CN116540198B - High-speed target motion track re-estimation method and system based on compact high-frequency radar - Google Patents
High-speed target motion track re-estimation method and system based on compact high-frequency radarInfo
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- CN116540198B CN116540198B CN202310493155.2A CN202310493155A CN116540198B CN 116540198 B CN116540198 B CN 116540198B CN 202310493155 A CN202310493155 A CN 202310493155A CN 116540198 B CN116540198 B CN 116540198B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/415—Identification of targets based on measurements of movement associated with the target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/03—Details of HF subsystems specially adapted therefor, e.g. common to transmitter and receiver
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
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- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a high-speed target motion track re-estimation method and system based on a compact high-frequency radar, which belong to the technical field of radars and comprise the steps of performing coherent accumulation on original radar echo data for a preset time period to obtain a target radial distance value and a target speed value, determining a target arrival angle value through a multiple signal classification algorithm, calculating a target original point track according to the target radial distance value and the target arrival angle value, performing track prediction on the target original point track by utilizing the target speed value to obtain a predicted track set, calculating an average course of each predicted track in the predicted track set, screening the predicted track set according to a course threshold value to obtain a screened predicted track set, and fusing the screened predicted track set to obtain a final track result. The invention utilizes the speed measurement value to re-estimate the original point trace of the target, and effectively improves the precision of the compact high-frequency radar output track under the condition of not changing the precision of the arrival angle estimation.
Description
Technical Field
The invention relates to the technical field of radars, in particular to a high-speed target motion track re-estimation method and system based on a compact high-frequency radar.
Background
High Frequency (HF) radar is receiving more and more attention with its beyond-the-horizon detection and all-weather operation characteristics, and especially in the field of target tracking and positioning, it is very widely used. Among them, the compact High-frequency ground wave radar (High-Frequency Surface WAVE RADAR, HFSWR) is widely used in coastal areas due to the advantages of small erection area, easy maintenance, low cost, etc. In recent years, HFSWR plays an important role in sea inversion and slow target detection.
The conventional method of HFSWR measurement track is to detect and then track, and first perform Constant False alarm detection (Constant False-ALARM RATE, CFAR) detection on the range-doppler spectrum to determine the radial distance and radial velocity of the target. The target signal of the cross-loop/monopole antenna is then subjected to angle of arrival (Direction Of Arrival, DOA) estimation using a multiple signal classification (Multiple Signal Classification, MUSIC) method, thereby obtaining the original trace of the target. And finally, filtering the original track by using a Kalman filter and other filtering algorithms, and outputting a final track. However, the error in the measurement of DOA is large, typically up to about 10 °. At this time, the accuracy improvement of the output track by using the filtering algorithm is not obvious. For this reason, many researchers have been working to improve the DOA estimation accuracy. For example, the TF-Music algorithm extracts envelope information of the target signal along the time-frequency ridge, and eliminates signal instability caused by Doppler frequency variation, thereby improving the orientation accuracy of the unstable target. In addition, narrower beam width can be obtained by utilizing the binary cross ring/monopole antenna array to estimate the angle, so that the DOA estimation accuracy is improved. However, under the condition of low target signal-to-noise ratio, the two methods have no obvious effect on improving DOA estimation accuracy. In addition, the positioning accuracy of the target can be improved by using the bistatic radar for cross positioning, but this requires high-cost hardware support. In summary, HFSWR outputs high precision motion profiles of high speed targets are a challenge.
In view of the challenges in the above applications, there is a need to propose new methods for high-speed target motion track tracking estimation.
Disclosure of Invention
The invention provides a high-speed target motion track re-estimation method and system based on a compact high-frequency radar, which are used for solving the defect that in the prior art, the precision of the compact high-frequency radar in the high-speed target motion track estimation is not high.
In a first aspect, the present invention provides a high-speed target motion track re-estimation method based on a compact high-frequency radar, including:
Receiving original radar echo data, performing a long-time coherent accumulation algorithm of a preset time period on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm;
Calculating according to the target radial distance value and the target arrival angle value to obtain a target original point track, and carrying out track prediction on the target original point track by utilizing the target speed value to obtain a predicted track set;
Calculating the average course of each predicted track in the predicted track set, and screening the predicted track set according to a course threshold value to obtain a screened predicted track set;
and fusing the screened predicted track sets to obtain a final track result.
