CN105301567A - Method for removing false positioning points based on speed consistency - Google Patents

Method for removing false positioning points based on speed consistency Download PDF

Info

Publication number
CN105301567A
CN105301567A CN201510670098.6A CN201510670098A CN105301567A CN 105301567 A CN105301567 A CN 105301567A CN 201510670098 A CN201510670098 A CN 201510670098A CN 105301567 A CN105301567 A CN 105301567A
Authority
CN
China
Prior art keywords
anchor point
target
point
doppler frequency
false bearing
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.)
Granted
Application number
CN201510670098.6A
Other languages
Chinese (zh)
Other versions
CN105301567B (en
Inventor
黄晓涛
刘文彦
朱家华
范崇祎
雷鹏正
周智敏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
National University of Defense Technology
Original Assignee
National University of Defense Technology
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by National University of Defense Technology filed Critical National University of Defense Technology
Priority to CN201510670098.6A priority Critical patent/CN105301567B/en
Publication of CN105301567A publication Critical patent/CN105301567A/en
Application granted granted Critical
Publication of CN105301567B publication Critical patent/CN105301567B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

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

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 method for removing false positioning points based on speed consistency. The technical scheme is that targets in a detecting scene are determined according the number of peak values in echoes of a multi-static radar, and as for each target, the following steps are carried out: step one, preliminarily removing false positioning points by using a distance criterion method; step two, as for each positioning point, the Doppler frequency from each receiving station to the positioning point is observed, and N Doppler frequency combinations are acquired by pair-wise combination; step three, the target speed of each positioning point is estimated by using different Doppler frequency combinations; step four, two types of speed consistency test statistics are calculated as for each positioning point; and step five, whether each positioning point is a false positioning point or not is judged by using the speed consistency test statistics. The method provided by the invention can recognize and remove the false positioning points more accurately.

