基于OpenMP的航迹融合并行优化方法

Parallel optimization of track fusion algorithm based on OpenMP

针对组网雷达中分布式数据融合计算量随数据量增大急剧增加的问题及航迹融合中最耗时的航迹关联环节,提出一种基于OpenMP的多线程优化方法。通过OpenMP并行计算雷达航迹间的关联距离,提升内部算法运算速度,并将数据接收、融合处理和结果输出过程进行多线程处理,进一步加快外部数据交互速度,提升融合处理整体时间性能。以大容量目标场景为测试用例,评估处理时间和优化加速比。仿真结果表明,所提并行优化方法能够有效提升运算速度。

Aiming at the problem that it is difficult to meet the real-time requirements with the increase of data volume in the distributed data fusion algorithm of netted radar,the track association algorithm based on statistical double-threshold method in the data fusion process is studied,and a multi-threaded optimization idea based on Open Multi-Processing(OpenMP)is proposed.The operation speed of the internal algorithm is improved by OpenMP parallel calculation of the correlation distance between radar tracks,and the external data transmission speed is accelerated by using three threads to separate the data receiving,fusion and sending processes,thus improving the processing speed of the overall fusion process.Taking the large capacity target scenario as the test case,the processing time and optimization acceleration ratio are evaluated.The simulation results show that the proposed parallel optimization method can effectively improve the computing speed.