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Proceedings Paper

Particle-systems implementation of the PHD multitarget tracking filter
Author(s): Tim Zajic; Ronald P. S. Mahler
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Paper Abstract

We report here on the implementation of a particle systems approximation to the probability hypothesis density (PHD). The PHD of the multitarget posterior density has the property that, given any volume of state space, the integral of the PHD over that volume yields the expected number of targets present in the volume. As in the single target setting, upon receipt of an observation, the particle weights are updated, taking into account the sensor likelihood function, and then propagated forward in time by sampling from a Markov transition density. We also incorporate resampling and regularization into our implementation, introducing the new concept of cluster resampling.

Paper Details

Date Published: 25 August 2003
PDF: 9 pages
Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); doi: 10.1117/12.488533
Show Author Affiliations
Tim Zajic, Lockheed Martin Tactical Systems (United States)
Ronald P. S. Mahler, Lockheed Martin Tactical Systems (United States)


Published in SPIE Proceedings Vol. 5096:
Signal Processing, Sensor Fusion, and Target Recognition XII
Ivan Kadar, Editor(s)

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