CN105353368A - Adaptive variable structure radar sea target tracking method based on policy decision - Google Patents
Adaptive variable structure radar sea target tracking method based on policy decision Download PDFInfo
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- CN105353368A CN105353368A CN201510758069.5A CN201510758069A CN105353368A CN 105353368 A CN105353368 A CN 105353368A CN 201510758069 A CN201510758069 A CN 201510758069A CN 105353368 A CN105353368 A CN 105353368A
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/66—Radar-tracking systems; Analogous systems
- G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
- G01S13/723—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar by using numerical data
-
- 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
Abstract
The present invention discloses an adaptive variable structure radar sea target tracking method based on policy decision. The method comprises the steps of receiving the target track point data output by a radar sensor by a network, using a certain data structure to store the track point data, forming a trend information map by analyzing the stored target track point data and target track data, carrying out association judgment on the current radar target track and target track point by using the trend information map, and adaptively changing the strcuture of the radar target tracking data processing according to a judgment result to realize the stable tracking of the target.
Description
Technical field
The present invention relates to a kind of adaptive variable structure radar based on policy determination to extra large method for tracking target.The method is at harbour, and the motion state of the complex condition targets such as rivers navigation channel is adjudicated, and follows the tracks of process structure according to court verdict adaptively changing, realize target tenacious tracking.
Background technology
From the eighties so far, the navigation channel transport handling capacity of China coast increases 5,000,000,000 tons by more than 300,000,000 tons, ships quantity sharply increases, and in order to more effectively supervise ship motion state, increasing radar equipment is deployed near harbour, harbour and navigation channel.Radar equipment can describe presence or absence and the position of target by electromagnetic mode, but realize implementing effectively to supervise and continue to follow the tracks of to target, process must be carried out by method for tracking target to all target informations detected of radar also to be managed, to realize following the tracks of the continuous reliable surveillance in supervision waters.
When carrying out target information processing and monitor waters situation management, due to heavy dense targets, phase mutual edge distance between target is usually less than radar resolution and radar stochastic error, and the state of Interconnected Fuzzy generally can continue the longer time, so the motion state at target and movement tendency must be taken into full account, carry out the associated allocation of targetpath and radar plot exactly, and use suitable model to go the current state of correct estimating target to reach the object to extra large target tenacious tracking.The present invention has taken into full account the many factors that may have influence on target tenacious tracking, overcomes the shortcoming that general data disposal route is attended to one thing and lose sight of another, enhances the practicality of method.
Summary of the invention
The object of the present invention is to provide a kind of adaptive variable structure radar based on policy determination to extra large method for tracking target.
The technical solution realizing the object of the invention is: the Targets Dots data exported by network reception radar sensor, and sets up some mark store data structure, and this data structure is divided into three-dimensional, is orientation, distance, time respectively.A mark is stored in corresponding data structure according to orientation, Distance geometry temporal information.By the method for already present targetpath according to position Dynamic Packet, the flight path target meeting packet positions thresholding being compiled is one group.The relative topological location matrix of the radar track in target close region is calculated by the group internal object number analyzing flight path grouping.Within each radar scanning cycle, the data structure that the result of being divided into groups by flight path stores with some mark associates, and by comparing the change closing on and put mark number in the radar scanning cycle, estimate the state (comprising clutter probability, Target Splitting probability etc.) of current period point mark.According to the estimation to current period point mark state, complete the screening of clutter point mark and the merging of split point mark.By the relative topological location matrix of radar track, complete current period and estimate that the some mark storage organization of process and the historical context point mark of flight path target and status information are picked out and be stored together, generate the situation information figure of single goal flight path.
According to situation information figure, judged by the state of decision function to current goal, and export the estimation of some track association strategy that current goal may exist and target travel trend.Decision function is defined as: input data are the situation information figure of single goal flight path, utilizing the relative topological location matrix of radar track confirmation target current is monotrack state or multiple target tracking state, if single goal state, then by percentage speed variation current for target, turning rate, relating dot mark type generates the current state vector of target as three dimensions, several typicalness (the linear uniform motion generated utilizing off-line data in this state vector and decision function, linear accelerating moves, straight line retarded motion, pass through still life motion and circular motion etc.) state vector do correlation calculations, corresponding dbjective state is selected according to the result of correlation calculations.If first multiple goal state then generates the prediction topology location matrix of target and adjacent objects according to target and the current course of adjacent objects, the speed of a ship or plane, complete the state correlation calculations of target.The last output packet according to the judgement of dbjective state generation strategy is containing the estimation of the prediction topology location matrix of target and adjacent objects, some track association strategy that current goal may exist and target travel trend.
According to the some track association strategy that decision function exports, change target following structure, the association ripple door size that design object is current and pattern, in the hope of can the position of the correctly current existence of coverage goal.After obtaining radar plot by association ripple door, according to the topology location matrix of target and adjacent objects, carry out the distribution of impact point track association.After completing associated allocation, according to the estimation of target travel trend, determine the motion model of current goal, and according to the velocity information in targetpath data, change the data updating rate of target following, to realize the tracking to extra large target.
