Systems Engineering and Electronics ›› 2025, Vol. 47 ›› Issue (10): 3218-3227.doi: 10.12305/j.issn.1001-506X.2025.10.09

• Sensors and Signal Processing • Previous Articles    

Low-altitude multi-target tracking algorithm in non-uniform clutter environment

Lina SHANG(), Mei DONG(), Baixiao CHEN()   

  1. National Key Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China
  • Received:2024-08-09 Online:2025-10-25 Published:2025-10-23
  • Contact: Mei DONG E-mail:2609361287@qq.com;dmei2006@xidian.edu.cn;bxchen@xidian.edu.cn

Abstract:

Aimming at the problem that in low-altitude environments, natural and human-made interferences can cause the background clutter to exhibit non-uniform distributions, resulting in an increase of false targets in multi-target tracking algorithms, a label unscented Kalman probability hypothesis density based on clustering (C-Label-UK-PHD) algorithm is proposed for low-altitude multi-target tracking. The algorithm first applies density clustering to partition the measurement data into dense and sparse regions, removing clutter measurements from each region to homogenize the measurement data, thereby suppressing the interference from non-uniform clutter. Then labels are used to distinguish between different targets and maintain the continuity of target trajectories. The simulation results show that this algorithm effectively suppresses the generation of false targets and achieves accurate, continuous and efficient multi-target tracking in non-uniform clutter environment.

Key words: multi-target tracking, random finite set, density clustering, clutter suppression, finite mixture model

CLC Number: 

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