In a second aspect, the present invention also provides a high-speed target motion track re-estimation system based on a compact high-frequency radar, including:
The detection module is used for receiving original radar echo data, carrying out a long-time coherent accumulation algorithm of a preset time period on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm;
The calculation module is used for calculating a target original point track according to the target radial distance value and the target arrival angle value, and carrying out track prediction on the target original point track by utilizing the target speed value to obtain a predicted track set;
The screening module is used for calculating the average course of each predicted track in the predicted track set, and screening the predicted track set according to a course threshold value to obtain a screened predicted track set;
And the fusion module is used for fusing the screened predicted track sets to obtain a final track result.
In a third aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the compact high frequency radar-based high speed target motion track re-estimation method as described in any one of the above when executing the program.
According to the compact high-frequency radar-based high-speed target motion track re-estimation method and system, the motion track of the target is predicted by fully utilizing the correlation among radar measurement data and utilizing the speed measurement and the original point track of the target, the track prediction is carried out on the original point track of the target by utilizing the speed measurement value, and the precision of the compact high-frequency radar output track is effectively improved under the condition that the precision of the arrival angle estimation is not changed.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a compact high-frequency radar-based high-speed target motion track re-estimation method provided by the invention;
FIG. 2 is a schematic diagram of DOA measurement results provided by the present invention;
FIG. 3 is a statistical histogram of predicted track corresponding heading provided by the present invention;
FIG. 4 is a diagram of the re-estimated motion trail result provided by the present invention;
FIG. 5 is a schematic diagram of a compact high-frequency radar-based high-speed target motion track re-estimation system;
Fig. 6 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Aiming at the problems that when the existing high-frequency compact radar detects a high-speed target, the speed of the target is high, the radial distance between the target and the radar is changed quickly, a plurality of DOAs need to be estimated by radar data, the number of signal snapshots is small, and the measured flight path deviates from the real flight path, the invention provides a high-speed target motion flight path re-estimation method based on the compact target radar, which can accurately estimate the motion flight path of a low-altitude flying target on the premise of not changing the radar waveform.
Fig. 1 is a schematic flow chart of a high-speed target motion track re-estimation method based on a compact high-frequency radar according to an embodiment of the present invention, as shown in fig. 1, including:
Step 100, receiving original radar echo data, performing a long-time coherent accumulation algorithm for a preset time period on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm;
step 200, calculating a target original track according to the target radial distance value and the target arrival angle value, and carrying out track prediction on the target original track by utilizing the target speed value to obtain a predicted track set;
Step 300, calculating the average course of each predicted track in the predicted track set, and screening the predicted track set according to a course threshold value to obtain a screened predicted track set;
And 400, fusing the screened predicted track sets to obtain a final track result.
The method comprises the steps of receiving radar echo data, carrying out long-time coherent accumulation detection on the original radar data to obtain radial distance and speed measurement values of a target, estimating corresponding DOA change through a MUSIC algorithm, calculating original points of the target according to the radial distance and the DOA measurement values of the target, carrying out track prediction on the original points in combination with the speed measurement values, calculating average heading of each predicted track, screening a predicted track set by using heading threshold values, fusing the screened predicted track sets, completing correction on the original points, and outputting a final track result.
The invention fully utilizes the relativity among radar measurement data, re-estimates the original point trace of the target by utilizing the speed measurement value, and effectively improves the precision of the compact high-frequency radar output track under the condition of not changing the precision of the arrival angle estimation.
Based on the above embodiment, performing coherent accumulation on the original radar echo data for a preset period of time to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm includes:
The method comprises the steps of determining the total frequency sweep cycle number of a radar, obtaining a radial distance value and a speed value of any frequency sweep cycle in the total frequency sweep cycle number of the radar through a long-time coherent accumulation algorithm in a preset time period, and obtaining an arrival angle value of any frequency sweep cycle in the total frequency sweep cycle number of the radar through a multiple signal classification algorithm.
