Optimized Genetic Algorithm-Based Multi-UAV Cooperative TDOA Localization for Complex Multipath Scenarios

Radiation source positioning is vitally important in electromagnetic environment monitoring activities. However, most current positioning methods cannot achieve high accuracy complex multipath scenarios. In this paper, we propose an optimized genetic algorithm based time difference of arriva (GA-TDOA) multiple unmanned aerial vehicle (UAV) cooperative positioning method. We first propose a multipath signal identification algorithm based on path loss analysis. This algorithm can eliminate the effect of non-line-of-sight (NLOS) signals, thus, improving the positioning accuracy in multipath scenarios. Then, we design an optimized GA to select the UAV nodes that are little influenced by noises. The optimized GA has fast convergence and low complexity. By using the selected UAV nodes to locate radiation sources, the robustness and positioning accuracy of the positioning method can be improved. Experimental results show that the GA-TDOA positioning method can effectively identify LOS signals in complex multipath scenarios, and the positioning accuracy is increased by about 40% compared with the existing positioning methods.