An optimization design of parametric array signal modulation algorithm based on NSGA-II and entropy weight TOPSIS

The acoustic parametric array is a transmitting device that utilizes high-frequency sound waves with similar frequencies to create sharp directivity, strong penetration, long propagation distance, and no sidelobes under the nonlinear action. However, this technology has not been widely adopted due to serious issues, such as time domain distortion. This paper focuses on analyzing the total harmonic distortion (THD) and intermodulation distortion (IMD), which are majorly concerned in engineering and compare the effects of different modulation algorithms, such as double-sideband modulation (DSB), single-sideband modulation (SSB), and modified amplitude modulation (MAM) for depth analysis. To address these issues and maximize the application scope of the parametric matrix system, a new modulation algorithm called weighted merge (WM) is proposed, based on the above three modulation algorithms. A multi-objective optimization model was established using a fast non-dominated sorting genetic algorithm (NSGA-II) with an elite strategy, and global optimization was carried out. The entropy weight TOPSIS method was used for comprehensive evaluation and decision analysis to find the ideal solution in different cases. By balancing the effects of different distortion components, this approach aims to solve practical problems in various engineering fields.