CN112255612B - Radar track random jitter evaluation method - Google Patents
Radar track random jitter evaluation method Download PDFInfo
- Publication number
- CN112255612B CN112255612B CN202011209612.3A CN202011209612A CN112255612B CN 112255612 B CN112255612 B CN 112255612B CN 202011209612 A CN202011209612 A CN 202011209612A CN 112255612 B CN112255612 B CN 112255612B
- Authority
- CN
- China
- Prior art keywords
- matrix
- radar
- track
- point
- error
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 10
- 238000004458 analytical method Methods 0.000 claims abstract description 28
- 230000001427 coherent effect Effects 0.000 claims abstract description 24
- 238000012360 testing method Methods 0.000 claims abstract description 14
- 239000011159 matrix material Substances 0.000 claims description 92
- 238000000034 method Methods 0.000 claims description 31
- 238000006243 chemical reaction Methods 0.000 claims description 13
- 230000008859 change Effects 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 9
- 238000010606 normalization Methods 0.000 claims description 5
- 238000001514 detection method Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract description 2
- 230000008569 process Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000009897 systematic effect Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000009432 framing Methods 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a radar track random jitter evaluation method, which maps the positions of radar track points into a polar coordinate system, calculates the position deviation condition of measurement radar track points relative to reference radar track points from two dimensions of angles and distances, and adopts a multi-scale coherent analysis method to quantify and evaluate the random jitter condition of test tracks relative to standard tracks in a plurality of periods.
Description
Technical Field
The invention belongs to the field of air traffic management, and particularly relates to a radar track random jitter evaluation method.
Background
Radar errors generally have systematic and random errors. The systematic error is the difference between the average value of the obtained results and the true value of the measured object, which is measured for a plurality of times on the same measured object. Systematic errors generally originate from the system itself, can be reduced by precise calibration, or can be substantially removed by mathematical compensation. Random errors are also called accidental errors or indefinite errors, are errors with mutual compensation formed by a series of tiny disorder fluctuations of related factors in the measuring process, and mainly are thermal noise and clutter interference of a receiver, and radar random errors can be thoroughly eliminated without an effective method, so that analysis of the radar random errors is needed.
The civil aviation control automation system is accessed to radar signals, target information is obtained through format analysis, and then the target information is displayed on a control system display interface. The controllers conduct daily control activities by observing information such as aircraft position, altitude, speed and the like on the control interface. In order to realize accurate control and ensure the flight safety of an airplane, a controller needs to know the accurate position information of the airplane, and can accurately distinguish the data quality of a radar source through random jitter evaluation of a radar track, so that control judgment errors are avoided.
The previous radar track jitter evaluation method is to calculate the error of a single point, and the random jitter of the track is represented by calculating the standard deviation or variance of the error. The variance or standard deviation represents the degree of overall discrete data, and does not consider the continuous and relevant characteristics of radar tracks in time.
Disclosure of Invention
The invention aims to: the invention aims to provide a practical radar track random jitter evaluation method, which is characterized in that complete available track data is obtained through early-stage data processing, then errors are calculated from two aspects of distance and angle, and a coherent analysis method is used for carrying out quantitative analysis on the error data to obtain a track jitter variation curve. The invention specifically comprises the following steps:
and 1, eliminating the wild value. The aircraft may change its altitude, speed, and position data over time during flight, but its altitude, speed, and position may change only a limited amount over a certain radar scan period. The target information scanned by the radar may deviate from the actual condition obviously due to the influence of some uncertain factors, so that the part of data is removed;
step 2, data compensation;
step 3, performing time alignment; the measured radar A and the standard radar B are respectively (x) A ,y A )、(x B ,y B ) The speed, angle and time are respectively (v) A ,c A ,t A )、(v B ,c B ,t B ). Because the reporting time of the two radars is not necessarily uniform, time alignment operation is required for data points in similar time. Because the time difference between the two radars is short and is smaller than or equal to the minimum scanning period of the two radars, the time alignment operation is realized by adopting a linear interpolation method;
