invention provides a method for tracking the scanning position of a mechanical scanning radar antenna. In the case of strong interference, the jammer can accurately measure the scanning period; in addition, in the case of a change in the scanning period, it is ensured that the jammer can achieve real-time tracking of the scanning position of the mechanical radar antenna.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for tracking the scanning position of a mechanical scanning radar antenna specifically includes the following steps:

[0007] S1. Deploy the jammer and align the receiving antenna on the jammer with the mechanical scanning radar antenna;

[0008] S2. Real-time collect radar signals and process them using a channelized receiver, measure the arrival time TOA, carrier frequency CF, pulse width PW, amplitude AMP, and AD sampling data of each pulse in the received radar signals, and form an original data set;

[0009] S3. Use a signal sorter to perform signal sorting on the original data set, screen out the target radar signals, and draw a time-amplitude diagram;

[0010] Specifically, take the original data set as the input data of the signal sorter to further obtain the pulse repetition period, variation law, and intra-pulse signal pattern of each radar signal; then match with the radar database to screen out the target radar signals, and obtain the amplitude AMP data set of the target radar signals; finally, draw a time-amplitude diagram based on the amplitude AMP data set and time stamps of the target radar signals;

[0011] S4. Perform smoothing filtering on the amplitude AMP data set of the target radar signals to remove the high-frequency random noise of the target radar signals and eliminate the interference caused by occasional high-power signals;

[0012] S5. Extract local peak features and perform clustering algorithm model training;

[0013] Specifically, according to the variation range of the scanning period T of the mechanical scanning radar antenna, use the binary search algorithm to extract the local peak and RMS value features of the amplitude AMP data set of the target radar signals, perform clustering algorithm model training, and then output the local peak feature categories, numbers, and moments, and mark each local peak point of the target radar signals on the time-amplitude diagram drawn in S3;

[0014] S6. Use the trained clustering algorithm model to output the local peak feature categories of the target radar signals;

[0015] Specifically, change the scanning period T of the mechanical scanning radar antenna and the radar transmission power P, use the clustering algorithm model to output the local peak feature categories of the target radar signals corresponding to different scanning periods T, compare with the local peak feature categories displayed on the time-amplitude diagram marked in S5, and correct the ones with incorrect display;

[0016] S7. Calculate the scanning period T of the mechanical scanning radar antenna according to the arrival time TOA difference between two adjacent local peak points;

[0017] Specifically, use the local peak feature categories of the target radar signals output by the clustering algorithm model, calculate the feature category corresponding to the maximum local peak of the target radar signals and mark it as the position where the mechanical scanning radar antenna is facing the jammer, and calculate the scanning period T of the mechanical scanning radar antenna according to the arrival time TOA difference between two adjacent local peak points in the feature category corresponding to the maximum local peak;

[0018] S8. Match the short-term data of the tracking position in the radar signal collected in S1 with the local peak characteristics within the scanning period T of the recorded mechanical scanning radar antenna, track the change in the scanning period of the mechanical scanning radar antenna based on the feature matching result and the time difference of arrival (TOA) of the feature points, i.e., the local peak points, and deduce the scanning position of the mechanical scanning radar antenna.

[0019] Specifically,

[0020] 1) Let the short-term data of the radar signal be the sequence s(τ), and the scanning period of the mechanical scanning radar antenna be T (T min ≤T≤T max ), where T min refers to the minimum scanning period of the mechanical scanning radar antenna, and T max refers to the maximum scanning period of the mechanical scanning radar antenna;

[0021] 2) Perform feature matching on the short-term data sequence s(τ) of the radar signal and the data of the recorded scanning position of the mechanical scanning radar antenna ;

[0022] 3) Normalize the amplitude AMP data of the radar signal in S1, and then calculate the root mean square error:

[0023]

[0024] where T is the scanning period of the mechanical scanning radar antenna; is the scanning position of the mechanical scanning radar antenna; δ is the root mean square error of the normalized amplitude data when the mechanical radar antenna scanning position is ; N is the number of data;

[0025] 4) If is less than the threshold, it indicates that the scanning period of the mechanical scanning radar antenna remains unchanged; if is greater than the threshold, it indicates that the scanning period of the mechanical scanning radar antenna has changed;

[0026] 5) Continue to calculate according to formula (1) between and , and deduce that the position corresponding to the minimum root mean square error is the scanning position of the mechanical scanning radar antenna.