Description

A kind of point of the false bearing based on rate uniformity elimination method
Technical field
The invention belongs to radar target field of locating technology, relate to a kind of false bearing based on rate uniformity point elimination method, the observation information that the method makes full use of multistatic radar particularly doppler information achieves ghost recognition and rejecting more accurately.
Background technology
Under multipath, false-alarm, non line of sight or other disturbed conditions, the position of target and the estimated value of speed significantly will depart from actual value, produce larger error of observation data, cause occurring false bearing point.Therefore, need to take certain measure identification and reject these false bearing points.Traditionally, mostly the elimination method of false bearing point is for many bases direction cross positioning, and needs that extra prior imformation is auxiliary could reject false bearing point.
Existing false bearing point elimination method mainly contains minimum distance method, maximum likelihood method, Lagrange relaxation method etc., but these method calculated amount are comparatively large, and in removing false bearing point process, the extra prior imformation of general needs is assisted, and is not suitable for real-time process.More method is adopted to be the method (hereinafter referred to as distance criterion method) utilizing distance criterion to reject false bearing point in real-time process, the target that the method first utilizes multistatic radar to obtain to the observed range sum of each cell site and receiving station (hereinafter referred to as Distance geometry, it should be noted that the concept of this Distance geometry refer to a cell site to a target therewith target to the Distance geometry of a receiving station, namely for the multistatic radar of M N number of receiving station of cell site, each target can observe M × N number of Distance geometry) carry out oval cross bearing, estimate all anchor points of target under this methodology position coordinates (concrete grammar flow process is see document Section 2.5: He Hongfei. the design and implimentation [D] of portable radar signal processor. master thesis, University of Electronic Science and Technology, 2009.).Then to the target localization point position coordinates of each estimation according to the anti-target of releasing of coordinate of receiving station and cell site to each receiving station and the Distance geometry to cell site, then calculate the anti-Distance geometry pushed away and corresponding observed range and difference, if these differences are greater than this threshold value of standard deviation of observational error, then think that this target localization point estimated is false bearing point and rejects.The advantage of the method is that its calculated amount is less, but it is not high to the recognition success rate of the false bearing point comparatively close with the position and speed of target.
Summary of the invention
For utilizing multistatic radar to reject false bearing point, improve the success ratio identifying false bearing point, the present invention proposes a kind of false bearing based on rate uniformity point elimination method on existing methods basis.The relatively existing method of the method has better effect.
The technical solution used in the present invention is, the rejecting of false bearing point is completed based on rate uniformity, it is characterized in that, first determine according to the peak number in the echo of multistatic radar the number detecting target in scene, and postpone according to the different time that each peak value has, (concrete grammar flow process is see document: YBar-Shalom.TrackingMethodsinaMultitargetEnvironment [J] .IEEETransactionsonAutomaticControl to utilize multidimensional apportion design to be separated each target, 1978,24 (4), 618-626.).Then to each target, comprise the following steps at any location moment k:
The first step, utilizes distance criterion method tentatively to reject false bearing point.
In order to reduce follow-up calculated amount, this step first obtain multistatic radar range-to-go and, then the distance criterion method in background technology is utilized to carry out oval cross bearing, and preliminary part false bearing point of rejecting wherein, obtain all anchor points (comprise true anchor point and false bearing point, represent with coordinate form) of target target under this methodology.
Second step, to each anchor point, observes each receiving station to the Doppler frequency of this anchor point, and combination of two obtains the combination of N number of Doppler frequency.
3rd step, uses the target velocity of the different each anchor points of Doppler frequency combinational estimation.
(concrete grammar flow process is see document: Wei Chongyu to utilize the target velocity of each anchor point of each Doppler frequency combinational estimation respectively, Xu is kind to drive, Wang Dongjin. multistatic radar maximum likelihood estimate target localization with test the speed [J]. applied science journal, 2000,18 (2): 117-121.), N number of target velocity estimated vector is obtained to each anchor point.
4th step, calculates two kinds of rate uniformity test statistics to each anchor point.
First, utilize N number of target velocity estimated vector of each anchor point to calculate the relative size of speed difference between two, be called velocity magnitude consistency check statistic;
Then, utilize N number of target velocity estimated vector of each anchor point to calculate the angle of friction speed, be called velocity reversal consistency check statistic.
5th step, whether each anchor point is false bearing point to utilize rate uniformity test statistics to judge.
Two kinds of rate uniformity test statistics are utilized to judge the confidence level of this anchor point to each anchor point.To the velocity magnitude calculated and orientation consistency test statistics, rule of thumb set two thresholdings respectively, if having any one to exceed respective setting thresholding in these two parameters, then think that the anchor point obtained is insincere, this anchor point is false bearing point, is rejected; Otherwise think that the anchor point obtained is credible, this anchor point is not false bearing point, is retained.
Through above-mentioned steps, just can locate arbitrarily the false bearing point that moment k judges each target more accurately, and reject.
Adopt the present invention can reach following technique effect:
The present invention can utilize rate uniformity to carry out identification and the rejecting of false bearing point.First invention of carrying utilizes distance criterion method to reject false bearing point to preliminary, obtains all anchor points of target target under this methodology, then utilizes the confidence level of rate uniformity statistic to these anchor points to judge.Judged by this profound level, more accurately can identify and reject false bearing point, comparing existing method and there is better effect.
Accompanying drawing explanation
Fig. 1 is realization flow figure of the present invention;
Fig. 2 is the simulation result utilizing the inventive method to carry out emulation experiment 1;
Fig. 3 is the simulation result utilizing the inventive method to carry out emulation experiment 2.
Embodiment
Fig. 1 is realization flow figure of the present invention.First determine according to the peak number in the echo of multistatic radar the number detecting target in scene, and postpone according to the different time that each peak value has, utilize multidimensional apportion design to be separated each target.Then to each target, comprise the following steps at any location moment k:
The first step, utilizes distance criterion method tentatively to reject false bearing point.
In order to reduce follow-up calculated amount, this step first obtain multistatic radar range-to-go and, then the distance criterion method in background technology is utilized to carry out oval cross bearing, and preliminary part false bearing point of rejecting wherein, obtain all anchor points (comprise true anchor point and false bearing point, represent with coordinate form) of target target under this methodology.
Second step, to each anchor point, observes each receiving station to the Doppler frequency of this anchor point, and combination of two obtains the combination of N number of Doppler frequency.
For convenience of description, suppose that multistatic radar has a cell site, three receiving stations make an explanation here.Concerning each anchor point in scene, the Doppler frequency that each receiving station observes to this anchor point is respectively D 1, D 2, D 3.Be D by the Doppler frequency combination of two of each anchor point 1and D 2, D 1and D 3, D 2and D 3three groups of data.More complicated many bases situation is processed in this approach similarly and carries out subsequent step.
