Method for Passive Location of UAV Conical Formation Based on Genetic Algorithm
Yuqing Sun, Liguo Fang · 2023
The pure direction-based passive positioning for unmanned aerial vehicles (UAVs) offers the advantages of high accuracy and low cost. However, the paradigm model of this implementation method lacks solution design in real-world scenarios. A passive receiving signal drone positioning model in a circular formation with unknown transmitting signal drone numbers is established through analytical geometry analysis and enumeration search. Qualitative segmentation was performed on conical formations, combined with drone positioning methods, and selection, crossover, and mutation operators were constructed based on fitness functions. A conical formation adjustment scheme based on genetic search algorithm was designed. Afterwards, a set of conical formation test data was constructed, and after adjustment, the unmanned aerial vehicle group reached the target state with errors Q(t)$\lt$ 0.1.