[0027] Preferably, the threshold is set to 5 to 10 times of

[0028] The beneficial effects of the present invention are:

[0029] 1) This method can track the scanning position of the radar antenna through a single receiving antenna, and the jammer can simulate the track at any angle of the radar;

[0030] 2) When the radar antenna scanning speed changes, this method can also infer the scanning position of the radar antenna, realizing the track simulation under the condition of changing the radar scanning cycle;

[0031] 3) The algorithm model can be adjusted under human intervention to achieve self-learning of the current electromagnetic environment and improve the accuracy of radar antenna scanning position recognition to adapt to more types of radars and geographical locations. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the process of the present invention;

[0033] Figure 2 It is a time-amplitude diagram drawn from the original amplitude data of the radar signal of the present invention;

[0034] Figure 3 This is a time-amplitude diagram after smoothing and filtering processing of the present invention;

[0035] Figure 4 This is a schematic diagram of local peak points found by the present invention using a clustering algorithm. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] Example

[0038] like Figures 1 to 4 As shown, a method for tracking the scanning position of a mechanical scanning radar antenna includes the following steps:

[0039] S1. Deploy a jammer at a fixed location within 1 km of the mechanical scanning radar and align the receiving antenna on the jammer with the mechanical scanning radar antenna.

[0040] S2, real-time acquisition of radar signals and processing them using a channelized receiver, measuring the arrival time TOA, carrier frequency CF, pulse width PW, amplitude AMP and AD sampling data of each pulse in the received radar signal to form an original data set;

[0041] S3. Use a signal sorter to sort the original data set, filter out the target radar signal and draw a time-amplitude graph;

[0042] Specifically, the original data set is used as the input data of the signal sorter to further obtain the pulse repetition period, variation law, and intra-pulse signal pattern of each radar signal; then it is matched with the radar database to screen out the target radar signal, and the amplitude AMP data set of the target radar signal is obtained; finally, a time-amplitude diagram is drawn based on the amplitude AMP data set and time stamp of the target radar signal;

[0043] S4. Perform smoothing filtering on the amplitude AMP data set of the target radar signal to remove the high-frequency random noise of the target radar signal and eliminate the interference caused by occasional high-power signals;

[0044] S5. Extract local peak features and perform clustering algorithm model training;

[0045] Specifically, according to the variation range of the scanning period T of the mechanical scanning radar antenna, the local peak and RMS value features of the amplitude AMP data set of the target radar signal are extracted using the binary search algorithm for clustering algorithm model training, and then the local peak feature categories, numbers, and moments are output, and each local peak point of the target radar signal is marked on the time-amplitude diagram drawn in S3;

[0046] S6. Use the trained clustering algorithm model to output the local peak feature categories of the target radar signal;

[0047] Specifically, change the scanning period T of the mechanical scanning radar antenna and the radar transmission power P, use the clustering algorithm model to output the local peak feature categories of the target radar signal corresponding to different scanning periods T, compare with the local peak feature categories shown on the time-amplitude diagram marked in S5, and correct the wrongly displayed ones;

[0048] S7. Calculate the scanning period T of the mechanical scanning radar antenna according to the time difference TOA between the arrival times of two adjacent local peak points;

[0049] Specifically, use the local peak feature categories of the target radar signal output by the clustering algorithm model to calculate the feature category corresponding to the maximum local peak of the target radar signal and mark it as the position where the mechanical scanning radar antenna is facing the jammer, and calculate the scanning period T of the mechanical scanning radar antenna according to the time difference TOA between two adjacent local peak points in the feature category corresponding to the maximum local peak;

[0050] S8. Match the short-time data at the tracking position in the radar signal collected in S1 with the local peak features within the scanning period T of the recorded mechanical scanning radar antenna, and track the change of the scanning period of the mechanical scanning radar antenna according to the feature matching result and the time difference TOA between the feature points, that is, the local peak points, to deduce the scanning position of the mechanical scanning radar antenna;

[0051] Specifically,

[0052] 1) Let the short - time data of the radar signal be the sequence s(τ), and the scanning period of the mechanically scanned radar antenna be T (T min ≤ T ≤ T max ), where T min refers to the minimum scanning period of the mechanically scanned radar antenna, and T max refers to the maximum scanning period of the mechanically scanned radar antenna;

[0053] 2) Perform feature matching on the short - time data sequence s(τ) of the radar signal and the data of the recorded scanning position of the mechanically scanned radar antenna ;

[0054] 3) Standardize the amplitude AMP data of the radar signal in S1, and then calculate the root - mean - square error:

[0055]

[0056] where T is the scanning period of the mechanically scanned radar antenna; is the scanning position of the mechanically scanned radar antenna; δ is the root - mean - square error of the normalized amplitude data when the mechanical radar antenna is at the scanning position ; N is the number of data;

[0057] 4) If is less than the threshold value, it indicates that the scanning period of the mechanically scanned radar antenna remains unchanged; if is greater than the threshold value, it indicates that the scanning period of the mechanically scanned radar antenna has changed;

[0058] 5) Continue to calculate according to formula (1) between and , and deduce that the position corresponding to the minimum root - mean - square error is the scanning position of the mechanically scanned radar antenna.