Specifically, in the embodiment of the invention, long-time coherent accumulation and MUSIC algorithm estimation are carried out on the original radar data to obtain the radial distance, speed and DOA measurement values of the target, which are respectively as follows:
Wherein r m、vm、θm represents the true radial distance, the true velocity value and the true DOA of the mth sweep cycle of the target, ε m,r、εm,v、εm,θ represents the measurement errors of the radar corresponding to the radial distance, the velocity value and the DOA, respectively, m=1, 2.
As shown in the DOA measurement results of fig. 2, it can be found that there is a certain deviation between the measurement results of the DOA and the real results due to the presence of measurement errors.
Based on the above embodiment, calculating a target original track according to the target radial distance value and the target arrival angle value includes:
and multiplying the target radial distance value of any sweep frequency period with the sine value and the cosine value of the corresponding arrival angle value respectively to obtain the target original point track.
Specifically, according to the embodiment of the invention, the original track of the target is calculated according to the radial distance and DOA measurement value of the target, and the track prediction is carried out on the original track by combining the speed measurement value, wherein the expression is as follows:
Wherein, the For the original trace of the spot to be measured,The radial distance, speed and DOA of the mth sweep period of the radar measurement are shown, respectively.
Based on the above embodiment, performing track prediction on the target original track by using the target speed value to obtain a predicted track set, including:
determining a correlation coefficient between the radar measurement arrival angle measurement set and the radar sweep frequency time sequence;
Determining a target predicted arrival angle value of the target nth sweep period based on the arrival angle value and the radial distance value of the target mth sweep period, the radial distance value of the nth sweep period, the distance difference value of the target motion in the m sweep periods and in the N sweep periods, and the correlation coefficient, wherein m=1, 2,..N, n=1, 2,..N, N is the number of the sweep periods;
multiplying the target radial distance value of any sweep frequency period with the sine value and the cosine value of the corresponding predicted angle value respectively to obtain a predicted motion track;
Repeating the steps to obtain the predicted track set.
Wherein determining a correlation coefficient between the radar angle of arrival measurement set and the time series of the sweep frequency comprises:
determining the radar arrival angle measurement set and the radar sweep frequency time sequence set;
Calculating the variance of the arrival angle measurement set to obtain a first variance, calculating the variance of the radar frequency sweep time sequence set to obtain a second variance, and calculating the covariance of the arrival angle measurement set and the radar frequency sweep time sequence set;
And obtaining the correlation coefficient according to the covariance, the first variance and the second variance.
The method for determining the target predicted arrival angle value of the target nth frequency sweep period based on the arrival angle value and the radial distance value of the target mth frequency sweep period, the radial distance value of the nth frequency sweep period, the distance difference value of the target motion in the m frequency sweep periods and the n frequency sweep periods and the correlation coefficient comprises the following steps:
determining a radial distance value and an arrival angle value of an mth frequency sweep period of the target, and determining a radial distance value of the nth frequency sweep period of the target, wherein the distance difference value of the target movement in the m frequency sweep periods and in the n frequency sweep periods;
Obtaining an arrival angle adjustment angle based on a radial distance value of the mth sweep period of the target, a radial distance value of the nth sweep period of the target, and a distance difference value of target movement in the m sweep periods and n sweep periods;
If it is determined that m and n are unequal and the product of the difference between m and n and the correlation coefficient is smaller than 0, adding the arrival angle adjustment angle to the arrival angle value of the mth sweep period of the target to obtain a predicted arrival angle value of the nth sweep period of the target;
If it is determined that m and n are unequal and the product of the difference between m and n and the correlation coefficient is greater than 0, subtracting the arrival angle adjustment angle from the arrival angle value of the target mth frequency sweep period to obtain a predicted arrival angle value of the target nth frequency sweep period;
If the m is determined to be equal to n, the target predicted arrival angle value of the target nth sweep period is equal to the arrival angle value of the target mth sweep period.
