Nonlinear filter algorithm for opto-electronic target tracking

Mao-tao Xiong; Jian-xun Song; Qin-zhang Wu

doi:10.1117/12.828778

20 May 2009 Nonlinear filter algorithm for opto-electronic target tracking

Mao-tao Xiong, Jian-xun Song, Qin-zhang Wu

Proceedings Volume 7283, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 72833K (2009) https://doi.org/10.1117/12.828778
Event: AOMATT 2008 - 4th International Symposium on Advanced Optical Manufacturing, 2008, Chengdu, Chengdu, China

Abstract

At present in opto-electronic targets tracking, traditional accepted algorithms inevitably connect with linear errors. To improve the degraded performance of general algorithms, the Adaptive Unscented Particle Kalman Filter (AUPF) algorithm is proposed. The algorithm combines with Unscented Kalman Filter (UKF) to incorporate the most current observation datum and to generate the importance density function. Additionally, the Markov Chain Monte Carlo (MCMC) steps are adopted to counteract the problem of particles impoverishment caused by re-sampling step and thus the diversity of the particles is maintained. The AUPF algorithm reduces the nonlinear influence and improves the tracking accuracy of the opto-electronic targets tracking system. The analytic results of Monte Carlo simulation prove the AUPF algorithm is right and feasible, and it enhances the stability, the convergence rate and the accuracy of tracking system. The simulation results and algorithm provide a new approach for precise tracking of opto-electronic targets, they must have better applicative prospect in various engineering than the traditional tracking algorithms.

Citation Download Citation

Mao-tao Xiong, Jian-xun Song, and Qin-zhang Wu "Nonlinear filter algorithm for opto-electronic target tracking", Proc. SPIE 7283, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 72833K (20 May 2009); https://doi.org/10.1117/12.828778

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