4.7 Article

A Novel 4D Track-before-Detect Approach for Weak Targets Detection in Clutter Regions

期刊

REMOTE SENSING
卷 13, 期 23, 页码 -

出版社

MDPI
DOI: 10.3390/rs13234942

关键词

weak target tracking; track-before-detect; clutter region; maneuvering targets

资金

  1. Natural Science Foundation of China [62071363,61771371]
  2. Natural Science Foundation of Shaanxi Province [2020JQ-303]
  3. China Postdoctoral Science Foundation [2019M663633]
  4. Civil aerospace technology advance research project [D020403]
  5. Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology)
  6. Key Laboratory for Robot & Intelligent Technology of Shandong Province (Shandong University of Science and Technology)

向作者/读者索取更多资源

The developed 4D TBD approach aims to track weak extended targets in cluttered environments. It addresses the challenges of high dimensional measurements, as well as heterogeneous background clutter and clutter regions. Experimental results demonstrate the effectiveness of the method in detecting close targets with a high detection rate.
A 4D TBD approach is developed here for closely weak extended target tracking and overcoming heterogeneous clutter background and various clutter regions. The 4D measurements in this work are the points containing three positional information in spatial space and corresponding timestamp. The proposed method is mainly designed to address two issues. The first one is the dilemma between the weak target detection and difficult computation originating from the high dimensions of measurement. The second issue is the suppression of inhomogeneous background clutter and various clutter regions. The extension experiment using synthetic data showcases that no false alarm track would be built in the clutter regions, and the detection rate of close targets exceeds 94%. The experiments using real 3D radar also prove that the method works well in tracking closely maneuvering extended targets even if a clutter region exists.

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