Specifically, in the embodiment of the invention, the original track is predicted by using the speed measurement, the radial distance and DOA of the nth frequency sweep period measured by the radar are taken as base points, and the DOA of the nth frequency sweep period measured by the radar is predicted by combining the radial distance of the nth frequency sweep period:
Wherein, the The DOA of the nth sweep period obtained by prediction is represented by taking the radar measurement value of the mth sweep period as a base point.DOA measured for the radar of the mth sweep period. arccos () is an inverse cosine function.The radial distance measured for the mth sweep period radar,The radial distance measured for the nth sweep period radar,For the speed of the mth sweep period radar measurement, T r is the duration of one sweep period. ρ is the correlation coefficient between the radar measured DOA and the time mT r, defined as follows:
Wherein, the Representation ofThe covariance with respect to T is given by,Representation ofD (T) represents the variance of T,For the DOA measurement set, t= { mT r |m=1, 2,..n } is the radar time series set.
Further, the radar measured value of the mth sweep period is taken as a base point, and the predicted motion track is taken as
Then, taking radar measured values of any sweep frequency period as base points, and predicting to obtain a set of motion tracks, wherein the set is as follows:
Wherein U p is a predicted set of motion tracks.
Based on the above embodiment, calculating an average heading of each predicted track in the predicted track set, and screening the predicted track set according to a heading threshold value to obtain a screened predicted track set, including:
Any predicted track in the predicted track set is obtained;
Determining longitude and latitude of any sweep frequency period, latitude of any sweep frequency period and longitude and latitude of the next period of any sweep frequency period of any predicted track;
determining a target first position based on the longitude and latitude of any frequency sweeping period, and determining a target second position based on the longitude and latitude of the next period of any frequency sweeping period;
Calculating the course from the first position of the target to the second position of the target, summing all the courses of any predicted course in the total frequency sweeping period number of the radar, and averaging to obtain the average course of any predicted course;
Repeating the steps to obtain a set of average heading of all the predicted tracks;
carrying out statistical analysis on the set of average heading of each predicted track based on the statistical histogram, obtaining heading corresponding to the highest box center in the histogram, and determining a preset track retention duty ratio by the heading information near the highest box center;
determining a screening course lower boundary and a screening course upper boundary according to the course corresponding to the highest box center and the preset track retention duty ratio;
and screening the set of average heading of all the predicted tracks by using the screening heading lower boundary and the screening heading upper boundary to obtain the screened predicted track set.
Specifically, the embodiment of the invention utilizes the heading threshold to screen the predicted track set by calculating the average heading of each predicted track.
Here, the average heading for each predicted track is calculated, expressed as:
Wherein, ψ m is the average heading of the mth track, head (P 1,P2) represents the heading from the position P 1 to the position P 2, x m,k is the longitude of the kth sweep period of the mth track, y m,k is the latitude of the kth sweep period of the mth track, x m,k+1 is the longitude of the (k+1) sweep period of the mth track, and y m,k+1 is the latitude of the (k+1) sweep period of the mth track.
And then, screening the predicted track by using the heading information, wherein the method comprises the following steps of:
And carrying out statistical analysis on the course set to obtain a statistical histogram of the course set. Let the highest box center of the histogram correspond to a heading of ψ c =119°. To preserve heading information of about ζ=80 percent of the highest box and its vicinity, then the upper and lower boundaries of heading are defined as:
Where χ l represents the lower boundary of the screening heading, χ r represents the upper boundary of the screening heading, P { χ l<ψm<χr } represents the probability that the heading is between χ l and χ r, ψ min represents the minimum value of the heading, ψ max represents the maximum value of the heading, and ζ represents the percentage of the predicted track that remains.
The predicted track, as shown in fig. 3, corresponds to a statistical histogram of heading, with a lower boundary of 110 ° and an upper boundary of 130 ° in order to preserve heading information of about 80% (ζ) of the highest box and its vicinity.