Compared with prior art, its remarkable advantage is in the present invention:
The present invention on the basis of existing technology, the radar plot data received and targetpath data are classified, utilize the situation information figure of the data construct single goal of classification, by the comparison of target situation information figure and reference sample, complete the estimation of target travel trend, determine the associating policy of a flight path.After the estimation completing target correlation behavior, adjust the data updating rate of the associating policy of a flight path, filtered motion model and target following adaptively according to estimated result.
The present invention is according to the result of data analysis, the state of target is estimated, environment residing for target is estimated, the actual conditions of interrelational form used in tracking and Filtering Model and interval and target are more met, to improve the tracking performance to extra large target.
Accompanying drawing explanation
Fig. 1 the present invention is based on the structural drawing of the adaptive variable structure radar target tracking method of policy determination.
Fig. 2 target relative topological location schematic diagram.
The algorithm structure figure of Fig. 3 policy determination.
Fig. 4 adaptive variable structure tracking structural drawing.
Embodiment
A kind of adaptive variable structure radar based on policy determination to extra large target following structure as shown in Figure 1.
(1) by the radar target point mark that network reception radar sensor transmits, a mark is put into the data structure designed according to orientation, Distance geometry chronological classification.The data structure that three-dimensional point mark stores evenly is divided into 64 sectors in orientation, and distance is divided into 100m/ unit, on the time with radar scanning cycle/unit.Consider when division unit, if divided thick, then computation complexity rose, and there is a large amount of double countings.
(2) targetpath existed is divided into groups according to positional information, grouping principle with the distance between target for thresholding, this thresholding is as the criterion with to phase mutual edge distance between target 1.5 times of radar resolution conversion in the actual scene to extra large target following, screens target in the mode being communicated with cluster.And the relative topological location matrix of the radar track in target close region is calculated by the group internal object number analyzing flight path grouping.The schematic diagram of target relative topological location as shown in Figure 2.Illustrate, the relative position of two targets is divided into four kinds of situations in Fig. 2.
Situation 1:
As Dis1>Dis2 and Azi1>Azi2, set up the relative topological location matrix of target 1, target 2.
Situation 2:
As Dis1>Dis2 and Azi1<Azi2, set up the relative topological location matrix of target 1, target 2.
Situation 3:
As Dis2>Dis1 and Azi2>Azi1, set up the relative topological location matrix of target 1, target 2.
Situation 4:
As Dis2>Dis1 and Azi2<Azi1, set up the relative topological location matrix of target 1, target 2.
(3) association process of drive point mark and flight path is carried out with the scan position of radar, within each radar scanning cycle, the data structure that the result of being divided into groups by flight path stores with some mark associates, and by comparing the change closing on and put mark number in the radar scanning cycle, concrete grammar is the sliding window time dimension of three-dimensional point mark storage organization being done to n/m, calculate the probability of occurrence at correspondence position (this correspondence position refer between target period in range of movement) place's point mark, m/n is met if there is probability, then think that the some mark of current period this position interior is effective, otherwise it can be used as clutter to reject.To judging that effective some mark continues the judgement on time dimension, the change of the available point mark number relatively on this position (this position refer between target period in range of movement), when available point mark number comparatively before several cycle increase to some extent, and when position being in the single goal radar return span on ordinary meaning, think that division appears in a mark, utilize average weighted method to be merged.It should be noted that the integrality in order to ensure data, what deposit in three-dimensional point mark storage organization is original point mark data, and the some mark through screening and merging is deposited separately, as the some mark data of a track association.Finally by the relative topological location matrix of flight path, complete current period and estimate that the some mark storage organization of process and the historical context point mark of flight path target and status information are picked out and be stored together, generate the situation information figure of single goal flight path.
(4) according to situation information figure, judged by the state of decision function to current goal.There are the situation information figure sample and dbjective state set that utilize off-line data to generate in decision function, the sample in the situation information figure of target generation and decision function compared, and selects corresponding dbjective state according to comparison result.The last output packet according to the judgement of dbjective state generation strategy is containing the estimation of the topology location matrix of target and adjacent objects, some track association strategy that current goal may exist and target travel trend.Algorithm structure figure as shown in Figure 3.
(5) according to the some track association strategy that policy determination exports, change target following structure, determine to comprise directive property ripple door, double wave door etc. by the association ripple door that target is current.After obtaining radar plot by association ripple door, according to the topology location matrix of target and adjacent objects, carry out the distribution of impact point track association, comprise unique allocation scheme, probability assignments mode etc.After completing associated allocation, according to the estimation of target travel trend, determine the motion model of current goal, comprise the motion model patterns such as CV, CA, CT and CS, and the velocity information current according to targetpath, change the data updating rate of target following, to reduce the impact of radar stochastic error on target at a slow speed, realize the tracking to extra large target.Algorithm structure figure as shown in Figure 4.In figure, dotted line is depicted as the current goal selected according to court verdict and follows the tracks of process structure.
