基于OpenMP的包络对齐并行方法研究与实现

Study and implementation of a parallel range alignment algorithm based on OpenMP

采用加矩形窗的积累互相关法和基于Fourier变换频域移位性质的最小熵法进行一维距离像包络对齐。针对包络对齐算法数据量大、复杂度高、运行时间长等缺点,提出一种应用于多核处理器的包络对齐并行算法。该方法利用OpenMP编译指导指令#pragma omp section和#pragma omp for对积累互相关算法和最小熵算法进行多线程并行优化。理论分析和仿真实验表明,该方法大大提升了算法的执行效率。

By using the accumulated cross correlation algorithm based on rectangular window and the minimum entropy algorithm based on the frequency shifting property of the Fourier transform, we aligne a one dimensional range profile. Traditional range alignment algorithms suffer from large data, high complexity, long running time, etc. To overcome such problems, we propose a parallel range alignment algorithm for multi-core processors. We use two compiling instructions ＂# pragma omp section＂ and ＂ # pragma omp for＂ of OpenMP for the accumulated cross correlation algorithm and the minimum entropy algorithm to achieve multi-threads parallel optimization. Theoretical analysis and experimental results show that the proposed method can increase the execution efficiency largely .