Based on the boundary of the heading, the predicted track is screened by using the heading:
Wherein, the For the course set of predicted tracks, χ l =110° represents the lower boundary of the screened course, χ r =130° represents the upper boundary of the screened course, U p is the set of predicted tracks, and U p,f is the set of predicted tracks after screening.
Based on the above embodiment, fusing the screened predicted track set to obtain a final track result, including:
and carrying out average fusion on the screened predicted track set based on the total frequency sweep cycle number of the radar and the preset track retention duty ratio to obtain the final track result.
Specifically, the screened predicted track sets are fused, the correction of the original track is completed, a final track result is output, and the expression is as follows:
Wherein S p is the fused track.
Fig. 4 shows the corrected motion track result in the embodiment of the present invention, and different symbols and marks are used to distinguish the radar position, the original point track, the real track and the re-estimated track, so that the re-estimated motion track has higher track precision compared with the original radar measurement track.
The high-speed target motion track re-estimation system based on the compact high-frequency radar provided by the invention is described below, and the high-speed target motion track re-estimation system based on the compact high-frequency radar described below and the high-speed target motion track re-estimation method based on the compact high-frequency radar described above can be correspondingly referred to each other.
Fig. 5 is a schematic structural diagram of a high-speed target motion track re-estimation system based on a compact high-frequency radar according to an embodiment of the present invention, as shown in fig. 5, including a detection module 51, a calculation module 52, a screening module 53, and a fusion module 54, where:
The detection module 51 is configured to receive original radar echo data, perform a long-time coherent accumulation algorithm for a preset period of time on the original radar echo data to obtain a target radial distance value and a target speed value, determine a target arrival angle value through a multiple signal classification algorithm, calculate a target original track according to the target radial distance value and the target arrival angle value, predict the target original track by using the target speed value to obtain a predicted track set, screen the predicted track set according to a heading threshold by using the screening module 53, and fuse the screened predicted track set by using the fusion module 54 to obtain a final track result.
Fig. 6 illustrates a physical schematic diagram of an electronic device, which may include a processor 610, a communication interface Communications Interface, a memory 630, and a communication bus 640, as shown in fig. 6, where the processor 610, the communication interface 620, and the memory 630 communicate with each other via the communication bus 640. The processor 610 may call logic instructions in the memory 630 to execute a method for estimating a high-speed target motion track based on a compact high-frequency radar, the method including receiving original radar echo data, performing a long-time coherent accumulation algorithm for a preset period of time on the original radar echo data to obtain a target radial distance value and a target speed value, determining a target arrival angle value through a multiple signal classification algorithm, calculating a target original track according to the target radial distance value and the target arrival angle value, performing track prediction on the target original track by using the target speed value to obtain a predicted track set, calculating an average course of each predicted track in the predicted track set, screening the predicted track set according to a course threshold to obtain a screened predicted track set, and fusing the screened predicted track set to obtain a final track result.
Further, the logic instructions in the memory 630 may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.
On the other hand, the invention also provides a computer program product, which comprises a computer program, wherein the computer program can be stored on a non-transitory computer readable storage medium, when the computer program is executed by a processor, the computer can execute the compact high-frequency radar-based high-speed target motion track re-estimation method provided by the methods, the method comprises the steps of receiving original radar echo data, performing a long-time coherent accumulation algorithm on the original radar echo data for a preset time period to obtain a target radial distance value and a target speed value, determining a target arrival angle value through a multiple signal classification algorithm, calculating to obtain a target original point track according to the target radial distance value and the target arrival angle value, predicting the target original point track by utilizing the target speed value to obtain a predicted track set, calculating the average course of each predicted track in the predicted track set, screening the predicted track set according to a course threshold, obtaining a screened predicted track set, and fusing the screened predicted track set to obtain a final track result.
In still another aspect, the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program being implemented when executed by a processor to perform the compact high-frequency radar-based high-speed target motion track re-estimation method provided by the above methods, where the method includes receiving raw radar echo data, performing a long-time coherent accumulation algorithm on the raw radar echo data for a preset period of time to obtain a target radial distance value and a target velocity value, determining a target arrival angle value by a multiple signal classification algorithm, calculating a target original track according to the target radial distance value and the target arrival angle value, performing track prediction on the target original track by using the target velocity value to obtain a predicted track set, calculating an average course of each predicted track in the predicted track set, screening the predicted track set according to a course threshold to obtain a screened predicted track set, and fusing the screened predicted track set to obtain a final track result.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present invention.
