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

fYear

2013

fDate

23-27 Sept. 2013

Firstpage

1

Lastpage

6

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);

fLanguage

English

Publisher

ieee

Conference_Titel

Oceans - San Diego, 2013

Conference_Location

San Diego, CA

Type

conf

Filename

6741120