Tracking a Maneuvering Target in Clutter by a New Smoothing Particle Filter
Yanqiu Li, Yi Shen, Zhiyan Liu, Ping He · 2006
Tracking maneuvering target in cluttered environment is a problem of great theoretical and application interest. In this paper a new smoothing particle filter algorithm is proposed which combines the particle filter with a Gibbs sampler to perform the smoothing of the estimation of the target maneuvering and measurement origin. This algorithm is used to estimate states of a maneuvering target from its cluttered measurements, and the simulation results show its powerful ability to solve the problem