Bulletin of Surveying and Mapping ›› 2026, Vol. 0 ›› Issue (8): 89-95.doi: 10.13474/j.cnki.11-2246.2026.0813

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A stable multi-target tracking method for ships in complex sea conditions based on interactive multiple models

Tao Zengjie, Zhang Hui, Yao Chaoyun, Zhu Juanxi   

  1. College of Electronic Science and Engineering, Hunan University of Information Technology, Changsha 410100, China
  • Received:2026-03-24 Published:2026-09-12

Abstract: [Purposes] Aiming at the core problems of ship multi-target tracking in complex sea conditions,such as high false alarm rate caused by strong sea clutter interference,track fracture and tracking loss caused by diverse maneuvering behaviors,and time-space synchronization of multi-source data in dense scenes,this paper proposes a ship multi-target stable tracking method based on interactive multi model (IMM). [Methods] This method uses a hierarchical processing architecture,first completes the multi-source data preprocessing and space-time alignment,and then designs the IMM adaptive tracking filtering algorithm.Through the parallel interaction of the three models of constant speed,acceleration and rotation rate and the joint probability data association,it realizes the adaptive tracking of maneuvering targets,and develops a variable threshold adaptive detection strategy.According to the sea state level,it dynamically adjusts the constant false alarm rate threshold to suppress clutter. [Findings] The results showed that the root mean square error of the method was 4.2±0.3 m,the trajectory integrity rate was 96.5% ±1.2%, and the detection probability was 0.88±0.03 under the 6-level sea state;In the high-frequency maneuver scenario,the lag time of model conversion is less than 0.3 s,and the tracking accuracy is significantly better than that of single model and traditional tracking scheme. [Conclusions] This method can provide effective technical support for ship traffic safety under adverse sea conditions.

Key words: ship multi-target tracking, interactive multiple models, complex sea conditions, adaptive detection, track reconstruction

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