step 4, carrying out coordinate conversion; measured radar A and standard radar B, and position measurement value of same targetRespectively (x) A ,y A )、(x B ,y B ). The coordinates of the radar a are (x RA ,y RA ) It is necessary to combine (x A ,y A )、(x B ,y B ) Conversion to (x) RA ,y RA ) In a polar coordinate system which is a pole, a (ρ A ,θ A ),(ρ B ,θ B )；
Step 5, calculating a distance error; after coordinate conversion, the positions of the targets detected by the detected radar A and the standard radar B are respectively (ρ) A ,θ A ),(ρ B ,θ B ) The difference in the two target-to-pole distances is calculated. Assuming that the target track has K points in total, K distance error values (Δρ) are obtained 1 ,Δρ 2 ,Δρ 3 …Δρ K )；
Step 6, calculating an angle error; after coordinate conversion, the positions of the targets detected by the detected radar A and the standard radar B are respectively (ρ) A ,θ A ),(ρ B ,θ B ) The difference between the two target polar angles is calculated. Assuming that the target track has K points in total, K angle error values (delta theta) are obtained 1 ,Δθ 2 ,Δθ 3 …Δθ K )；
Step 7, multi-scale coherent analysis; and calculating according to the step 4 and the step 5 to obtain the distance error and the angle error of the two points. And respectively carrying out coherent analysis calculation on the distance error and the angle error. For example, the distance jitter is calculated using a coherent analysis method: selecting a scale N (N is a positive integer greater than 1), such as N is 5, and taking the distance error of 5 track points as a group to obtain a 1*5-dimensional vector X 1 ＝(Δρ 1 ,Δρ 2 ,Δρ 3 ,Δρ 4 ,Δρ 5 ) Selecting five continuous groups to obtain a 5-order matrixAnd solving a covariance matrix E of the matrix, solving a eigenvalue of the covariance matrix E, and obtaining a coherence coefficient according to a coherence coefficient calculation formula.
And 8, drawing a jitter curve. If the scale n=5, the window matrix is shifted to the right by one track point, a new matrix overlapping four fifths is obtained, and the coherence coefficient is obtained again according to the method of step 7. The window continues to move right, so that the coherence coefficient is obtained, and adjacent coherence coefficients are connected to obtain a coherence coefficient curve.
In step 1, a rejection threshold is set, and the altitude, speed and position data of the aircraft change with time during the flight, but the altitude, speed and position change within a certain radar scanning period is limited. The target information scanned by the radar may deviate from reality obviously due to the influence of some uncertain factors, so that the part of data is rejected. Setting the maximum speed of a civil aircraft as v (m/s) and the radar scanning period as T(s), wherein the distance between two continuous detection points is not more than v x T (m), setting a random error fixed fault tolerance rate of 20%, and eliminating the points which do not meet the conditions when the distance between two adjacent points is less than v x T x 1.2 (m).
The speed of a general civil aircraft is limited in the flight process, and the speed of the civil aircraft is 900km/h in the straight line flat flight process. Assuming that the speed of the aircraft is 900km/h and the aircraft is in straight flight, if the radar scanning period is 4s, the distance between two adjacent track points is about 250m/s 4 s=1000m under the condition of not accounting for random errors, and the distance between the two adjacent track points is not more than 2000m under the normal condition in consideration of the random errors. Therefore, when performing the calculation, it is necessary to discard some data that is significantly abnormal. The rejection threshold is set, and can be obtained by adding a fixed value on the basis of the theoretical flight distance, and the fixed value can be set to be 1000m according to a large amount of track point data in the actual flight process.
The step 2 comprises the following steps: after step 1, the following situation may occur, where the radar under test has three track points a 1 、A 2 、A 3 After the outlier is removed in the step 1, the track point A is left 1 、A 3 The radar scan period to be measured is known as T, at which point A 1 And point A 3 The time difference between them becomes 2T, so that linearity is required in order to avoid different time scale effectsDifferential method, compensating for a data point instead of point A 2 ；
Because of the situation of possible defect and defect after outlier rejection, or the situation that the track point cannot be reported due to radar scanning and reporting defects. At this time, the missing data needs to be padded by using a linear difference method. Knowing the radar scan period as T, setting track point A 1 The position is (x) 1 ,y 1 ,v 1 ,ω 1 ) Track point A 3 The position is (x) 3 ,y 3 ,v 2 ,ω 2 ) Wherein (x) 1 ,y 1 ) Representing track point A 1 Two-dimensional coordinate data, v 1 Representing track point A 1 Speed, omega 1 Representing track point A 1 Heading of (x) 3 ,y 3 ) Representing track point A 3 Two-dimensional coordinate data, v 2 Representing track point A 1 Speed, omega 2 Representing track point A 3 Adopts a linear differential method to compensate a data point A2 to replace a track point A 2 Then the position of A2 (x 2 ,y 2 ) The method comprises the following steps:
