Abstract
Traditional radar waveforms are easily intercepted and interfered with by enemy’s reconnaissance system with the time–frequency periodic pattern recognition. Frequency and pulse repetition frequency (PRF) agility is an effective approach to decrease interception probability and increase anti-jamming capabilities. On the other hand, the agility brings about high sidelobes and the difficulty of parameter estimation using the range-Doppler signal processing. In this article, an optimization and high-resolution imaging algorithm for sparse stepped linear frequency modulation waveform (SSLFMW) with frequency and PRF agility is developed. The range and Doppler 2-D autocorrelation function of the agile waveform is investigated to pave a way to find an optimization strategy for frequency and PRF to suppress range and Doppler sidelobes. Relied on the pulse trains of low Doppler sidelobes, we propose a method of cognitive transmitting and motion retrieval based on the maximum likelihood principle to eliminate the frequency and range coupling in velocity estimation. The 2-D sparse reconstruction with conjugate gradient solver is proposed to efficiently reconstruct the high-resolution range-Doppler image with the frequency and PRF agility waveform. Both simulated and real-measured data sets are used to verify the improved performance of the proposal.
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