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A distributed object-oriented multi-mission radar waveform design implementation

机译:分布式面向对象的多任务雷达波形设计实现

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This paper furthers the development of Genetic Algorithms (GAs) and their application to the design of multi-mission radar waveforms. An application was developed with the goal of developing a waveform suite that finds the Pareto optimal solutions to a multi-objective optimization radar problem. Utilizing the Strength Pareto Evolutionary Algorithm 2 (SPEA2) a series of radar parameters are optimized along the fitness metrics of interest. This implementation builds upon the previous work of [1] to develop an application that is capable of analyzing longer more realistic scenarios. It also advances the previous research by solving for the Pareto optimal front of a simultaneous Synthetic Aperture Radar (SAR) and Moving Target Indication (MTI) mission. These preliminary results are presented to validate the performance of the new application against previous work and introduce some results of the multi-mission radar suite.
机译:本文进一步介绍了遗传算法(GA)的发展及其在多任务雷达波形设计中的应用。开发了一个应用程序,其目的是开发一个波形套件,该套件可以找到多目标优化雷达问题的帕累托最优解。利用强度帕累托进化算法2(SPEA2),沿着感兴趣的适应性指标对一系列雷达参数进行了优化。此实现建立在[1]的先前工作的基础上,以开发能够分析更长的更现实的场景的应用程序。它还通过解决同时合成孔径雷达(SAR)和移动目标指示(MTI)任务的帕累托最优前沿,来推进先前的研究。提出这些初步结果是为了验证新应用相对于以前的工作的性能,并介绍多任务雷达套件的一些结果。

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