App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 2

Multi-object identity matching method based on probabilistic association for millimeter-wave and acoustic signals

Mo Yongchen1,2
Wang Juan1
Xue Can2,3
Zhang Xu1,2
Zhuge Huixin2
1. School of Robotics and Intelligent Manufacturing, Huzhou Normal University, Huzhou Zhejiang 313000, China
2. Huzhou Institute of Zhejiang University, Huzhou Zhejiang 313098, China
3. Shanghai Fire Research Institute of Ministry of Emergency Management, Shanghai 200032, China
DOI: 10.19734/j.issn.1001-3695.2026.06.0164

Abstract

To address unstable identity association in multi-object tracking under heterogeneous and asynchronous sensing conditions, this study proposes a Multi-Feature Adaptive Matching (MFAM) method for anonymous millimeter-wave radar tracks and acoustic tags. MFAM models track–tag matching as a probabilistic association problem, constructs the observation likelihood using single-base-station range residuals and observation uncertainty, introduces a historical identity prior, and performs identity assignment through statistical gating and global matching. It also uses short-term identity memory to improve identity preservation during occlusion recovery. Experiments in three-target same-direction, crossing, 2 s occlusion, and 4 s occlusion recovery scenarios show that MFAM maintains high MOTA and IDF1. Compared with SORT-E, MFAM reduces identity switches by 66.7%, 56.3%, and 50.0% in the crossing, 2 s occlusion, and 4 s occlusion scenarios, respectively. The results demonstrate that MFAM improves identity association stability without appearance features and enhances identity continuity during trajectory crossing and recovery from short-term observation loss.

Foundation Support

国家重点研发计划项目(2021YFB3900800)
浙江省市场监督管理局科研项目(ZD2025009)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.06.0164
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 2

Publish History

[2026-10-21] Accepted Paper

Cite This Article

莫永晨, 王娟, 薛灿, 等. 基于概率关联的毫米波与声信号多目标身份匹配方法 [J]. 计算机应用研究, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0164. (Mo Yongchen, Wang Juan, Xue Can, et al. Multi-object identity matching method based on probabilistic association for millimeter-wave and acoustic signals [J]. Application Research of Computers, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0164. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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