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Asynchronous track-to-track association algorithm based on similarity degree of interval-real sequence
Received date: 2014-05-21
Revised date: 2014-10-08
Online published: 2014-10-14
Supported by
National Natural Science Foundation of China(61032001); Program for New Century Excellent Talents in University of Ministry of Education of China(NCET-11-0872)
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.
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 . DOI: 10.7527/S1000-6893.2014.0275
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