Cognitive Frequency Agility Waveform for Precise Velocity Deblurring Detection of High-speed Targets

High-speed target accurate detection is a challenge in a completely random frequency agility radar system. On the one hand, velocity ambiguity is an inherent phenomenon for highspeed moving targets. On the other hand, random phase fluctuation caused by frequency agility aggravates the range-azimuth coupling of target echo signals. Therefore, traditional signal processing methods are unable to effectively resolve velocity ambiguity in frequency agility radar systems. In this article, considering the urgent need to solve velocity ambiguity in frequency agility radar, we propose a random frequency coherent coded waveform (RFCCW) with the properties of frequency cognitive waveform (FCW) to achieve high-speed targets accurate detection. Especially, the echoes of RFCCW are first classified into different bursts according to the high pulse repetition interval (PRI) of FCW, and then joint processing of the fuzzy number estimation of the velocity and keystone transform (KT) is performed to correct range cell walk in the FCW echoes. Thus, the estimated coarse velocity is acquired by the fast Fourier transform (FFT) in FCW echoes, which is based on a proposed peak sidelobe difference (PSLD) criterion. Next, after range cell walk correction in all bursts by the coarse velocity, a coherent accumulation method based on modified nonuniform discrete Fourier transform (NUDFT) is proposed, aiming to achieve precise velocity deblurring focusing on a high-speed target in the range-velocity domain. Simulation results show that the proposed waveform is more conducive to solving the velocity ambiguity of a high-speed target than the existing waveforms, and the proposed signal coherent processing method can achieve better focusing accuracy of the target compared to existing processing methods.