3rd step, uses the target velocity of the different each anchor points of Doppler frequency combinational estimation.
Doppler frequency is utilized to combine D respectively 1and D 2, D 1and D 3, D 2and D 3estimate the target velocity of each anchor point, obtain three target velocity estimated vector v 12, v 13, v 23.
4th step, calculates two kinds of rate uniformity test statistics to each anchor point.
First, utilize 3 of each anchor point target velocity estimated vectors to calculate the relative size (without unit) of speed difference between two, be called velocity magnitude consistency check statistic:
F 1 = | ( v 12 - v 13 ) | 2 min ( | v 12 | 2 , | v 13 | 2 ) , F 2 = | ( v 12 - v 23 ) | 2 min ( | v 12 | 2 , | v 23 | 2 ) , F 3 = | ( v 23 - v 13 ) | 2 min ( | v 23 | 2 , | v 13 | 2 ) - - - ( 1 )
Wherein, || 2represent 2 norms calculating this vector, min () represents the minimum value of getting in set.
Then, utilize 3 target velocity estimated vectors of each anchor point to calculate the angle (unit is degree) of friction speed, be called velocity reversal consistency check statistic:
A 1 = a cos ( ( v 12 * v 13 ) | v 12 | 2 · | v 13 | 2 ) , A 2 = a cos ( ( v 12 * v 23 ) | v 12 | 2 · | v 23 | 2 ) , A 3 = a cos ( ( v 23 * v 13 ) | v 23 | 2 · | v 13 | 2 ) - - - ( 2 )
Wherein, acos represents inverse cosine function, and * represents the dot product of vector, represents being multiplied in mathematical meaning.
5th step, whether each anchor point is false bearing point to utilize rate uniformity test statistics to judge.
Two kinds of rate uniformity test statistics are utilized to judge the confidence level of this anchor point to each anchor point.To the velocity magnitude calculated and orientation consistency test statistics, can pass through to judge whether following hypothesis becomes Rob Roy to judge the confidence level of anchor point:
max ( F 1 , F 2 , F 3 ) ≤ F 0 max ( A 1 , A 2 , A 3 ) ≤ A 0 - - - ( 3 )
Wherein, thresholding F 0and A 0the mode that can be set by experience is acquired (for personnel's moving target, setting F 0be no more than 2, A 0be no more than 15 degree).If above formula is false, then think that the anchor point obtained is insincere, this anchor point is false bearing point, is rejected; Otherwise think that the anchor point obtained is credible, this anchor point is not false bearing point, is retained.
Through above-mentioned steps, just can locate arbitrarily the false bearing point that moment k judges each target more accurately, and reject.
Fig. 2 is the simulation result utilizing the inventive method to carry out emulation experiment 1.First simulating scenes is done following setting: T position coordinates in cell site is (0,0), four receiving station R 1~ R 4position coordinates is (-25,43), (50,0), (0,84), (75,43), the position coordinates of a target is (50,50), position coordinates unit is m, speed is (3 ,-4), and speed unit is m/s, in addition a position and speed is also had all at the chaff interference of change, for the manufacture of false bearing point.Wherein R 1, R 3and R 4the Distance geometry of receiving station and Doppler frequency observation data are all from target, and R 2the Distance geometry of receiving station and Doppler frequency observation data are from chaff interference, and the Doppler frequency observation data of this receiving station and its excess-three receiving station forms three wrong Doppler's observing frequencies and combines to manufacture false bearing point.In Fig. 2, the horizontal ordinate of each subgraph represents that relative target velocity reversal angle, chaff interference velocity reversal angle is by the difference be rotated counterclockwise, in order to be characterized in the change size on velocity reversal, and identical with the velocity reversal of target when horizontal ordinate is 0; Chaff interference velocity magnitude is all identical with target velocity size in any angle.Ordinate represents ghost recognition success ratio.In each subgraph, the implication of legend is as follows: circular lines expression utilizes distance criterion method to the recognition success rate (being designated as in figure " distance criterion ") of false bearing point, and now the standard deviation threshold value of observational error is decided to be 2m; Lineae trapezoidea represents the recognition success rate (being designated as in figure " velocity magnitude consistance ") utilizing velocity magnitude consistency check statistic to false bearing point, and now threshold value is decided to be 2; Square line represents the recognition success rate (being designated as in figure " velocity reversal consistance ") utilizing velocity reversal consistency check statistic to false bearing point, and now threshold value is decided to be 15 degree.In Fig. 2, all emulation all uses above-mentioned thresholding, and in each subgraph, only chaff interference position coordinates is different.10000 Monte Carlo simulations are carried out to the velocity reversal angular difference value of each chaff interference and target and adds up recognition success rate.In Fig. 2 (a), target and chaff interference are all positioned at (50,50), now utilize the identification of distance criterion method to lose efficacy, very low to the recognition success rate of false bearing point; Utilize the identification of two kinds of rate uniformity test statistics then comparatively effective, when the velocity reversal angular difference value of chaff interference and target is 30 ~ 220 degree, recognition success rate reaches 100%.In Fig. 2 (b), chaff interference is positioned at (46,46), and distance objective is comparatively far away, now just false bearing point can be rejected based on distance criterion method, utilize the identification of rate uniformity test statistics also to reach same effect.In Fig. 2 (c), chaff interference is positioned at (48,48), and at this moment distance criterion method can not identify false bearing point preferably, and relative to utilizing, the recognition success rate of rate uniformity test statistics is lower.In Fig. 2 (d), chaff interference is positioned at (52,52), and result and Fig. 2 (c) of this figure are similar.
Fig. 3 is the simulation result utilizing the inventive method to carry out emulation experiment 2.Other scene setting in Fig. 3 and Fig. 2 are identical with threshold settings, but are thick-and-thin unlike chaff interference velocity reversal, identical with the direction of target velocity; Chaff interference velocity magnitude gets different amplification values at any location moment k respectively relative to target velocity size.In Fig. 3, the horizontal ordinate of each subgraph represents the amplification value of chaff interference velocity magnitude relative to target velocity size, be called speed amplitude amplification, as-0.5 represents that chaff interference speed is 1-0.5=0.5 times of target velocity, 1 represents that chaff interference speed is 1+1=2 times of target velocity.Ordinate represents ghost recognition success ratio.In each subgraph, the implication of legend is identical with Fig. 2 with expression.10000 Monte Carlo simulation statistics recognition success rates are carried out to often kind of speed amplitude amplification.In Fig. 3 (a), target and chaff interference are all positioned at (50,50), now utilize the identification of distance criterion method to lose efficacy, very low to the recognition success rate of false bearing point; When utilizing the identification of rate uniformity test statistics, be that near 0, effect is poor in speed amplitude amplification, because now the position of chaff interference and speed and target are all closely.In Fig. 3 (b), chaff interference is positioned at (46,46), and distance objective is comparatively far away, now just false bearing point can be rejected based on distance criterion method, utilize the identification of rate uniformity test statistics also to reach same effect.Fig. 3 (c) and 3 (d) middle chaff interference lay respectively at (48,48) and (52,52), at this moment distance criterion method can not identify false bearing point preferably, and relative to utilizing, the recognition success rate of rate uniformity test statistics is lower.But the chaff interference presented due to these two subgraphs all has certain difference with target on position and speed, therefore utilizing distance criterion method and utilize the recognition success rate of rate uniformity test statistics all to improve relative to Fig. 3 (a), is particularly near 0 in speed amplitude amplification.

