Work

Merging/Splitting Tracking of Resolvable Group Targets Based on ISODATA Algorithm

Year: 2026

Type: article

Abstract: Resolvable group target tracking under merging/splitting conditions is a difficult task due to group structure changes. This article proposes an algorithm for tracking, merging, and splitting of groups founded on the ISODATA technique for iterative self-organizing data analysis and the generalized labeled multi-Bernoulli filter. The criteria for detecting group target merging and splitting were established: subgroup splitting is detected based on distances between group members and their corresponding subgroup centroids, while merging is determined by distances between the centroids of different subgroups. The proposed method can dynamically estimate the states and number of group members, the subgroup structures, and the number of subgroups within resolvable group targets. Simulation experiments demonstrate that the algorithm effectively estimates the states, quantity, internal structure, and number of subgroups of resolvable group targets in scenarios involving group merging and splitting.

Source: Electronics

DOI: 10.3390/electronics15204757

Authors: Ziran Zhou, Weifeng Liu, Zhi Zhao, Xiangxi Meng

Institutions: Shaanxi University of Science and Technology, National Earthquake Response Support Service, Computer Emergency Response Team

Language: English

Topic: Target Tracking and Data Fusion in Sensor Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: National Natural Science Foundation of China