Self-adaptation flight path data correlation method

Abstract

The invention discloses a self-adaptation flight path data correlation method comprising the following steps: establishing and maintaining a public data flight path table and a message queue, wherein the flight path table is mainly used for maintaining flight path data and comprises attribute information of flight paths per se, information of flight path points, information of sequential lengths, state information of an affiliated flight path, information of an affiliated fused flight path and the like, and the message queue comprises flight path batch numbers used for searching corresponding flight paths; and distinguishing correlation states of an input flight path into three states, namely undistributed state, undetermined distribution state and determined distribution state by automatically updating a flight path correlation sequential length M, thus enabling a flight path correlation algorithm to automatically adapt to different target distribution, different target motion states, and different tracking dimensions, tracking accuracy and tracking stability of different sensors and overcome adverse influences of the differences on correlation judgments. By applying the method, data synthesis is carried out only on input flight paths in the determined distribution state, so that the precision of the fused flight path is favorably maintained.

Description

technical field [0001] The invention belongs to the technical field of command control or information processing, and in particular relates to an adaptive track data correlation method, which can be used in a track data fusion system to perform multi-source track data correlation processing. Background technique [0002] In various track data correlation algorithms based on statistical theory, the relevant judgments of input tracks from different sources are all calculated and decided based on "statistical distance". For two tracks with the same dimension, expressed at the same time and in the same coordinate system, the statistical distance is generally defined as: [0003] (1) [0004] In the formula: [0005] - observation bias vector, , for the target at The state vector at time, , , , is the sensor number, is the number of sensors, ; is the sum of the error covariance matrix of the two sensors tracking the target tr...

AI Technical Summary

Problems solved by technology

in the system Using a fixed set value will lead to the advance or lag of relevant judgments, which will affect the accuracy of the fusion track in the data synthesis link, and cause the track attributes to be unknown or attribute jumps for a long time in the target comprehensive recognition link

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