Poisson Multi-Bernoulli Radar Mapping Using Gibbs Sampling
Preprint, 2016

This paper addresses the radar mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multi-object posterior density of the map given a set of measurements. The landmarks in the map are modeled as extended objects, and the measurements are described as a Poisson process, conditioned on the map. We use a Poisson process prior on the map and prove that the posterior distribution is a hybrid Poisson, multi-Bernoulli mixture distribution. We devise a Gibbs sampling algorithm to sample from the batch multi-object posterior. The proposed method can handle uncertainties in the data associations and the cardinality of the set of landmarks, and is parallelizable, making it suitable for large-scale problems. The performance of the proposed method is evaluated on synthetic data and is shown to outperform an state-of-the-art method.

Författare

Maryam Fatemi

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Karl Granström

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Lennart Svensson

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Francisco J. R. Ruiz

Lars Hammarstrand

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Styrkeområden

Transport

Ämneskategorier

Signalbehandling