Transformer Based Multi-Target Bernoulli Tracking for Maritime Radar

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Sweeney, Caden, Kim, Du Yong, Ristic, Branko, Cheung, Brian
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915358387994624
author Sweeney, Caden
Kim, Du Yong
Ristic, Branko
Cheung, Brian
author_facet Sweeney, Caden
Kim, Du Yong
Ristic, Branko
Cheung, Brian
contents Multi-target tracking in the maritime domain is a challenging problem due to the non-Gaussian and fluctuating characteristics of sea clutter. This article investigates the use of machine learning (ML) to the detection and tracking of low SIR targets in the maritime domain. The proposed method uses a transformer to extract point measurements from range-azimuth maps, before clustering and tracking using the Labelled mulit- Bernoulli (LMB) filter. A measurement driven birth density design based on the transformer attention maps is also developed. The error performance of the transformer based approach is presented and compared with a constant false alarm rate (CFAR) detection technique. The LMB filter is run in two scenarios, an ideal birth approach, and the measurement driven birth approach. Experiments indicate that the transformer based method has superior performance to the CFAR approach for all target scenarios discussed
format Preprint
id arxiv_https___arxiv_org_abs_2506_20319
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Transformer Based Multi-Target Bernoulli Tracking for Maritime Radar
Sweeney, Caden
Kim, Du Yong
Ristic, Branko
Cheung, Brian
Image and Video Processing
Signal Processing
Multi-target tracking in the maritime domain is a challenging problem due to the non-Gaussian and fluctuating characteristics of sea clutter. This article investigates the use of machine learning (ML) to the detection and tracking of low SIR targets in the maritime domain. The proposed method uses a transformer to extract point measurements from range-azimuth maps, before clustering and tracking using the Labelled mulit- Bernoulli (LMB) filter. A measurement driven birth density design based on the transformer attention maps is also developed. The error performance of the transformer based approach is presented and compared with a constant false alarm rate (CFAR) detection technique. The LMB filter is run in two scenarios, an ideal birth approach, and the measurement driven birth approach. Experiments indicate that the transformer based method has superior performance to the CFAR approach for all target scenarios discussed
title Transformer Based Multi-Target Bernoulli Tracking for Maritime Radar
topic Image and Video Processing
Signal Processing
url https://arxiv.org/abs/2506.20319