Bearings-only TMA on manoeuvring target: a Gaussian mixture approach

This paper considers the problem of manoeuvring target tracking with bearings-only measurements collected by a single source. We use the switching multiple models description where the target motion is described by a finite collection of m models, each of one corresponding to a possible evolution, a...

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Bibliographic Details
Published in:IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications pp. 127 - 136
Main Author: Laneuville, D
Format: Conference Proceeding
Language:English
Published: Stevenage IET 2008
Subjects:
Filtering methods in signal processing
Interpolation and function approximation (numerical analysis)
Markov processes
Signal processing theory
Markov chain
approximation theory
Gaussian mixture approach
switching multiple models description
filtering theory
target tracking
Markov processes
approximation scheme
bearings-only measurements
optimal filter
target tracking manoeuvring
ISBN:0863419100, 9780863419102
Online Access:Get full text
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Summary:This paper considers the problem of manoeuvring target tracking with bearings-only measurements collected by a single source. We use the switching multiple models description where the target motion is described by a finite collection of m models, each of one corresponding to a possible evolution, and a Markov chain to model the jump between the different models. We test a new approximation scheme to avoid the exponential growth in the number of terms corresponding to the optimal filter.
ISBN:0863419100
9780863419102
DOI:10.1049/ic:20080064