Particle-systems implementation of the PHD multitarget tracking filter

Tim Zajic; Ronald P. S. Mahler

doi:10.1117/12.488533

25 August 2003 Particle-systems implementation of the PHD multitarget-tracking filter

Tim Zajic, Ronald P. S. Mahler

Proceedings Volume 5096, Signal Processing, Sensor Fusion, and Target Recognition XII; (2003) https://doi.org/10.1117/12.488533
Event: AeroSense 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Tim Zajic and Ronald P. S. Mahler "Particle-systems implementation of the PHD multitarget-tracking filter", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.488533

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