DocumentCode :
3416534
Title :
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
Link To Document :
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