日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2312.15823

A Sequential Detection and Tracking of Very Low SNR Objects

A Sequential Detection and Tracking of Very Low SNR Objects

シェア:XThreadsFacebookLINEはてブBluesky

著者: Reza Rezaie

分類: eess.SY, cs.AI, cs.HC, cs.RO, cs.SY

原文アブストラクト

A sequential detection and tracking (SDT) approach is proposed for detection and tracking of very low signal-to-noise (SNR) objects. The proposed approach is compared with two existing particle filter track-before-track (TBD) methods. It is shown that the former outperforms the latter. A conventional detection and tracking (CDT) approach, based on one-data-frame thresholding, is considered as a benchmark for comparison. Simulations demonstrate the performance.