the step 3 comprises the following steps: time alignment is required: the track point data after the repair is divided into measured radar data and standard radar data, and the reporting time of the two radars is not necessarily uniform, so that the data points in similar time need to be subjected to time alignment operation. Because the time difference between the two radars is short and less than or equal to the minimum scanning period of the two radars, the time alignment operation is realized by adopting a linear interpolation method. Setting the position of a target point detected by a detected radar A as A 1 The coordinates are (x A ,y A ) The speed, angle and time are v respectively A ,c A ,t A The method comprises the steps of carrying out a first treatment on the surface of the The target position detected by the standard radar B is B 1 The coordinates are (x B ,y B ) The speed, angle and time are v respectively B ,c B ,t B Through linearity ofObtaining a point B after interpolation 1 Point A 'at the same time' 1 Point A' 1 The position of (x' A ,y’ A ) The calculation formula is as follows:
step 4 comprises: coordinate conversion is required. And obtaining complete corresponding information of the track points after data processing, wherein the radar track information is rectangular coordinate system data. In order to obtain the corresponding distance error and angle error, coordinate transformation is required, and the position (x RA ,y RA ) As a pole of the polar coordinates. The measured radar A and the standard radar B are respectively (x) A ,y A )、(x B ,y B ) It is necessary to combine (x A ,y A )、(x B ,y B ) Conversion to (x) RA ,y RA ) In a polar coordinate system which is a pole, a (ρ A ,θ A ),(ρ B ,θ B ) Wherein ρ is A Representing the distance, theta, of the polar coordinates of the radar a being measured A An angle ρ representing the polar A coordinate of the radar under test B Distance, θ, representing the B polar coordinates of a standard radar B Angle representing standard radar B polar coordinates:
the step 5 comprises the following steps: distance error calculation is required: the distance error is the difference between the distance from the test radar target position to the pole and the distance from the standard radar target position to the pole. The distance error has a positive value and a negative value. Setting up K points in total of the target track to obtain K distance error values (Δρ) 1 ,Δρ 2 ,Δρ 3 …Δρ K )，Δρ K Representing a kth distance error value; to simplify the subsequent calculation, the pair (Δρ 1 ,Δρ 2 ,Δρ 3 …Δρ K ) Normalization processing is carried out to obtain K values (delta zeta) 1 ,Δξ 2 ,Δξ 3 …Δξ K )：
Wherein i=1, 2,3 … K, Δζ K Representing Deltaρ K Normalizing the processed value.
The step 6 comprises the following steps: the angle error calculation needs to be performed: the angle error is the difference between the included angle between the test radar target and the polar axis and the included angle between the standard radar target and the polar axis. The angle error has a positive and negative value. Setting up K points in total of the target track to obtain K angle error values (delta theta) 1 ,Δθ 2 ,Δθ 3 …Δθ K )，Δθ K Representing the Kth angle error value, the following calculation needs to be performed on (Δθ 1 ,Δθ 2 ,Δθ 3 …Δθ K ) Normalization processing is performed to obtain K values (Deltaτ 1 ,Δτ 2 ,Δτ 3 …Δτ K )，Δτ K Represents delta theta K The processed values are normalized according to equation (4).
The step 7 comprises the following steps: and (3) calculating the distance error and the angle error of the two points according to the step (4) and the step (5), and respectively carrying out coherent analysis calculation on the distance error and the angle error. For example, the distance jitter is calculated using a coherent analysis method: selecting a scale N (N is a positive integer greater than 1), such as N is 5, and taking the distance error of 5 track points as a group to obtain a 1*5-dimensional vector X 1 ＝(Δρ 1 ,Δρ 2 ,Δρ 3 ,Δρ 4 ,Δρ 5 ) Selecting 5 consecutive groups to obtain a 5-order matrixAnd solving a covariance matrix E of the matrix, solving a eigenvalue of the covariance matrix E, and obtaining a coherence coefficient according to a coherence coefficient calculation formula.
Obtaining an error matrix D of each point, and obtaining a coherence coefficient according to the matrix D, wherein the method specifically comprises the following steps:
step 7-1: for an m n-dimensional matrix D, the matrix D consists of distance errors or angle errors of successive track points. Solving an n-dimensional covariance matrix B of the model;
step 7-2: eigenvalue λ of covariance matrix B 1 、λ 2 …λ n ，λ n Representing an nth eigenvalue;
step 7-3: the coherence coefficient k is calculated according to the following formula:
wherein lambda is max Lambda is lambda 1 、λ 2 …λ n Maximum value of (2); the larger the k value, the more dissimilar the data;
and 7-4, respectively carrying out coherent analysis on the track distance error and the track angle error.
