Research And Implementation Of Parallel Optimization Technology On Evaluation Of GNSS Spatial Signal Quality

With the rapid development of satellite navigation,navigation signals become closely related to us and are widely used in transportation,hydrological monitoring,weather forecasting,emergency rescue and other fields.Carrying out evaluation of signal quality is benefit to help monitor the quality of navigation signals and provide highly reliable and usable navigation signals.Fast and accurate evaluation of signal quality can quickly assess navigation signal performance and improve navigation service capabilities.This paper aims to study the parallel acceleration strategy of evaluation of GNSS signal quality,improve the efficiency of signal quality analysis,and provide high-quality signal services for navigation users.This paper takes the evaluation of Galileo E5 signal quality as the research object,selects two major modules of signal capture and signal tracking to study the parallel scheme,and selects the relevant curve generation algorithm module to verify the parallel scheme.After the literature research,three parallel strategies were proposed including based on the Parallel Computing Toolbox parallel program,the Spark distributed parallel program,and the CUD A programming parallel program.Firstly,analyzing signal capturing,signal tracking and correlation curve algorithms,locating hotspots and time-consuming code logic.For signal capturing,contrast experiments were used to design and implement three parallel schemes.The experiment results show that a single capture of CUDA-programmed parallel capture scheme takes only 0.5 seconds and the hotspot code logic only takes 0.36 seconds,which has a good acceleration effect compared to the original algorithm.Proposing two concurrent strategies of signal tracking algorithm including based on Spark distributed parallelism and CUDA-based parallelism.The same experiment data is used to design and implement the two parallel schemes.The experimental results show that the speedup ratio of parallel tracking scheme based on CUDA programming reaches 12.66,which has better acceleration effect.After the parallelization of signal capture and signal tracking,the parallel scheme based on CUDA programming has good execution efficiency.To verify the applicability of the parallel scheme based on CUDA programming for signal quality evaluation,designing the parallel scheme for the correlation curve generation.Then the correlation curve generation based on CUDA is designed from the aspects of data storage,parallel flow,kernel function implementation and C-MEX file design and implementation.Using the same raw data to execute experiments on original algorithm and the parallel scheme,through experiments,the average time-consuming 0.26 seconds for the parallel correlation curve generation based on CUDA,and the time-consuming 0.026 seconds for generating a single correlation curve,the parallel scheme based on CUDA has obvious acceleration effect on correlation curve generation algorithm.Through the verification of the parallel correlation curve generation based on CUDA,combined with many large matrix operations and other characteristics involved in signal quality evaluation,this paper proposes a parallel acceleration strategy based on CUDA.The CUDA parallel strategy has good scalability,provides a common programming interface to facilitate simultaneous evaluation of multiple satellites,accelerates the evaluation of signal quality through parallel programming based on CUDA improves the efficiency of signal evaluation,also provides high quality navigation signals.