Abstract
Detection of maneuvering small targets has always been an important yet challenging task for radar signal processing. One primary reason is that target variable motions within coherent processing interval generate energy migrations across multiple resolution bins, which severely deteriorate the parameter estimation performance. A coarse-to-fine strategy for the detection of maneuvering small targets is proposed. Integration of small points segmented coherently is performed first, and then an optimal inter-segment integration is utilized to derive the coarse estimation of the chirp rate. Sparse fractional Fourier transform (FrFT) is then employed to refine the coarse estimation at a significantly reduced computational complexity. Simulation results verify the proposed scheme that achieves an efficient and reliable maneuvering target detection with -16dB input signal-to-noise ratio (SNR), while requires no exact a priori knowledge on the motion parameters.
基金项目
国家自然科学基金(62171029)
国家自然科学基金(61931015)
国家自然科学基金(U1833203)
北京市自然科学基金(4172052)
Basic Research Program of Jiangsu Province(SBK2019042353)
维普
万方数据