一种基于RFT和分段处理的高速机动目标相参积累算法

高速机动目标会在短时间内跨越距离单元（Range Migration, RM），并且由于目标机动性产生跨多普勒单元（Doppler Spread, DS）等问题。基于搜索的传统处理算法通过时间和计算量换取积累性能，不利于工程应用。本文提出一种通过分段处理方式对回波进行相参积累的算法。该算法在保证子片段内回波RM和DS问题可以忽略的前提下，将积累时间划分为若干个子片段。在该分段准则下通过Radon-Fourier Transform（RFT）对子片段进行处理。随后，根据各子片段RFT积累峰值位置分布特性和相位差异，设计一种子片段间的相参积累方案，实现多个子片段间峰值能量的相参积累。所提算法在子片段内可以忽略目标机动性的影响，避免了子片段内目标机动参数（加速度项）的搜索，可在积累性能和计算效率之间取得良好平衡。 

Coherent integration algorithm for high-speed maneuvering targets based on RFT and segmented processing

The high-speed maneuvering target would cross the Doppler unit and the Range unit in a short time. The traditional multi-dimensional search-based coherent integration method was not conducive to engineering realization. This paper presented a coherent integration algorithm for high-speed maneuvering targets based on segmented processing. In this algorithm, the Range Migration and Doppler Spread caused by the target acceleration could be ignored in sub-segment, and then the coherent integration of the echo signals in each sub-segment completed by Radon-Fourier Transform (RFT). Then, according to the peak accumulation characteristics and phase characteristics of each sub-segment RFT, a coherent integration algorithm was designed among sub-segments to realize the accumulation of peak energy among multiple sub-segments. The proposed algorithm can ignore the influence of target maneuverability in the sub-segments, avoid the search of target maneuvering parameters (acceleration) in the subsegments, and achieve a good balance between accumulation performance and computational efficiency