Smoothing innovations and data association with IPDA

Authors:
Taek Lyul Song;Darko MušIcki
Affiliations:
Department of Electronic Systems Engineering, Hanyang University, Sa 3 Dong 1271, Room #409, 3rd Eng. Building, Ansan, Kyunggido 426-791, Republic of Korea;Department of Electronic Systems Engineering, Hanyang University, Sa 3 Dong 1271, Room #407, 3rd Eng. Building Ansan, Kyunggido 426-791, Republic of Korea
Venue:
Automatica (Journal of IFAC)
Year:
2012

Citing 3
Cited 0

Estimation with Applications to Tracking and Navigation

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Tracking in a cluttered environment with probabilistic data association

Automatica (Journal of IFAC)
Brief Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing

Automatica (Journal of IFAC)

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Abstract

Surveillance sensors return detections from targets as well as the clutter measurements. Data association algorithms often use innovations to discriminate between the target and the clutter measurements. Reducing the covariance of innovations reduces the surveillance area from which measurements are used, reducing the number of clutter measurements. This paper introduces smoothing innovations which reduce innovation covariance, and improve the data association performance. This concept is applied to the Integrated Probabilistic Data Association (IPDA) to produce a Smoothing IPDA (sIPDA). sIPDA trajectory estimation errors are reduced with a smoothing delay. A surprising outcome is that sIPDA improves the false track discrimination in real time (without the smoothing delay).