A Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model
Signal Processing
2021-09-06 v1
Abstract
We propose a scalable track-before-detect (TBD) tracking method based on a Poisson/multi-Bernoulli model. To limit computational complexity, we approximate the exact multi-Bernoulli mixture posterior probability density function (pdf) by a multi-Bernoulli pdf. Data association based on the sum-product algorithm and recycling of Bernoulli components enable the detection and tracking of low-observable objects with limited computational resources. Our simulation results demonstrate a significantly improved tracking performance compared to a state-of-the-art TBD method.
Keywords
Cite
@article{arxiv.2109.01490,
title = {A Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model},
author = {Thomas Kropfreiter and Jason L. Williams and Florian Meyer},
journal= {arXiv preprint arXiv:2109.01490},
year = {2021}
}
Comments
published at FUSION conference 2021