In step 7-4, the coherent analysis of the track distance error specifically includes the following steps:
step a1, calculating a multi-order matrix F of track distance error change 1 ：
Wherein Δζ N The distance error of the test radar and the standard radar is normalized, K represents the total number of selected track points, and N represents the scale;
step a2, selecting a window with the size of N multiplied by N for coherent analysis, wherein the selected window matrix is D 1 ，D 1 Is a slave matrix F 1 A matrix of N consecutive columns truncated:
wherein X is N Represents D 1 Matrix data for each column of the matrix.
The matrix D is found according to the following formula 1 Covariance matrix E of (2) 1 ：
Therein cov (X) i ,X j )＝E[(X i -E(X i ))(X j -E(X j ))]，1≤i，j≤n；cov(X i ,X j ) Representative vector X i ,X j Is a cooperative variance value of (1). Calculating a eigenvalue of a matrix E, and calculating a coherence coefficient lambda according to a formula (5);
step a3, right shifting the window matrix by one lattice, obtaining the coherence coefficient of the current window, and sequentially calculating the coherence coefficient of the new window matrix after right shifting until the window reaches the rightmost end of the matrix;
and a4, connecting adjacent coherence coefficients to obtain a distance error change coherence coefficient curve.
In step 7-4, the coherent analysis of the track angle error specifically includes the following steps:
step b1, calculating a multi-order matrix F2 of the track angle error change:
step b2, selecting a window with the size of N multiplied by N for coherent analysis, wherein the selected window matrix is D 2 ，D 2 Is a slave matrix F 2 A matrix of N consecutive columns truncated:
wherein X is N Represents D 2 Matrix data for each column of the matrix.
Solving a matrix D according to a formula (6) 2 Covariance matrix E of (2) 2 Solving a matrix E 2 Calculating a coherence coefficient lambda according to formula (5);
step b3, right shifting the window matrix by one lattice, obtaining the coherence coefficient of the current window, and sequentially calculating the coherence coefficient of the new window matrix after right shifting until the window reaches the rightmost end of the matrix;
and b4, connecting adjacent coherence coefficients to obtain an angle error change coherence coefficient curve.
The beneficial effects are that: the invention has the following technical effects:
1. the data compensation and time alignment criteria are considered, enhancing the integrity and usability of the data, and increasing the smoothness and continuity of the final coherence coefficient curve.
2. Track jitter is evaluated more comprehensively from two directions of distance and angle.
3. A coherent analysis method is used in the process of evaluating jitter, and a mode of a multi-scale window matrix is designed, so that the robustness and noise immunity of the result are enhanced.
4. The method of the window matrix is adopted, the framing thought of signal processing is used, and partial overlapping areas exist between the former window matrix and the latter window matrix, so that the window matrix can be smoothly transited in the moving process.
Drawings
The foregoing and/or other advantages of the invention will become more apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings and detailed description.
Fig. 1 is a schematic diagram of distance and angle error calculation.
Fig. 2 is a schematic diagram of a multi-scale window matrix coherence analysis.
Fig. 3 is a schematic diagram of the error coherence coefficient variation curve.
FIG. 4 is a flowchart illustration of a track random jitter estimation procedure.
Detailed Description
As shown in fig. 4, the invention provides a radar track random jitter evaluation method, which comprises the following steps:
and 1, outlier rejection. The occurrence of the radar scan deviates significantly from the actual situation data. For example track point a in two cycles of the same target scanned by an existing radar 1 、A 2 . Track point A 1 Is of the speed of (1)The degree is 250m/s, and the track point A 2 Is 800m/s, A for a civil aircraft 2 The speed of the point is obviously beyond the normal range, and the point is removed.
And 2, data compensation. After the first step, the following situation may occur that the radar under test has the existing track point A 1 、A 2 、A 3 After outlier rejection, the track point A is left 1 、A 3 To avoid different time scale effects, it is therefore necessary to use a linear differential method to compensate for a data point instead of point a 2 。
Assuming a radar scan period of 4s, the existing track point A 1 (-4800m,2000m,250m/s,π/2)、A 3 (-3000, 2000,240m/s, pi/2), then the position of track point A2 (x 2 ,y 2 ) The method comprises the following steps:
and 3, time alignment. The measured radar A and the standard radar B are respectively (x) A ,y A )、(x B ,y B ) The speed, angle and time are respectively (v) A ,c A ,t A )、(v B ,c B ,t B ). Because the reporting time of the two radars is not necessarily uniform, time alignment operation is required for data points in similar time. Because the time difference between the two radars is short and less than or equal to the minimum scanning period of the two radars, the time alignment operation is realized by adopting a linear interpolation method.
