4.6 Article

Multiple Sensor Linear Multi-Target Integrated Probabilistic Data Association for Ultra-Wide Band Radar

期刊

IEEE ACCESS
卷 8, 期 -, 页码 227161-227171

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3045933

关键词

Target tracking; Radar tracking; Ultra wideband radar; Clutter; Pollution measurement; Radar; Probabilistic logic; UWB; IR-UWB radar; multiple target tracking; probabilistic data association; LM-IPDA; localization

资金

  1. Future Innovation Research Funds through the Ulsan National Institute of Science and Technology (UNIST) [1.200034.01]
  2. Development of Drone System for Ship and Marine Mission through the Civil Military Technology Cooperation Center [2.180832.01]
  3. National Research Foundation of Korea (NRF) - Korea Government (MSIT) [2020R1F1A1075857]
  4. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2020R1A6A1A03040570]
  5. National Research Foundation of Korea [2020R1F1A1075857] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Ultra-Wide Band (UWB) radar has a number of advantages of resolving multipath, exceptional spatial resolution, and ranging performance. However, several difficulties are confronted for multiple target tracking using UWB radars such as clutter signals which contaminate target signals, and unidentified number and behavior of the targets. Hence, this paper presents to develop a multiple moving target tracking algorithm, consisting of preprocessing and multiple target tracking steps. In the preprocessing step, static clutter reduction and constant false alarm rate (CFAR) detection extract the target candidate range measurements from each UWB radar. Then, two multiple target tracking (MTT) steps are developed: range- based MTT and position-based MTT. The range-based MTT is mainly based on existing linear multi-target integrated probabilistic data association (LM-IPDA) from each UWB radar measurement. Then the outputs of each LM-IPDA are gathered in the positioning center to estimate the position of multiple targets. On the other hands, the position-based MTT is based on multiple sensor LM-IPDA (msLM-IPDA) as an accurate target tracking method for various uncertainties by improving the probabilistic model of LM-IPDA. The tracking performance of two MTT methods is investigated with both numerical simulation and experiments.

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