Multi-scan smoothing for tracking manoeuvering target trajectory in heavy cluttered environment

An automatic target tracking algorithm must be capable of dealing with an unknown number of targets and their trajectory behaviour inside the surveillance region. However, due to target motion uncertainties, heavily populated clutter measurements and low detection probabilities of targets, the smoot...

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Bibliographic Details
Published in:IET radar, sonar & navigation sonar & navigation, 2017-12, Vol.11 (12), p.1815-1821
Main Authors: Memon, Sufyan, Son, Hungsun, Memon, Kashif Hussain, Ansari, Arsalan
Format: Article
Language:English
Subjects:
automatic target tracking
clutter
false‐track discrimination
fixed‐interval integrated track splitting smoothing
FTD
heavily populated clutter measurements
heavy cluttered environment
ITS‐S
low detection probabilities
manoeuvering target trajectory tracking
multiscan smoothing
Research Article
sensor fusion
smoothing data association
smoothing methods
surveillance region
target motion uncertainty
target tracking
target trajectory accuracy
video surveillance
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Description
Summary:An automatic target tracking algorithm must be capable of dealing with an unknown number of targets and their trajectory behaviour inside the surveillance region. However, due to target motion uncertainties, heavily populated clutter measurements and low detection probabilities of targets, the smoothing algorithms often fail to detect the true number of target trajectories. In this study, the authors discussed some deficiencies and insignificances of existing smoothing algorithms and proposed a new smoothing data association based algorithm called fixed-interval integrated track splitting smoothing (ITS-S). The proposed algorithm employ smoothing data association algorithm and compared with existing smoothing algorithms outperform in terms of target trajectory accuracy and false-track discrimination (FTD). However, existing algorithms fail to generate smoothed target trajectory and provides insignificant FTD performance in such difficult environments as illustrated in this simulation study. The ITS-S shows improved smoothing performance compared with that of existing algorithms for a manoeuvering target tracking in a heavily populated cluttered environment and low detection probabilities.
ISSN:1751-8784
1751-8792
DOI:10.1049/iet-rsn.2017.0019