A Nonlinear Frequency Modulation Agile Waveform Optimization Algorithm for Pulse Doppler Radar

Traditional pulse Doppler radar faces limitations such as range ambiguity and clutter folding when detecting long-range slow-moving small targets in strong clutter backgrounds. The agile waveform technique aims to suppress these issues by varying the parameters of the transmitted waveform between pulses within the coherent processing interval (CPI). However, due to the differing range sidelobes produced by the matched filtering output of the agile waveform, range sidelobe modulation (RSM) effect occurs after Doppler processing, resulting in higher sidelobes in the Doppler domain. To address these challenges, a nonlinear frequency modulation (NLFM) agile waveform optimization algorithm for Pulse Doppler radar is proposed in this paper. First, the spectrum of NLFM waveforms is initially mathematically formulated by using a cosine series representation. Then, considering the RSM effect and waveform orthogonality, with the optimization objectives being the similarity and orthogonality of the agile waveforms. Finally, the Genetic Algorithm-Particle Swarm Optimization (GA-PSO) algorithm is employed to solve the optimization objectives, resulting in a set of NLFM waveforms with improved performance. Simulation results demonstrate that the proposed algorithm can strike a good balance between the RSM suppression and waveform orthogonality. The designed waveforms, when filtered by mismatched filters, effectively reduces the signal-to-noise ratio loss(SNRL) relative to the initial waveforms.