Adaptive PHD-track oriented tracker: applications in infrared detection contexts

Dominique Maltese

doi:10.1117/12.3014084

7 June 2024 Adaptive PHD-track oriented tracker: applications in infrared detection contexts

Dominique Maltese

Proceedings Volume 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII; 1305702 (2024) https://doi.org/10.1117/12.3014084
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Nowadays, multi target trackers have to be more self-adaptive to face pluralities of detection and clutter contexts. For instance, current naval surveillance systems have to deal with different kinds of threats including asymmetric targets for suicide actions or harassing missions. Moreover, time and space fluctuating heavy clutters have to be considered (solar reflection on sea, ground…). Usually, dedicated clutter maps techniques are implemented to adapt tracker parameters to local detection statistics and false alarms rates. In this paper, a self-adaptive tracking concept is proposed. It combines a PHD (Probabilistic Hypothesis Density) filter for clutter suppression, with a current track-oriented tracker. The first module adapts the functioning point of the terminal tracker to low/medium clutter situations. Regarding new algorithms under study, results are provided with infrared registered maritime scenes. They put forward performances that are achieved.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dominique Maltese "Adaptive PHD-track oriented tracker: applications in infrared detection contexts", Proc. SPIE 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, 1305702 (7 June 2024); https://doi.org/10.1117/12.3014084

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