Let the target point detected by the detected radar A be A 1 (-4800 m,2000 m), speed, angle, time (250 m/s, pi/2,123456 (10 ms)); the target position detected by the standard radar B is B 1 Time t B 123445 (10 ms), the linear interpolation gives point a 'at the same time as point B1' 1 Point A' 1 The position of (X 'is' A ,y’ A )：
And 4, converting coordinates. The measured radar A and the standard radar B are respectively (x) A ,y A )、(x B ,y B ). The coordinates of the radar a are (x RA ,y RA ) It is necessary to combine (x A ,y A )、(x B ,y B ) Conversion to (x) RA ,y RA ) In a polar coordinate system which is a pole, a (ρ A ,θ A ),(ρ B ,θ B )。
Let the target point detected by the detected radar A be A 1 (-4827.5 m,2000 m), the target position detected by standard radar B is B 1 (-4900 m,190 m), the coordinates of the radar A to be measured are (0, 0). The A is obtained after the conversion of the polar coordinate conversion formula (3) 1 Polar coordinates (5225.4,2.749), B 1 The polar coordinates of the points are (5255.5,2.772).
And 5, calculating the distance error. After coordinate conversion, the positions of the targets detected by the detected radar A and the standard radar B are respectively (ρ) A ,θ A ),(ρ B ,θ B ) The difference in the two target-to-pole distances is calculated. Assuming that the target track has K points in total, K distance error values (Δρ) are obtained 1 ,Δρ 2 ,Δρ 3 …Δρ K )。
And 6, calculating an angle error. After coordinate conversion, the positions of the targets detected by the detected radar A and the standard radar B are respectively (ρ) A ,θ A ),(ρ B ,θ B ) The difference between the two target polar angles is calculated. Assuming that the target track has K points in total, K are obtainedAngle error value (delta theta) 1 ,Δθ 2 ,Δθ 3 …Δθ K )。
Step 5 and step 6 calculate distance and angle error data, as shown in FIG. 1, it can be seen that the target positions measured in two periods for the same target measured radar A and standard radar B are respectively A 1 (ρ A1 ,θ A1 )、A 2 (ρ A2 ,θ A2 ) And B 1 (ρ B1 ,θ B1 )、B 2 (ρ B2 ,θ B2 )，A 1 、A 2 For locations that have undergone prior data processing.
For example, existing A 1 ，A 2 ，A 3 ，A 4 ，A 5 Five sets of error data were obtained from the error calculations for the five test track points (-30.1, -0.023), (-42.1, -0.02), (-26.5, -0.025), (-32, -0.02), (-40, -0.022). And respectively carrying out normalization processing on the distance error and the angle error according to a formula 4 to obtain: (0.769,0.4), (0,1), (1,0), (0.647,1), (0.135,0.4).
And 7, multi-scale coherent analysis. And calculating according to the step 4 and the step 5 to obtain the distance error and the angle error of the two points. And respectively carrying out coherent analysis calculation on the distance error and the angle error.
Assuming that the window length n=3, the distance error is (a 1 ,a 2 ,a 3 ,…a K ) Will (a) 1 ,a 2 ,a 3 ) Is transposed as the first column of the matrix, and then shifted right by one data point (a 2 ,a 3 ,a 4 ) And so on until moving to the (K-2) th point, to obtain (a) K-2 ,a K-1 ,a K ) The transposed matrix is used as the K-2 column of the matrix, and the N× (K-N+1) order matrix is finally formed, as shown in FIG. 2.
During coherent analysis, selecting a window with the size of N multiplied by N, performing coherent analysis calculation according to a formula 5 and a formula 6 from the first column of the matrix to obtain a first coherent coefficient, then moving the window to the right to obtain a second window matrix until the window moves to the right end of the matrix, representing the window matrix 1 and the window matrix 2 to the right end of the matrix in fig. 2, respectively solving covariance matrix 1, covariance matrix 2 and the like for the window matrix, and then solving eigenvalues of the covariance matrix according to the formula 5.
For matrices, e.g.
Obtaining covariance matrix according to formula 6
Obtaining E A The characteristic values of (2) are: 1,1,1
According to equation 5 there is k=1-1/(1+1+1) =0.67
In the present invention, the window matrix is selected to have two dimensions, n=3 or 5. Tests are carried out according to different radar scanning periods and the sizes of different window scales, and the effect of evaluating the track random jitter is best when the window size is set to be 3 or 5.
