Target track optimization method based on dual-fusion maximum entropy fuzzy clustering JPDA

Abstract

The invention belongs to the technical field of radar. The invention relates to a flight path optimization method, in particular to a target track optimization method based on dual-fusion maximum entropy fuzzy clustering JPDA. The method comprises the following steps: (1) performing state prediction and updating by adopting a Kalman filter on the basis of a maximum entropy fuzzy clustering method,and performing preliminary screening on a target trace point set obtained at a moment k + 1according to an elliptical wave gate rule during scanning and tracking; (2) multiplying the measurement membership degree taking the wave gate center as the clustering center by the corresponding position of the wave gate membership degree taking the effective measurement data as the clustering center to obtain the bidirectional membership degree between each effective measurement and all the wave gate centers; and (3) analyzing clutter distribution and combining the bidirectional membership degree to obtain a final association probability, obtaining state estimation and estimation error covariance of the target according to a standard JPDA algorithm filtering program, and finally iterating trackingtrack information of the target. The method is high in tracking precision, and avoids complex correlation matrix splitting.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a target track optimization method based on double fusion maximum entropy fuzzy clustering JPDA. Background technique [0002] At this stage, with the continuous emergence of various new system radars, the characteristics that can be used in the field of multi-target tracking are becoming more and more diversified. Among them, data association technology is still the key in the field of multi-target tracking. It establishes a mapping relationship between the target and its measurement according to a specific data association algorithm, which is equivalent to using it to judge the specific relationship between the target and a certain measurement. to associate. Therefore, the quality of data association greatly affects the performance of target tracking. Data association research in complex background environments is still one of the directions that needs to be continu...

AI Technical Summary

Problems solved by technology

It is mainly to study and solve the problem of overlapping target gates in the multi-target tracking system, in which the measurement data in the overlapping gates have a serious impact on the update of the respective target tracks, especially the small-angle crossing between multiple targets will cause the When moving in parallel, common echoes between adjacent targets will cause the updated track to shift towards the direction of the common echo, which will easily cause target tracks to merge or cross

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