Efficient Multi-Dimensional Optimization of Airborne Medium PRF Based on Genetic Algorithm
The design of the pulse repetition frequency(PRF)group of airborne pulse Doppler(PD)radar is the foundation to the overall radar design,which directly influences the radar's performance and application scenarios.In the design process of medium to high PRF groups,the optimization of multi-dimensional parameters is essential.The large number of adjustable parameters lead to a severe expansion in potential combinations,posing a great challenge to computational resources and time.Traditional optimization methods still face the problem of an enormous number of ex-haustive combinations,even after the parameter range is defined.Additionally,the design cycle of airborne radar system is usually short,with frequently changing mode requirements.It is necessary to complete the selection and preliminary optimization of the parameters in the early stage of the scheme in a short time,so as to facilitate subsequent design.This paper proposes an efficient multi-dimensional optimization method based on genetic algorithm,which not only increases the optimization dimensions to better meet the engineering needs,but also significantly enhances the optimization effi-ciency.The effectiveness of the proposed method has been validated through practical applications,demonstrating its significant value to the overall design argumentation of airborne PD radars.
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