Three-Dimensional Cooperative TDOA Location Method with Multi-UAV Based on Quantum Wind Driven Optimization

Abstract

Three-dimensional (3D) cooperative time- difference-of-arrival (TDOA) location model aims to solve the 3D location information of unmanned air vehicles (UAV) in complex environment without GPS. This paper uses a singlechain coding quantum wind driven optimization combined with Chan algorithm (Chan-QWDO) to solve the non-linear optimization problem in 3D cooperative TDOA location model. QWDO algorithm uses quantum rotation angle combined with chaotic equation and quantum rotation gate strategy on population evolution. Compared with Chan algorithm (Chan), particle swarm optimization (PSO) and genetic algorithms (GA), the Chan-QWDO algorithm shows better performance in 3D cooperative TDOA location problem. The simulation results show that if the parameters are assumed reasonably, Chan- QWDO algorithm has stable performance, fast convergence speed and strong adaptability. And the mean square error (MSE) is lower than other algorithms which means Chan-QWDO algorithm has higher positioning accuracy.