Claims (2)
1. one kind based on the adaptive variable structure radar of policy determination to extra large method for tracking target, it is characterized in that: the radar plot that network receives is stored in data structure by orientation, Distance geometry time three dimensions, the data structure that three-dimensional point mark stores evenly is divided into 64 sectors in orientation, distance is divided into 100m/ unit, on the time with radar scanning cycle/unit, the targetpath existed is divided into groups according to positional information, grouping principle with the distance between target for thresholding, this thresholding is as the criterion with to phase mutual edge distance between target 1.5 times of radar resolution conversion in the actual scene to extra large target following, to be communicated with the mode of cluster to the target of screening same group, for the target in same group, to organize the dimension that internal object number is matrix, the orientation of group internal object is row, and distance is row, sets up the relative topological location matrix of flight path, then the time dimension of three-dimensional point mark storage organization is done to the sliding window of n/m, calculate the probability of occurrence at corresponding position point mark, this correspondence position to refer between target period in range of movement, m/n is met if there is probability, then think that the some mark of current period this position interior is effective, otherwise it can be used as clutter to reject, to judging that effective some mark continues the judgement on time dimension, the change of the available point mark number relatively on this position, this position to refer between target period in range of movement, when available point mark number comparatively before several cycle increase to some extent, and when position being in the single goal radar return span on ordinary meaning, think that division appears in a mark, utilize average weighted method to be merged, then by the relative topological location matrix of flight path, complete current period and estimate that the some mark storage organization of process and the historical context point mark of flight path target and status information are picked out and be stored together, generate the situation information figure of single goal flight path, finally using the input of situation information figure as decision function, decision function is defined as: input data are the situation information figure of single goal flight path, utilizing the relative topological location matrix of radar track confirmation target current is monotrack state or multiple target tracking state, if single goal state, then by percentage speed variation current for target, turning rate, relating dot mark type generates the current state vector of target as three dimensions, the state vector of the several typicalness generated utilizing off-line data in this state vector and decision function does correlation calculations, corresponding dbjective state is selected according to the result of correlation calculations, if first multiple goal state then generates the prediction topology location matrix of target and adjacent objects according to target and the current course of adjacent objects, the speed of a ship or plane, complete the state correlation calculations of target, the output packet of decision function is containing the estimation of the prediction topology location matrix of target and adjacent objects, some track association strategy that current goal may exist and target travel trend.
2. a kind of adaptive variable structure radar based on policy determination according to power 1 is to extra large target tenacious tracking method, it is characterized in that: according to the output of decision function, change target following structure, determine the association ripple door that target is current, comprise directive property ripple door, double wave door; After obtaining radar plot by association ripple door, according to the topology location matrix of target and adjacent objects, carry out the distribution of impact point track association, comprise unique allocation scheme, probability assignments mode; After completing associated allocation, according to the estimation of target travel trend, determine the motion model of current goal, comprise CV, CA, CT and CS motion model pattern, and the velocity information current according to targetpath, change the data updating rate of target following, to reduce the impact of radar stochastic error on target at a slow speed, realize the tracking to extra large target.
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| CN107144837A (en) * | 2017-04-24 | 2017-09-08 | 北京海兰信数据科技股份有限公司 | The multi-object tracking method and system of a kind of navigation radar data interconnection |
| CN107561527A (en) * | 2017-07-27 | 2018-01-09 | 中国船舶重工集团公司第七二四研究所 | A kind of shipborne radar sea bogey heading speed of a ship or plane high-accuracy compensation computational methods |
| CN108089184A (en) * | 2017-12-08 | 2018-05-29 | 中国船舶重工集团公司第七二四研究所 | A kind of TWS radar targets spatial position grouping parallel tracking processing method |
| CN108107410A (en) * | 2017-12-08 | 2018-06-01 | 中国船舶重工集团公司第七二四研究所 | A kind of abnormal shape radar cascading judgement object detection method |
| CN109001725A (en) * | 2018-06-07 | 2018-12-14 | 中国人民解放军海军工程大学 | A kind of sea unmanned boat sea multi-object tracking method |
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| CN111929653A (en) * | 2020-07-21 | 2020-11-13 | 上海交通大学 | Target detection and tracking method and system based on unmanned ship marine radar |
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| CN111289954B (en) * | 2020-03-31 | 2022-03-15 | 四川长虹电器股份有限公司 | Point cloud division and track matching method for millimeter wave radar target tracking |
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| CN111650581A (en) * | 2020-06-15 | 2020-09-11 | 南京莱斯电子设备有限公司 | Radar global target track automatic starting method based on environment perception |
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| CN111693962A (en) * | 2020-06-18 | 2020-09-22 | 中国人民解放军空军研究院战略预警研究所 | Target motion model estimation method based on cross inspection |
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| CN111929653A (en) * | 2020-07-21 | 2020-11-13 | 上海交通大学 | Target detection and tracking method and system based on unmanned ship marine radar |
| CN111929653B (en) * | 2020-07-21 | 2024-03-26 | 上海交通大学 | Target detection and tracking method and system based on unmanned ship navigation radar |
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