Claims (1)

1. the point of the false bearing based on a rate uniformity elimination method, it is characterized in that, first determine according to the peak number in the echo of multistatic radar the number detecting target in scene, and postpone according to the different time of each peak value, multidimensional apportion design is utilized to be separated each target, then to each target, k carries out following steps at any time:
The first step, utilizes distance criterion method tentatively to reject false bearing point:
According to multistatic radar range-to-go and, utilize distance criterion method to carry out oval cross bearing, reject false bearing point, obtain the anchor point that target is preliminary;
Second step, to each anchor point that the first step obtains, observes each receiving station to the Doppler frequency of this anchor point, and combination of two obtains the combination of N number of Doppler frequency:
3rd step, uses the target velocity of the different each anchor points of Doppler frequency combinational estimation:
Utilize the target velocity of each anchor point of each Doppler frequency combinational estimation respectively;
4th step, calculates two kinds of rate uniformity test statistics to each anchor point:
First, utilize N number of target velocity estimated vector of each anchor point to calculate the relative size of speed difference between two, be called velocity magnitude consistency check statistic;
Then, utilize N number of target velocity estimated vector of each anchor point to calculate the angle of friction speed, be called velocity reversal consistency check statistic:
5th step, whether each anchor point is false bearing point to utilize rate uniformity test statistics to judge:
Two kinds of rate uniformity test statistics are utilized to judge the confidence level of this anchor point to each anchor point; To the velocity magnitude consistency check statistic calculated and orientation consistency test statistics, rule of thumb set two thresholdings respectively, if have any one to exceed respective setting thresholding in these two parameters, then think that the anchor point obtained is insincere, this anchor point is false bearing point, is rejected; Otherwise think that the anchor point obtained is credible, this anchor point is not false bearing point, is retained.
CN201510670098.6A 2015-10-13 2015-10-13 A kind of false bearing point elimination method based on rate uniformity Active CN105301567B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510670098.6A CN105301567B (en) 2015-10-13 2015-10-13 A kind of false bearing point elimination method based on rate uniformity