And 8, drawing a jitter curve. And (3) right-shifting the window matrix by one track point to obtain a new matrix overlapped with ((N-1)/N), and re-obtaining the coherence coefficient according to the method of the step (7). The window continues to move right, so that the coherence coefficient is obtained, and adjacent coherence coefficients are connected to obtain a coherence coefficient curve. As shown in fig. 3, the distance error coherence analysis is performed on the test track by using two windows with n=3 and n=5, so as to obtain two error coherence coefficient curves, and it can be seen from the two error coherence coefficient curves that the random jitter analysis of the test track by using the two windows with two scales basically accords with the random deviation degree of the test track and the standard track.
The invention provides a radar track random jitter evaluation method, and the method and the way for realizing the technical scheme are numerous, the above is only the preferred embodiment of the invention, and it should be pointed out that a plurality of improvements and modifications can be made to the person skilled in the art without departing from the principle of the invention, and the improvements and modifications are also considered as the protection scope of the invention. The components not explicitly described in this embodiment can be implemented by using the prior art.
Claims (5)
1. The radar track random jitter evaluation method is characterized by comprising the following steps of:
step 1, eliminating wild values;
step 2, data compensation;
step 3, performing time alignment;
step 4, carrying out coordinate conversion;
step 5, calculating a distance error;
step 6, calculating an angle error;
step 7, performing multi-scale coherent analysis;
step 8, drawing a jitter curve;
wherein, step 5 includes: setting up K points in total of the target track to obtain K distance error values (Δρ) 1 ,Δρ 2 ,Δρ 3 …Δρ K )，Δρ K Representing a kth distance error value; pair (Deltaρ) 1 ,Δρ 2 ,Δρ 3 …Δρ K ) Normalization processing is carried out to obtain K values (delta zeta) 1 ,Δξ 2 ,Δξ 3 …Δξ K )：
Wherein i=1, 2,3 … K, Δζ K Representing Deltaρ K Normalizing the processed value;
the step 6 comprises the following steps: setting up K points in total of the target track to obtain K angle error values (delta theta) 1 ,Δθ 2 ,Δθ 3 …Δθ K )，Δθ K Represents the K-th angle error value, for (delta theta) 1 ,Δθ 2 ,Δθ 3 …Δθ K ) Normalization processing is performed to obtain K values (Deltaτ 1 ,Δτ 2 ,Δτ 3 …Δτ K )，Δτ K Represents delta theta K Normalizing the processed value according to formula (4);
the step 7 comprises the following steps: according to the step 5 and the step 6, calculating to obtain the distance error and the angle error of two points, obtaining an error matrix D of each point, and obtaining a coherence coefficient according to the matrix D, wherein the method specifically comprises the following steps:
step 7-1: for an m multiplied by n dimensional matrix D, solving an n dimensional covariance matrix B thereof;
step 7-2: eigenvalue λ of covariance matrix B 1 、λ 2 …λ n ，λ n Representing an nth eigenvalue;
step 7-3: the coherence coefficient k is calculated according to the following formula:
wherein lambda is max Lambda is lambda 1 、λ 2 …λ n Maximum value of (2);
step 7-4, respectively carrying out coherent analysis on the track distance error and the track angle error;
in step 7-4, the coherent analysis of the track distance error specifically includes the following steps:
step a1, calculating a multi-order matrix F of track distance error change 1 ：
Wherein ΔζN represents the normalized value of the distance error between the test radar and the standard radar, K represents the total number of selected track points, and N represents the scale;
step a2, selecting a window with the size of N multiplied by N for coherent analysis, wherein the selected window matrix is D 1 ，D 1 Is a slave matrix F 1 A matrix of N consecutive columns truncated:
wherein X is N Represents D 1 Matrix data for each column of the matrix;
the matrix D is found according to the following formula 1 Covariance matrix E of (2) 1 ：
Therein cov (X) i ,X j )＝E[(X i -E(X i ))(X j -E(X j ))]，1≤i，j≤n；cov(X i ,X j ) Representative vector X i ,X j Is a covariance value of (1); calculating a eigenvalue of a matrix E, and calculating a coherence coefficient lambda according to a formula (5);
step a3, right shifting the window matrix by one lattice, obtaining the coherence coefficient of the current window, and sequentially calculating the coherence coefficient of the new window matrix after right shifting until the window reaches the rightmost end of the matrix;
step a4, connecting adjacent coherence coefficients to obtain a distance error change coherence coefficient curve;
in step 7-4, the coherent analysis of the track angle error specifically includes the following steps:
step b1, calculating a multi-order matrix F of track angle error change 2 ：
Step b2, selecting a window with the size of N multiplied by N for coherent analysis, wherein the selected window matrix is D 2 ，D 2 Is a slave matrix F 2 A matrix of N consecutive columns truncated:
wherein X is N Represents D 2 Matrix data for each column of the matrix;
solving a matrix D according to a formula (6) 2 Covariance matrix E of (2) 2 Moment determinationArray E 2 Calculating a coherence coefficient lambda according to formula (5);
step b3, right shifting the window matrix by one lattice, obtaining the coherence coefficient of the current window, and sequentially calculating the coherence coefficient of the new window matrix after right shifting until the window reaches the rightmost end of the matrix;
and b4, connecting adjacent coherence coefficients to obtain an angle error change coherence coefficient curve.
