非差模式的GNSS数据并行解算设计及实现

基于精密单点定位技术的非差模式是当前GNSS数据处理的主要策略之一。随着测站规模的增大,非差模式的处理时间也线性递增,传统的串行处理方法需消耗大量的计算时间。采用工厂模式和责任链模式实现了非差精密单点定位;利用轻量级的并行编程技术从底层设计并实现了基于任务的非差多核并行解算;进一步在网络多节点环境中建立并发布非差计算服务,实现了网络多节点协同并行解算GNSS数据。通过大量数据的测试与试验,验证了多核多节点的非差并行解算方案的高效性。试验结果表明,单节点多核并行、双节点网络并行、四节点网络并行、六节点网络并行的计算效率分别比单节点串行方案平均提高了2.74,5.30,9.38和14.69倍。

Design and Implementation of Parallel Processing Strategy for GNSS Data Based on the Undifferenced Method

The undifferenced pattern based on precise point positioning ( PPP) technology is one of the main strate-gies of the current Global Navigation Satellite System ( GNSS) data processing. With the increasing scale of the sta-tions, the processing time of undifferenced model is also linear increasing, and the traditional serial processing methods need to consume a lot of computing time. The PPP technology is implemented by using the factory design pattern and the chain of responsibility design pattern, and the parallel computing of PPP is designed from the bot-tom. In order to realize the network multi-node co-processing GNSS data, a lightweight multi-core undifferenced parallel computing based on the task is realized by adopting task parallel extensions technology, and the undiffer-enced computing services are established and released on the network nodes by using windows communication foun-dation technology. The high efficiency of undifferenced parallel computing scheme under multi-core multi-node platform is validated through a large amounts of data experiments, and the results show that compared to the single-node serial processing, the average increase rate of computational efficiency is 2.74 in single-node multi-core par-allel computing, 5.30 in two-node network parallel computing, 9.38 in four-node network parallel computing, and 14.69 in six-node network parallel computing.