Bulk-FFBP：基于距离向整体处理的快速分解后向投影算法

距离向分块快速分解后向投影(Block-FFBP)算法通过子孔径合成降低了传统BP的算法复杂度，并且通过距离向分块，简化了繁琐的极坐标与直角坐标的转换。然而，距离分块操作使各块引入了斜距范围波动，而且插值核长度余量导致了算法的内存效率低下，从而降低了成像效率。该文提出一种基于距离向整体处理的Bulk-FFBP算法，并细分为基于距离向控制点的Bulk-FFBP以及无控制点的Bulk-FFBP。文中通过仿真对两种Bulk-FFBP算法进行了误差分析、成像性能分析以及算法效率分析，并与Block-FFBP算法进行对比，证实了Bulk-FFBP的优越性。

Bulk-FFBP: Fast Factorized Back-projection Algorithm Based on Range Bulk Processing

Block Fast Factorized Back-Projection (Block-FFBP) algorithm adopts a subaperture synthesis approach to reduce the computing complexity of the conventional BP algorithm, and partitions the echo data into blocks in range to avoid the complicated transforms between polar and Cartesian coordinates. However, Block- FFBP results in a range span vibration of the data blocks, and Block-FFBP needs an extra data length associated with the interpolation kernel. That gives rise to the inefficiency of the memory, and furthermore the degradation of the imaging speed. A range Bulk processing based FFBP (Bulk-FFBP) algorithm is proposed in this paper. It is implemented in two ways. One is based on a series of range pivots, and the other one is of no pivots. The outperformance of Bulk-FFBP relative to Block-FFBP is verified through simulations in error analysis, imaging evaluation and computing efficiency test.