2. The method according to claim 1, wherein in step 1, a maximum speed of a civil aircraft is set to v (m/s), a radar scanning period is set to T(s), a distance between two consecutive detection points should be no greater than v×t (m), a random error fixed fault tolerance is set to 20%, a distance between two adjacent points should be less than v×t×1.2 (m), and points which do not satisfy the above conditions are eliminated.
3. The method according to claim 2, wherein step 2 comprises: setting three existing track points A of the radar to be tested 1 、A 2 、A 3 After the outlier is removed in the step 1, the track point A is left 1 、A 3 The radar scan period is known as T, at which point trace A 1 And point A 3 The time difference between them becomes 2T, and track point A is set 1 The position is (x) 1 ,y 1 ,v 1 ,ω 1 ) Track point A 3 The position is (x) 3 ,y 3 ,v 2 ,ω 2 ) Wherein (x) 1 ,y 1 ) Representing track point A 1 Two-dimensional coordinate data, v 1 Representing track point A 1 Speed, omega 1 Representing track point A 1 Heading of (x) 3 ,y 3 ) Representing track point A 3 Two-dimensional coordinate data, v 2 Representing track point A 1 Speed, omega 2 Representing track point A 3 Adopts a linear differential method to compensate a data point A2 to replace a track point A 2 Then the position of A2 (x 2 ,y 2 ) The method comprises the following steps:
4. a method according to claim 3, wherein step 3 comprises: setting the position of a target point detected by a detected radar A as A 1 The coordinates are (x A ,y A ) The speed, angle and time are v respectively A ,c A ,t A The method comprises the steps of carrying out a first treatment on the surface of the The target position detected by the standard radar B is B 1 The coordinates are (x B ,y B ) The speed, angle and time are v respectively B ,c B ,t B Obtaining a point B after linear interpolation 1 Point A 'at the same time' 1 Point A' 1 The position of (x' A ,y’ A ) The calculation formula is as follows:
。
5. the method of claim 4, wherein step 4 comprises: the position (x) of the radar a to be measured RA ,y RA ) A pole as polar coordinates; the measured radar A and the standard radar B are respectively (x) A ,y A )、(x B ,y B ) It is necessary to combine (x A ,y A )、(x B ,y B ) Conversion to (x) RA ,y RA ) In a polar coordinate system which is a pole, a (ρ A ,θ A ),(ρ B ,θ B ) Wherein ρ is A Representing the distance, theta, of the polar coordinates of the radar a being measured A An angle ρ representing the polar A coordinate of the radar under test B Distance, θ, representing the B polar coordinates of a standard radar B Angle representing standard radar B polar coordinates:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011209612.3A CN112255612B (en) | 2020-11-03 | 2020-11-03 | Radar track random jitter evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011209612.3A CN112255612B (en) | 2020-11-03 | 2020-11-03 | Radar track random jitter evaluation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112255612A CN112255612A (en) | 2021-01-22 |
| CN112255612B true CN112255612B (en) | 2024-02-13 |
Family
ID=74268583
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011209612.3A Active CN112255612B (en) | 2020-11-03 | 2020-11-03 | Radar track random jitter evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112255612B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113836123A (en) * | 2021-07-22 | 2021-12-24 | 南京沃旭通讯科技有限公司 | Track cleaning method based on distance and angle |
| CN113838313B (en) * | 2021-11-29 | 2022-02-18 | 中国民用航空总局第二研究所 | Obstacle identification method for course beacon channel clearance jitter |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000284049A (en) * | 1999-03-31 | 2000-10-13 | Mitsubishi Electric Corp | Radar integration tracking system |
| CN108896973A (en) * | 2018-07-13 | 2018-11-27 | 北京无线电测量研究所 | Scaling method, point the mark method for evaluating quality, storage medium of radar data |
| CN110990756A (en) * | 2019-12-03 | 2020-04-10 | 中国电子科技集团公司第二十八研究所 | Aerial target track quality assessment method based on extension type layer-by-layer analysis |
| CN111366900A (en) * | 2020-02-18 | 2020-07-03 | 上海机电工程研究所 | Tracking radar track quality evaluation method, system and medium based on residual error statistics |
| CN111477036A (en) * | 2020-04-08 | 2020-07-31 | 中国电子科技集团公司第二十八研究所 | Method for detecting aircraft height abnormity of air traffic control automation system |
