Target track optimization method based on information entropy weight and nearest neighbor data association

A nearest neighbor, target track technology, applied in the field of radar, can solve the problems of wrong association, limited accuracy improvement, and inaccurate filtering results, achieving the effect of low transformation cost, easy transformation and upgrading, and improved accuracy
CN109901153AActive Publication Date: 2019-06-18XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2019-06-18

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Abstract

The invention discloses a target track optimization method based on information entropy weight and nearest neighbor data association. The method comprises the following steps: obtaining measurement vectors of a measurement point at the first two moments after track initiation, and calculating an initial state vector of a target; carrying out initialization on a Kalman filter; calculating a state estimation vector, an estimation error covariance matrix, a prediction vector, an innovation covariance matrix and Kalman gain of the target at the moment k through an iteration method; obtaining candidate measurement points falling into the center of a tracking gate at the moment k; and when the number of the measurement points at the moment k is larger than 1, optimizing and updating the target track at the moment k through an entropy weight method. Through deep mining of known measurement information, and on the basis of not changing the priori information, the method makes full use of the information carried by the target measurement point, so that the method has lower transformation cost and better applicability, and meanwhile, improves accuracy of radar track tracking.
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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 information entropy weight and nearest neighbor data association. Background technique

[0002] At present, 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, and data association technology is still the key technology in the field of multi-target tracking. Data association is based on the target and its quantity. A mapping relationship between measurements is established according to a specific data association algorithm, and data association can be used to determine which measurement the target is associated with. Therefore, the accuracy of data association seriously affects the radar's target tracking performance.

[0003] Typical data association target tracking algorithms include nearest neighbor al...

Claims

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