A UAV Single Station Passive Location Algorithm Based on Harris Trevally Fish Optimization
Jingpeng Gao, Pengjie Zhao, Tianran Zhang, Jianfei Qian · 2024
The traditional swarm intelligence optimization algorithm is used to solve the UAV single station passive location with reduced positioning accuracy due to the continuous motion of the UAV. To address this problem, this paper proposes a UAV single station passive location algorithm based on Harris Trevally Fish Optimization (HTFO). The algorithm combines historical and real-time phase difference information, and introduces the Harris factor and Host foraging ideology. It improves the algorithm's searching ability while avoiding the algorithm from falling into local optimum. The simulation results show that the proposed algorithm is better than the traditional algorithm in performance stability, and the positioning accuracy is improved by 6.13%, which has good value for engineering applications.