Title :
MEFPDA-SCKF for underwater single observer bearings-only target tracking in clutter
Author :
Dengfeng Mei ; Kaizhou Liu ; Yanyan Wang
Author_Institution :
State Key Lab. of Robot., Shenyang Inst. of Autom., Shenyang, China
Abstract :
The MEFPDA-SCKF algorithm, which is based on square-root cubature Kalman filter (SCKF) and maximum entropy fuzzy probabilistic data association (MEFPDA), is proposed for single observer bearings-only target tracking in cluttered underwater environment. SCKF is used to solve the nonlinear state estimation of bearings-only tracking. MEFPDA is used to reduce the interference of clutter and provide reliable bearings. Simulation and field experiment are conducted to verify the effectiveness of the proposed algorithm.
Keywords :
Kalman filters; clutter; entropy; state estimation; target tracking; MEFPDA-SCKF algorithm; clutter interference; cluttered underwater environment; maximum entropy fuzzy probabilistic data association; nonlinear state estimation; square-root cubature Kalman filter; target tracking; underwater single observer bearings; Accuracy; Clutter; Covariance matrices; Kalman filters; Observers; Probabilistic logic; Target tracking; Bearings-only tracking; maximum entropy fuzzy probabilistic data association (MEFPDA); probabilistic data association (PDA); square-root cubature Kalman filter (SCKF);
Conference_Titel :
Oceans - San Diego, 2013
Conference_Location :
San Diego, CA