| CN111680870A (en) * | 2020-04-29 | 2020-09-18 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Comprehensive evaluation method for target motion trajectory quality |
| CN111736172A (en) * | 2020-08-24 | 2020-10-02 | 中国人民解放军国防科技大学 | Air target detection method based on atmospheric disturbance coherent laser detection |
-
2020
- 2020-11-03 CN CN202011209612.3A patent/CN112255612B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000284049A (en) * | 1999-03-31 | 2000-10-13 | Mitsubishi Electric Corp | Radar integration tracking system |
| CN108896973A (en) * | 2018-07-13 | 2018-11-27 | 北京无线电测量研究所 | Scaling method, point the mark method for evaluating quality, storage medium of radar data |
| CN110990756A (en) * | 2019-12-03 | 2020-04-10 | 中国电子科技集团公司第二十八研究所 | Aerial target track quality assessment method based on extension type layer-by-layer analysis |
| CN111366900A (en) * | 2020-02-18 | 2020-07-03 | 上海机电工程研究所 | Tracking radar track quality evaluation method, system and medium based on residual error statistics |
| CN111477036A (en) * | 2020-04-08 | 2020-07-31 | 中国电子科技集团公司第二十八研究所 | Method for detecting aircraft height abnormity of air traffic control automation system |
| CN111680870A (en) * | 2020-04-29 | 2020-09-18 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Comprehensive evaluation method for target motion trajectory quality |
| CN111736172A (en) * | 2020-08-24 | 2020-10-02 | 中国人民解放军国防科技大学 | Air target detection method based on atmospheric disturbance coherent laser detection |
Non-Patent Citations (1)
| Title |
|---|
| 飞行目标的抖动及雷达散射截面计算;李民权;《合肥工业大学（自然科学版）》;第26卷(第5期);1021-1024 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112255612A (en) | 2021-01-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112255612B (en) | Radar track random jitter evaluation method | |
| CN110045342B (en) | Method for evaluating effectiveness of radar relative system error estimation | |
| CN108319570B (en) | Asynchronous multi-sensor space-time deviation joint estimation and compensation method and device | |
| JP2009002794A (en) | Apparatus and method for wake integration and program | |
| CN110211178B (en) | Pointer instrument identification method using projection calculation | |
| CN109856616B (en) | Method for correcting error of radar positioning relative system | |
| CN111680870A (en) | Comprehensive evaluation method for target motion trajectory quality | |
| CN112229406A (en) | Redundancy guide full-automatic landing information fusion method and system | |
| CN110555398A (en) | Fault diagnosis method for determining first arrival moment of fault based on optimal filtering smoothness | |
| CN109856623B (en) | Target state estimation method for multi-radar linear flight path line | |
| CN109856622B (en) | Single-radar linear track target state estimation method under constraint condition | |
| CN109781116B (en) | Error self-calibration fusion positioning method based on active sensor mean value iteration | |
| CN113238208B (en) | Method for calculating forward acoustic scattering Doppler frequency shift of moving target in irregular track water | |
| CN109117720B (en) | Pointer instrument reading identification method based on machine vision | |
| EP2929366B1 (en) | Improvements in and relating to course and/or speed data | |
| RU2721623C1 (en) | Method for determining the instantaneous position of the drift point of an unmanned aerial vehicle from information of an angle measurement channel | |
| CN109856619B (en) | Radar direction finding relative system error correction method | |
| CN107271974B (en) | Space-time error solving method based on stable angular points | |
| CN113359122B (en) | Pulse radar measurement data rationality checking method and device | |
| CN109856624B (en) | Target state estimation method for single-radar linear flight path line | |
| CN111693962B (en) | Target motion model estimation method based on cross inspection | |
| CN110767322B (en) | Ocean floating platform hot spot stress calculation method based on response surface model | |
| CN113933798A (en) | Global sensor system error partition registration algorithm based on similarity principle | |
| CN106125061B (en) | A kind of Targets Dots fusion method of the system deviation based on Gaussian Profile | |
| CN112198504B (en) | Fusion filtering method for interleaving of active and passive observation features |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |