A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System

Abstract

To track multiple extended targets for the nonlinear system, this paper employs the idea of the particle filter to track kinematic states and shape formation of extended targets. First, the Bayesian framework is proposed for multiple extended targets to jointly estimate multiple extended target state and association hypothesis. Furthermore, a joint proposal distribution is defined for the multiple extended target state and association hypothesis. Then, the Bayesian framework of multiple extended target tracking is implemented by the particle filtering which could release the high computational burden caused by the increase in the number of extended targets and measurements. Simulation results show that the proposed multiple extended target particle filter has superior performance in shape estimation and improves the performance of the position estimation in the situation that there are spatially closed extended targets.

An Extended Target Tracking Algorithm Based on Gaussian Surface Fitting

“…. ξ i is the basic cubature point in the equation (14). Spread the cubature points according to the measurement equation:…”

“…e multitarget tracking algorithm builds a random nite set based on multitarget states and measurements separately [9][10][11], which avoids data correlation but requires consideration of the division of the measurement set at each moment [12][13][14]. In addition, this algorithm only provides the state set at each moment, and a reasonable track generation algorithm needs to be added [15].…”

Application of Improved Simplex Quadrature Cubature Kalman Filter in Nonlinear Dynamic System

“…Nonlinear filtering and estimation based on Bayes framework have been widely applied in many fields, such as target tracking [1][2][3][4][5], navigation [5,6] and positioning [7,8], power system [9][10][11], and pattern recognition [12]. Recent years have seen a surge of interest in solving the nonlinear estimation problems.…”