A multisensor single target tracking simulator: MUST

Author

Karan, Mehmet ; McMichael, Daniel W.

Author_Institution

Cooperative Res. Centre for Sensor Signal & Inf. Process., The Levels, SA, Australia

fYear

1996

fDate

21-22 Nov 1996

Firstpage

159

Lastpage

164

Abstract

This paper describes a multisensor single target tracking simulator “MUST” developed at CSSIP. MUST is based on a multisensor extended Kalman filter (EKF) which can handle asynchronous nonlinear multiple measurements of target parameters such as range, bearing, range rate and elevation angle. Multiple measurements from each sensor are handled by the probabilistic data association (PDA) filter. MUST provides a flexible platform where the performance of the EKF-PDA tracker can be assessed for different sensor, target and environment scenarios. This paper also presents some simulation results for different tracking scenarios and gives an initialization algorithm for the EKF-PDA algorithm

Keywords

Kalman filters; Monte Carlo methods; probability; sensor fusion; simulation; target tracking; tracking; CSSIP; MUST; Monte Carlo simulation; asynchronous nonlinear multiple measurements; extended Kalman filter; initialization algorithm; multisensor single target tracking simulator; probabilistic data association filter; Computational modeling; Nonlinear equations; Parameter estimation; Performance analysis; Sampling methods; Sensor phenomena and characterization; Sensor systems; Signal processing; Target tracking; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Fusion Symposium, 1996. ADFS '96., First Australian

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3601-1

Type

conf

DOI

10.1109/ADFS.1996.581100

Filename

581100