@inproceedings{8b34837c16314163b839e0a59abf31b3,
title = "Aeromarine reentry vehicle tracking based on asynchronous data fusion of multi-airborne-platform sensors",
abstract = "Asynchronous multi-sensor data fusion is a significant and practical problem in multi-airborne-platform combat system. In this paper, the low-altitude-period reentry vehicle (RV) tracking problem based on multi-airborne-platform is considered. We propose two fusion tracking algorithms for asynchronous observations of airborne infrared devices. The first one is based on the time registration policy, which unifies the observations of different nodes at different time to the fusion instant by interpolation. The second one is a new method based on asynchronous sequential fusion, which fuses the sequential observations of different nodes by state prediction. For the strong nonlinearity of reentry vehicle motion model and infrared angle observation, we use the particle filter to estimate the target states. Simulation results show that the two policies are both effective, but the time registration algorithm has better tracking precision in the assuming circumstance. Further experiments illustrate that the fusion performance is related to the observation sample rate, and the asynchronous sequential fusion method is more flexible in application.",
keywords = "Asynchronous fusion, Particle filter, Reentry vehicle, Time registration",
author = "Lijia Zhao and Meiqin Liu and Zhen Fan and Yan He",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 29th Chinese Control and Decision Conference, CCDC 2017 ; Conference date: 28-05-2017 Through 30-05-2017",
year = "2017",
month = jul,
day = "12",
doi = "10.1109/CCDC.2017.7978858",
language = "英语",
series = "Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2073--2078",
booktitle = "Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017",
}