阅读说明：本技术 一种基于时空相关性的主被动传感器综合关联判决方法 (Active and passive sensor comprehensive association judgment method based on time-space correlation ) 是由 陆翔 周恒亮 姚远 匡华星 周亮 于 2020-06-12 设计创作，主要内容包括：本发明涉及一种基于时空相关性的主被动传感器综合关联判决方法。针对传统主被动传感器观测目标运动特征关联方法所存在的关联结果跳变、一对多错误关联等问题,本发明提出了一种基于时空相关性的主被动传感器航迹关联方法,具体步骤包括：读取基于目标运动特征的关联判决结果、基于时间相关性关联判决、基于空间相关性关联判决、基于时间-空间相关性的综合关联判决,从而提升关联判决结果的稳定性并消除一对多错误关联等问题,从而有效提高主被动关联判决结果的可信度。(The invention relates to an active and passive sensor comprehensive association judgment method based on space-time correlation. Aiming at the problems of association result jumping, one-to-many error association and the like existing in the traditional association method for observing the target motion characteristics by the active and passive sensors, the invention provides an active and passive sensor track association method based on space-time correlation, which comprises the following specific steps: the method comprises the steps of reading a correlation judgment result based on target motion characteristics, a correlation judgment based on time correlation, a correlation judgment based on space correlation and a comprehensive correlation judgment based on time-space correlation, so that the stability of the correlation judgment result is improved, the problems of one-to-many wrong correlation and the like are solved, and the reliability of the active and passive correlation judgment results is effectively improved.)

1. An active and passive sensor comprehensive association judgment method based on space-time correlation is characterized in that:

step 1: reading a plurality of association judgment results of the ith target track of the active sensor and the jth target track of the passive sensor based on motion characteristics; recording the judgment times of judging as 'associated' in the multiple association judgment results as N, and recording the judgment times of judging as 'unassociated' in the multiple association judgment results as M;

step 2: setting a time decorrelation threshold λ_r0.1, set time re-correlation threshold lambda_d0.9; if it is

and step 3: if the ith target track of the active sensor and the jth target track of the passive sensor are judged to be time correlation, the multiple correlation judgment results based on the target motion characteristics of the ith target track of the active sensor and the kth target track of the passive sensor are recorded, and the frequency of judging as 'correlation' in the multiple correlation judgment results is recorded as N₂(ii) a If N > N₂Judging that the ith target track of the active sensor and the jth target track of the passive sensor are in spatial correlation; if N is less than or equal to N₂Judging that the ith target track of the active sensor and the kth target track of the passive sensor are in spatial correlation;

and 4, step 4: if the ith target track of the active sensor and the jth target track of the passive sensor meet the spatial correlation and the temporal correlation, the comprehensive correlation judgment result is correlation; if the spatial correlation is not correlated and the time correlation is correlated, synthesizing the correlation judgment result to maintain the last correlation judgment result; if the correlation of the spatial correlation and the correlation of the time are not satisfied, synthesizing the correlation judgment result to maintain the last correlation judgment result; and if the spatial correlation is not correlated and the temporal correlation is not correlated, the comprehensive correlation judgment result is not correlated.

Technical Field

The invention relates to a correlation method for observing flight paths by a master sensor and a passive sensor

Background

The accurate association and high-confidence fusion of the active and passive sensor data are key cores for realizing the deep fusion of the active and passive sensing data and exerting the integrated sensing efficiency. The existing active and passive association judgment method only depends on the motion characteristics of the target to carry out association judgment, has the problems of unstable association result, one-to-many error association and the like, and is difficult to meet the requirement of high-reliability active and passive fusion application of mass observation data in a complex detection environment.

Disclosure of Invention

The invention provides an active and passive sensor comprehensive association judgment method based on space-time correlation, which effectively reduces the probability of occurrence of phenomena of unstable association result, one-to-many wrong association and the like in the traditional association method by adopting association judgment based on time correlation, association judgment based on space correlation and comprehensive association judgment based on time-space correlation.

The realization process of the invention mainly comprises the following steps:

step 1, reading and counting a judgment result of the active sensor observation track and the passive sensor observation track which are to be subjected to the association judgment and adopting the association judgment based on the target motion characteristic.

Step 2: and performing correlation judgment based on time correlation on the observed tracks of the active and passive sensors.

And step 3: and performing correlation judgment based on spatial correlation on the observation navigation of the active and passive sensors.

And 4, step 4: and performing comprehensive correlation judgment based on time-space correlation on the observation navigation of the active and passive sensors.

The invention comprehensively utilizes the motion correlation characteristics, the time correlation characteristics and the space correlation characteristics of different sensors to observe the same target to carry out comprehensive correlation judgment on the flight path, thereby solving the problems of unstable correlation results, high one-to-many correlation error rate and the like caused by the correlation judgment only depending on the target motion characteristics in the traditional active and passive sensor correlation judgment method, effectively improving the reliability of the correlation judgment results and providing support for active and passive fusion application.

Drawings

FIG. 1 is a comprehensive association decision method for active and passive sensors based on space-time correlation;

fig. 2 is a diagram illustrating an embodiment of a method for determining a comprehensive association between active and passive sensors based on spatiotemporal correlation.

Detailed Description

The implementation process of the embodiment of the present invention is shown in fig. 2, and is specifically described as the following process:

step 1: and reading and counting a plurality of correlation judgment results based on the target motion characteristics.

1) Reading a plurality of association judgment results of the ith target track of the active sensor and the jth target track of the passive sensor based on motion characteristics;

2) recording the judgment times of judging as 'associated' in the multiple association judgment results as N, and recording the judgment times of judging as 'unassociated' in the multiple association judgment results as M;

step 2: and (4) association decision based on time correlation.

1) Setting a threshold: setting a time decorrelation threshold λ_r0.1, set time re-correlation threshold lambda_d＝0.9；

2) And (3) performing time correlation judgment: if it isJudging that the ith target track of the active sensor and the jth target track of the passive sensor are time correlation decorrelation; if it isJudging that the ith target track of the active sensor and the jth target track of the passive sensor are time-correlation; if it is

Maintaining the previous decision;

and step 3: and (4) association decision based on spatial correlation.

1) Recording one-to-many correlation decision results: if the ith target track of the active sensor and the jth target track of the passive sensor are judged to be time correlation, recording multiple correlation judgment results based on target motion characteristics of the ith target track of the active sensor and the kth target track of the passive sensor,recording the times of judging as 'association' in the multiple association judgment result as N₂；

2) Performing correlation decision of spatial correlation: if N > N₂Judging that the ith target track of the active sensor and the jth target track of the passive sensor are in spatial correlation; if N is less than or equal to N₂Judging that the ith target track of the active sensor and the kth target track of the passive sensor are in spatial correlation;

and 4, step 4: and (4) comprehensive association judgment based on time-space correlation.

The synthetic association decision is performed according to the following table.

Table 1 comprehensive association decision