Claims (9)
1. A high-speed target motion track re-estimation method based on a compact high-frequency radar is characterized by comprising the following steps:
Receiving original radar echo data, performing a long-time coherent accumulation algorithm of a preset time period on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm;
Calculating according to the target radial distance value and the target arrival angle value to obtain a target original point track, and carrying out track prediction on the target original point track by utilizing the target speed value to obtain a predicted track set;
Calculating the average course of each predicted track in the predicted track set, and screening the predicted track set according to a course threshold value to obtain a screened predicted track set;
Fusing the screened predicted track sets to obtain a final track result;
Calculating the average course of each predicted track in the predicted track set, screening the predicted track set according to a course threshold value to obtain a screened predicted track set, and the method comprises the following steps:
Any predicted track in the predicted track set is obtained;
determining longitude and latitude of any sweep frequency period and longitude and latitude of the next period of any sweep frequency period of the any predicted track;
determining a target first position based on the longitude and latitude of any frequency sweeping period, and determining a target second position based on the longitude and latitude of the next period of any frequency sweeping period;
Calculating the course from the first position of the target to the second position of the target, summing all the courses of any predicted course in the total frequency sweeping period number of the radar, and averaging to obtain the average course of any predicted course;
Repeating the steps to obtain a set of average heading of all the predicted tracks;
carrying out statistical analysis on the set of average heading of the predicted flight path based on the statistical histogram, obtaining heading corresponding to the center of the highest box in the histogram, and determining a preset flight path retention duty ratio by the information of heading nearby the center of the highest box;
determining a screening course lower boundary and a screening course upper boundary according to the course corresponding to the highest box center and the preset track retention duty ratio;
and screening the set of average heading of all the predicted tracks by using the screening heading lower boundary and the screening heading upper boundary to obtain the screened predicted track set.
2. The compact high-frequency radar-based high-speed target motion track re-estimation method according to claim 1, wherein performing a long-time coherent accumulation algorithm for a preset period of time on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm comprises:
The method comprises the steps of determining the total frequency sweep cycle number of a radar, obtaining a radial distance value and a speed value of any frequency sweep cycle in the total frequency sweep cycle number of the radar through a long-time coherent accumulation algorithm in a preset time period, and obtaining an arrival angle value of any frequency sweep cycle in the total frequency sweep cycle number of the radar through a multiple signal classification algorithm.
3. The compact high-frequency radar-based high-speed target motion track re-estimation method according to claim 1, wherein calculating a target origin track from the target radial distance value and the target arrival angle value comprises:
and multiplying the target radial distance value of any sweep frequency period with the sine value and the cosine value of the corresponding arrival angle value respectively to obtain the target original point track.
4. The compact high-frequency radar-based high-speed target motion track re-estimation method according to claim 1, wherein performing track prediction on the target original track by using the target speed value to obtain a predicted track set comprises:
determining a correlation coefficient between the radar arrival angle measurement set and the radar sweep frequency time sequence;
Determining a target predicted arrival angle value of the target nth sweep period based on the arrival angle value and the radial distance value of the target mth sweep period, the radial distance value of the nth sweep period, the distance difference value of the target motion in the m sweep periods and in the N sweep periods, and the correlation coefficient, wherein m=1, 2,..N, n=1, 2,..N, N is the number of the sweep periods;
multiplying the target radial distance value of any sweep frequency period with the sine value and the cosine value of the corresponding predicted angle value respectively to obtain a predicted motion track;
Repeating the steps to obtain the predicted track set.
