Abstract
The extraction algorithm of target characteristics resonance set at the high-frequency band plays a significant role in defense applications like early warning. The paper proposes a new method to extract the characteristic resonance set of radar targets in the resonance frequency region using an autoregressive moving average model optimized by root mean square propagation particle swarm optimization. Considering that the total scattering response in the resonant region consists of early-time and late-time responses, the autoregressive moving average model approximate the total scattering responses to avoid errors caused by intercepting the late-time response. Further, the paper investigated the impact of the swarm optimization algorithm on the accuracy of moving average model parameters when obtaining the resonance set at different target aspects. The extracted characteristic resonance results within a range of azimuth directions through an aircraft target paradigm indicate that the new method is more convenient and precise than the matrix beam prediction method.
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