PHD filtering with localised target number variance

Delande, Emmanuel, Houssineau, Jérémie and Clark, Daniel (2013) PHD filtering with localised target number variance. In Signal Processing, Sensor Fusion, and Target Recognition XXII. vol. 8745, SPIE.. (doi:10.1117/12.2015786).

Record type: Conference or Workshop Item (Paper)

Abstract

Mahler's Probability Hypothesis Density (PHD filter), proposed in 2000, addresses the challenges of the multipletarget detection and tracking problem by propagating a mean density of the targets in any region of the state space. However, when retrieving some local evidence on the target presence becomes a critical component of a larger process - e.g. for sensor management purposes - the local target number is insufficient unless some confidence on the estimation of the number of targets can be provided as well. In this paper, we propose a first implementation of a PHD filter that also includes an estimation of localised variance in the target number following each update step; we then illustrate the advantage of the PHD filter + variance on simulated data from a multiple-target scenario.

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Published date: 23 May 2013

Additional Information: © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Venue - Dates: Signal Processing, Sensor Fusion, and Target Recognition XXII, , Baltimore, MD, United States, 2013-04-29 - 2013-05-02

Keywords: Higher-order statistics, Multi-object filtering, PHD filter, Target number variance

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