基于区实混合序列相似度的异步不等速率航迹关联算法

doi:10.7527/S1000-6893.2014.0275

Abstract

Abstract:

Because local sensors in the distributed multi-target tracking system usually start working at different time and provide tracks at different rates with different communication delays, the local tracks from different sensors are usually asynchronous. The current solution is to synchronize the tracks before track association. But the estimation error spreads when synchronizing, which affects the performance of correlation. To solve the problem, an asynchronous track-to-track association method based on similarity degree of interval-real sequence is presented. Firstly, the track sequences are transformed to same-length sequences which contain interval data and real data by interval-real sequence transform (IRST). Then a new difference measurement for the sequences is defined, by which the correlation degree can be calculated and the track association conclusion be made. Simulation results show that the presented method can effectively solve the asynchronous track-to-track association problem, and its performance is seldom affected in the case of different communication delays and disorderly data.

Key words: asynchronous track, interval grey number, track association, target tracking, information fusion

CLC Number:

V243.2
TN957

YI Xiao, HAN Jianyue, ZHANG Huaiwei, GUAN Xin. Asynchronous track-to-track association algorithm based on similarity degree of interval-real sequence[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(4): 1212-1220.

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Asynchronous track-to-track association algorithm based on similarity degree of interval-real sequence

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