[0059] As a further technical solution of this embodiment, the threshold value is set to 5 - 10 times of

[0060] Working principle of the present invention: The present invention classifies the local peak features of radar signals through a clustering algorithm model; the accuracy of the clustering algorithm model is achieved through manual correction, and then supervised algorithm learning is carried out; the scanning period T of the mechanical scanning radar antenna is obtained from the time-of-arrival (TOA) difference between two adjacent local peak points in the feature category corresponding to the maximum local peak output by the clustering algorithm model; then, the local peak features within the scanning period T of the mechanical scanning radar antenna recorded in the radar database are feature-matched with the short-time data of the radar signals collected in real time by the jammer, and the scanning position of the mechanical scanning antenna is deduced according to the matching result, so as to realize the intelligent tracking of the scanning position of the mechanical scanning radar antenna.

[0061] The present invention can be applied to a radar jammer to realize the real-time tracking of the scanning position of the radar antenna, avoid the problem that the jammer cannot track the scanning position of the radar antenna due to the change of the radar scanning period, and further improve the authenticity of various deception jammings implemented by the jammer on the radar.

[0062] The embodiments described above are only used to describe the preferred embodiments of the present invention, rather than to limit the scope of the present invention. Without departing from the principles and essence of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A tracking method for the scanning position of a mechanical scanning radar antenna, characterized in that, Specifically, the following steps are included: S1. Deploy a jammer and align the receiving antenna on the jammer with the mechanical scanning radar antenna; S2. Collect radar signals in real time and process them using a channelized receiver, measure the arrival time TOA, carrier frequency CF, pulse width PW, amplitude AMP, and AD sampling data of each pulse in the received radar signals, and form an original data set; S3. Use a signal sorter to perform signal sorting on the original data set, screen out the target radar signals, and draw a time-amplitude diagram; Specifically, take the original data set as the input data of the signal sorter, further obtain the pulse repetition period, variation law, and in-pulse signal pattern of each pulse in the radar signal; then match with the radar database to screen out the target radar signals, and obtain the amplitude AMP data set of the target radar signals; finally, draw a time-amplitude diagram based on the amplitude AMP data set and time stamps of the target radar signals; S4. Perform smoothing filtering on the amplitude AMP data set of the target radar signals to remove the high-frequency random noise of the target radar signals and eliminate the interference caused by occasional high-power signals; S5. Extract local peak features and perform clustering algorithm model training; Specifically, according to the variation range of the scanning period T of the mechanical scanning radar antenna, use the binary search algorithm to extract the local peak and RMS value features of the amplitude AMP data set of the target radar signals, perform clustering algorithm model training, then output the local peak feature categories, numbers, and moments, and mark each local peak point of the target radar signals on the time-amplitude diagram drawn in S3; S6. Use the trained clustering algorithm model to output the local peak feature categories of the target radar signals; Specifically, change the scanning period T of the mechanical scanning radar antenna and the radar transmission power P, use the clustering algorithm model to output the local peak feature categories of the target radar signals corresponding to different scanning periods T, compare with the local peak feature categories shown on the time-amplitude diagram marked in S5, and correct the wrongly displayed ones; S7. Calculate the scanning period T of the mechanical scanning radar antenna according to the arrival time TOA difference between two adjacent local peak points; Specifically, use the local peak feature categories of the target radar signals output by the clustering algorithm model, calculate the feature category corresponding to the maximum local peak of the target radar signals and mark it as the position where the mechanical scanning radar antenna is facing the jammer, and calculate the scanning period T of the mechanical scanning radar antenna according to the arrival time TOA difference between two adjacent local peak points in the feature category corresponding to the maximum local peak; S8. Match the short-time data at the tracking position in the radar signals collected in S1 with the local peak features within the recorded scanning period T of the mechanical scanning radar antenna, and track the change of the scanning period of the mechanical scanning radar antenna according to the feature matching result and the arrival time TOA difference of the feature points, i.e., local peak points, and deduce the scanning position of the mechanical scanning radar antenna; Specifically, 1) Let the short - time data of the radar signal be the sequence s(τ), and the scanning period of the mechanically scanned radar antenna be T (T min ≤T≤T max ), where T min refers to the minimum scanning period of the mechanically scanned radar antenna, and T max refers to the maximum scanning period of the mechanically scanned radar antenna; 2) Perform feature matching on the short-time data sequence s(τ) of the radar signal and the data of the recorded mechanical scanning radar antenna scanning position ; 3) Standardize the amplitude AMP data of the radar signals in S1, and then calculate the root mean square error: Among them, T is the scanning period of the mechanical scanning radar antenna; is the scanning position of the mechanical scanning radar antenna; δ is the scanning position of the mechanical radar antenna when the root mean square error of the normalized amplitude data; N is the number of data; 4) If δ is less than the threshold value, it indicates that the scanning period of the mechanical scanning radar antenna remains unchanged; if δ is greater than the threshold value, it indicates that the scanning period of the mechanical scanning radar antenna changes; 5) Continue the calculation according to formula (1) between and to deduce that the position corresponding to the minimum root mean square error is the scanning position of the mechanical scanning radar antenna.

2. The tracking method for the scanning position of a mechanical scanning radar antenna according to claim 1, characterized in that, The threshold is set to be 5 to 10 times of δ when the scanning period remains unchanged

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