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510670098.6A CN105301567B (en) 2015-10-13 2015-10-13 A kind of false bearing point elimination method based on rate uniformity

Publications (2)

Publication Number Publication Date
CN105301567A true CN105301567A (en) 2016-02-03
CN105301567B CN105301567B (en) 2018-06-15

Family

ID=55199048

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510670098.6A Active CN105301567B (en) 2015-10-13 2015-10-13 A kind of false bearing point elimination method based on rate uniformity

Country Status (1)

Country Link
CN (1) CN105301567B (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08136652A (en) * 1994-11-07 1996-05-31 Toyota Motor Corp Device for detecting ground speed of vehicle
US20040012517A1 (en) * 2002-07-17 2004-01-22 Ramzi Abou-Jaoude Integrated multiple-up/down conversion radar test system
CN101738606A (en) * 2008-11-21 2010-06-16 清华大学 Method for detecting coherent integration of radar target based on generalized Doppler filter bank

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08136652A (en) * 1994-11-07 1996-05-31 Toyota Motor Corp Device for detecting ground speed of vehicle
US20040012517A1 (en) * 2002-07-17 2004-01-22 Ramzi Abou-Jaoude Integrated multiple-up/down conversion radar test system
CN101738606A (en) * 2008-11-21 2010-06-16 清华大学 Method for detecting coherent integration of radar target based on generalized Doppler filter bank

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
贺鸿飞: "便携式雷达信号处理机的设计与实现", 《万方学位论文》 *
郭晓丽: "基于位置服务的移动对象隐私保护技术研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *

Also Published As

Publication number Publication date
CN105301567B (en) 2018-06-15

Similar Documents

Publication Publication Date Title
CN104215951B (en) System and method for detecting low-speed small target under sea cluster background
US9562965B2 (en) Two-stage filtering based method for multiple target tracking
KR101628154B1 (en) Multiple target tracking method using received signal strengths
CN106383344B (en) Multistation Radar Moving Target detection method based on fusion criterion
CN103487801A (en) Method of radar for recognizing true and false warheads
CN111157943B (en) TOA-based sensor position error suppression method in asynchronous network
CN103592620B (en) Gao Zhongying signal solution location ambiguity method in Long baselines positioning using TDOA system
CN105425223A (en) Detection method of sparse distance extension radar target in generalized Pareto clutter
CN107124762A (en) A kind of wireless location method of efficient abatement non-market value
KR20150082973A (en) Method and apparatus for analysis of ionosphere observation signal using radar
CN105425206A (en) Steady least square positioning method in nonsynchronous wireless network
KR101280513B1 (en) Localization method based on gauss-netwon method using tdoa/fdoa, and localization apparatus using the same
CN103760544A (en) Scattering center extraction method and system for radar target
CN104155653B (en) SAR back projection imaging method based on feature distance subspace
Molnár et al. Development of an UWB based indoor positioning system
CN105301567A (en) Method for removing false positioning points based on speed consistency
JP6210845B2 (en) Target tracking device and target tracking method
CN104316905A (en) Self-adaptive kalman filtering method for processing flight time distance measurement data
CN104316929A (en) Power spectrum identification method and apparatus
Doğançay et al. Selective angle measurements for a 3D-AOA instrumental variable TMA algorithm
Chen et al. Passive localization for emitter with unknown LFM signal based on signal parameter estimation
RU2572079C2 (en) Method and system for combined processing of range and velocity measurements for multirange all-round looking radar system
CN104237880B (en) Structure changes Joint Probabilistic Data Association formation target tracking method
Romeo et al. Data fusion with ML-PMHT for very low SNR track detection in an OTHR
KR20180007827A (en) System and method for obtaining information of underwater target

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant