A FISST approach for single target multi-measurement problem

作者：Liu Yanli^*; Fan Xiaoping; Zhang Heng; Fu Ping

来源：Journal of Information and Computational Science, 2012, 9(10): 2789-2797.

• Bayesian frameworks
• Bayesian model
• Extend kalman filters
• Finite set statistics
• Multi sensor
• Multi-measurement
• Multitarget
• Particle filter
• Probability hypothesis density filter
• Random finite sets

Inspired by the current popular multi-target Probability Hypothesis Density (PHD) filter, this paper uses Random Finite Sets (RFS) formalism to solve the problem of tracking a target that can be observed by multi-sensor. The solution to the single target multi-measurement problem is built on Finite Set Statistics (FISST) Bayesian framework. In addition, a SMC implementation of the FISST filtering is proposed and demonstrated on a number of particles. Compared with the traditional methods, such as the Extend Kalman Filter (EKF) and Particle Filter (PF), FISST filtering prove to be best in tracking.

• 出版日期2012
• 单位中南大学