Multi-platform multi-target tracking fusion via covariance intersection: using fuzzy optimised modified Kalman filters with measurement noise covariance estimation

Presented in this paper is a detailed novel approach to tracking multiple moving targets from multiple moving platforms and fusing the individual estimates within platform centric nodes via covariance intersection. The approach presents a method of deconstructing the target model into a nonlinear el...

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Bibliographic Details
Published in:IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications pp. 185 - 194
Main Authors: Wren, T.J, Mahmood, A
Format: Conference Proceeding
Language:English
Published: Stevenage IET 2008
Subjects:
Algebra
Combinatorial mathematics
Digital signal processing
Filtering methods in signal processing
fuzzy logic feedback structure
covariance matrices
fuzzy set theory
Frobenius norm
multiple moving target tracking
feedback
multi-platform multi-target tracking fusion
platform centric nodes
target tracking
measurement noise covariance estimation
measurement covariance matrix
covariance intersection
fuzzy optimised modified Kalman filters
Kalman filters
ISBN:0863419100, 9780863419102
Online Access:Get full text
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Summary:Presented in this paper is a detailed novel approach to tracking multiple moving targets from multiple moving platforms and fusing the individual estimates within platform centric nodes via covariance intersection. The approach presents a method of deconstructing the target model into a nonlinear element and a Kalman filter, modelling the target position and velocity vectors of the targets. The method avoids the increased complexity of using extended Kalman filters. The model state noise covariance is restructured by considering the source of the noise within the simplified imposed model and the measurement noise covariance is estimated from a single coefficient optimized moving average filter. The filter coefficient is optimally determined by the minimization of the variance of the Frobenius norm of the current estimated measurement covariance matrix, via a fuzzy logic feedback structure.
ISBN:0863419100
9780863419102
DOI:10.1049/ic:20080071