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The purpose of this study is to present a technique for enhancing multi-rotor spoke microphone array configurations through the utilisation of the Multiple Population Genetic Algorithm (MPGA) to meet the acoustic positioning demands of small UAVs. First, we analyse the pros and cons of both the Simple Genetic Algorithm (SGA) and the MPGA. Then, we construct the objective function using the main lobe width and peak side-lobe level as the optimisation parameters. To simplify the process, we determine the distance from the origin to each array element on a rotating arm and represent these coordinates as an array along the spoke of the rotating arm. This array serves as a sample individual based on the rotational symmetry of multiple rotating arms. The results of the simulation demonstrate that the method effectively enhances the resolution of the array in the UAV noise band by narrowing the main lobe width while maintaining the maximum sub-lobe level. Furthermore, this methodology showcases efficient convergence speed and resilience, emphasising the viability of utilising MPGA for the purpose of microphone array design. The current study introduces an effective optimisation approach for constructing microphone arrays used in acoustic positioning systems for small unmanned aerial vehicles (UAVs). The proposed method improves the performance and accuracy of acoustic localisation systems for UAVs and provides reliable technical support for monitoring and locating UAV missions.
Cao et al. (Thu,) studied this question.