A Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model

2021/09/03 by Thomas Kropfreiter, Kropfreiter, Thomas, Jason L. Williams +3 · 1 citation
Computer Science · Environmental Science · #FOS: Electrical engineering #Signal Processing (eess.SP) #Species Distribution and Climate Change #Target Tracking and Data Fusion in Sensor Networks #Video Surveillance and Tracking Methods #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2109.01490

openalex publication_date 2021/09/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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• Coherent Track-Before-Detect

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