Group Target Tracking for Highly Maneuverable Unmanned Aerial Vehicles Swarms: A Perspective

Author:

Chen Yudi1ORCID,Jiao Yiwen1,Wu Min2ORCID,Ma Hongbin1ORCID,Lu Zhiwei1ORCID

Affiliation:

1. Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China

2. School of Space Information, Space Engineering University, Beijing 101416, China

Abstract

Group target tracking (GTT) is a promising approach for countering unmanned aerial vehicles (UAVs). However, the complex distribution and high mobility of UAV swarms may limit GTTs performance. To enhance GTT performance for UAV swarms, this paper proposes potential solutions. An automatic measurement partitioning method based on ordering points to identify the clustering structure (OPTICS) is suggested to handle non-uniform measurements with arbitrary contour distribution. Maneuver modeling of UAV swarms using deep learning methods is proposed to improve centroid tracking precision. Furthermore, the group’s three-dimensional (3D) shape can be estimated more accurately by applying key point extraction and preset geometric models. Finally, optimized criteria are proposed to improve the spawning or combination of tracking groups. In the future, the proposed solutions will undergo rigorous derivations and be evaluated under harsh simulation conditions to assess their effectiveness.

Funder

National Science Foundation of China

National Postdoctoral Program for Innovative Talents

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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