Evolutionary Algorithms Based Sparse Spectrum Waveform Optimization
This chapter presents a technique to determine a suite of 'optimal' waveforms (in the Pareto sense) for a single platform radar system performing multiple radar missions simultaneously. The authors contend that a waveform suite can be determined by applying the Strength Pareto Evolutionary Algorithm 2 (SPEA2) developed by Zitzler et al. to find waveform parameters that successfully realize a set of objectives particular to a variety of radar missions. The objectives to be optimized are dictated by the missions of interest. The mapping of these objective functions to actual radar performance parameters is used in the SPEA2 algorithm to determine how best to perform multiple radar missions simultaneously, such as ground moving target indication (GMTI), airborne moving-target indication (AMTI), synthetic aperture radar (SAR) imaging, etc. using a single radar system. This chapter introduces the concept of using an evolutionary computational approach to design optimal waveforms for a diverse set of radar missions. Results are presented for a scaled multi-mission multi-objective function scenario to illustrate the potential of the proposed methodology.
Evolutionary Algorithms Based Sparse Spectrum Waveform Optimization, Page 1 of 2
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