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常规雷达对隐身、超声速和高机动目标存在回波信噪比不足、距离徙动和多普勒谱扩展问题。将Keystone变换和修正离散Chirp-Fourier变换(MDCFT)相结合,提出了一种新的雷达信号处理算法。该算法通过Keystone变换补偿距离徙动问题,利用MDCFT对多普勒谱严重扩展的目标回波进行相参积累,提高目标检测性能的同时完成了对目标参数的估计,且该算法在方位向欠采样时仍可适用。最后对算法运算量及性能进行了分析,通过仿真验证了该算法的有效性。
Routine radar has steep, hypersonic and maneuvering targets with insufficient echo signal-to-noise ratio, distance migration and Doppler spread. Combining Keystone transform and modified discrete Chirp-Fourier transform (MDCFT), a new radar signal processing algorithm is proposed. The algorithm compensates the distance migration problem by using Keystone transform, and uses MDCFT to coherently accumulate the target echoes of Doppler spectrum. This algorithm can improve the target detection performance and estimate the target parameters at the same time. Sampling is still applicable. Finally, the computational complexity and performance of the algorithm are analyzed. The effectiveness of the algorithm is verified by simulation.