Parallel Algorithms for Earth Observation Coverage of Satellites

Coverage-rate computation is crucial in satellite mission planning. However, with increasingly wider mission scope and stricter demands on planning efficacy, how to improve the computing performance of coverage rate has become an important topic. In this paper, traditional grid-point approach (GPA) was used as a primary algorithm to solve satellite's earth observation coverage. To find the causes of error and propose optimization strategies, this paper also summarized grid generation and ray casting method involved in the abovementioned traditional grid-point approach. In the analysis of optimization strategies, the parallel technique was used to improve the algorithm efficiency. Based on applicable scenarios of the grid-point approach, four different sorts of grid-point generating precisions were designed, and the performance of all the parallel grid-point algorithms was tested. The test findings showed that all the parallel algorithms have significantly better performance than their serial counterparts, and the parallel optimization effect of GPU is superior to that of CPU.