Title :
Extended Kalman particle filter angle tracking (EKPF-AT) algorithm for tracking multiple targets
Author :
Hou, Sheng-Yun ; Hung, Hsien-Sen ; Kao, Tsai-Sheng
Author_Institution :
Dept. of Electron. Eng., Hwa Hsia Inst. of Technol., Taipei, Taiwan
Abstract :
In this paper, we present an angle tracking algorithm based on the extended Kalman particle filter (EKPF), called EKPF-AT, using an array of sensors with known locations. This algorithm is capable of determining DOA angles using a single snapshot of data during the interval between each time step. The EKPF combines particle filtering (PF) with the extended Kalman filter (EKF) in order to prevent sample impoverishment during its resampling process. The effectiveness of the proposed algorithm is demonstrated via computer simulations in scenarios involving targets with crossing trajectories.
Keywords :
Kalman filters; direction-of-arrival estimation; nonlinear filters; particle filtering (numerical methods); sensor arrays; target tracking; arrival direction angles; extended Kalman particle filter angle tracking algorithm; multiple target tracking; sensor array; angle tracking; direction of arrival (DOA); extended Kalman filter (EKF); particle filter (PF);
Conference_Titel :
System Science and Engineering (ICSSE), 2010 International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-6472-2
DOI :
10.1109/ICSSE.2010.5551746