5. The compact high-frequency radar-based high-speed target motion track re-estimation method according to claim 4, wherein determining a correlation coefficient between a radar arrival angle measurement set and a radar sweep time sequence comprises:
determining the radar arrival angle measurement set and the radar sweep frequency time sequence set;
Calculating the variance of the arrival angle measurement set to obtain a first variance, calculating the variance of the radar frequency sweep time sequence set to obtain a second variance, and calculating the covariance of the arrival angle measurement set and the radar frequency sweep time sequence set;
And obtaining the correlation coefficient according to the covariance, the first variance and the second variance.
6. The method for estimating a high-speed target motion track based on a compact high-frequency radar according to claim 4, wherein determining the target predicted arrival angle value of the target n-th sweep period based on the arrival angle value and the radial distance value of the target m-th sweep period, the radial distance value of the n-th sweep period, the distance difference between the target motion in the m-th sweep period and the n-th sweep period, and the correlation coefficient comprises:
determining a radial distance value and an arrival angle value of an mth frequency sweep period of the target, and determining a radial distance value of the nth frequency sweep period of the target, wherein the distance difference value of the target movement in the m frequency sweep periods and in the n frequency sweep periods;
Obtaining an arrival angle adjustment angle based on a radial distance value of the mth sweep period of the target, a radial distance value of the nth sweep period of the target, and a distance difference value of target movement in the m sweep periods and n sweep periods;
If it is determined that m and n are unequal and the product of the difference between m and n and the correlation coefficient is smaller than 0, adding the arrival angle adjustment angle to the arrival angle value of the mth sweep period of the target to obtain a predicted arrival angle value of the nth sweep period of the target;
If it is determined that m and n are unequal and the product of the difference between m and n and the correlation coefficient is greater than 0, subtracting the arrival angle adjustment angle from the arrival angle value of the target mth frequency sweep period to obtain a predicted arrival angle value of the target nth frequency sweep period;
If the m is determined to be equal to n, the target predicted arrival angle value of the target nth sweep period is equal to the arrival angle value of the target mth sweep period.
7. The compact high-frequency radar-based high-speed target motion track re-estimation method according to claim 1, wherein the merging the screened predicted track set to obtain a final track result comprises:
and carrying out average fusion on the screened predicted track set based on the total frequency sweep cycle number of the radar and the preset track retention duty ratio to obtain the final track result.
8. A compact high-frequency radar-based high-speed target motion track re-estimation system, comprising:
The detection module is used for receiving original radar echo data, carrying out a long-time coherent accumulation algorithm of a preset time period on the original radar echo data to obtain a target radial distance value and a target speed value, and determining a target arrival angle value through a multiple signal classification algorithm;
The calculation module is used for calculating a target original point track according to the target radial distance value and the target arrival angle value, and carrying out track prediction on the target original point track by utilizing the target speed value to obtain a predicted track set;
The screening module is used for calculating the average course of each predicted track in the predicted track set, and screening the predicted track set according to a course threshold value to obtain a screened predicted track set;
the fusion module is used for fusing the screened predicted track sets to obtain a final track result;
the screening module is specifically used for:
Any predicted track in the predicted track set is obtained;
determining longitude and latitude of any sweep frequency period and longitude and latitude of the next period of any sweep frequency period of the any predicted track;
determining a target first position based on the longitude and latitude of any frequency sweeping period, and determining a target second position based on the longitude and latitude of the next period of any frequency sweeping period;
Calculating the course from the first position of the target to the second position of the target, summing all the courses of any predicted course in the total frequency sweeping period number of the radar, and averaging to obtain the average course of any predicted course;
Repeating the steps to obtain a set of average heading of all the predicted tracks;
carrying out statistical analysis on the set of average heading of the predicted flight path based on the statistical histogram, obtaining heading corresponding to the center of the highest box in the histogram, and determining a preset flight path retention duty ratio by the information of heading nearby the center of the highest box;
determining a screening course lower boundary and a screening course upper boundary according to the course corresponding to the highest box center and the preset track retention duty ratio;
and screening the set of average heading of all the predicted tracks by using the screening heading lower boundary and the screening heading upper boundary to obtain the screened predicted track set.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the compact high frequency radar-based high speed target motion trail re-estimation method according to any one of claims 1 to 7 when the program is executed.
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