Research On Test And Evaluation Method Of Beidou High-precision Receiver In Electric Power

With the development of China's Beidou satellite navigation system,a trend of"Beidou+industry" integration has formed.Electric power as an important energy pillar industry,its innovative application with Beidou system promotes the intelligent development of power systems and improves the management level of power systems.However,the power environment is special and the accuracy requirements are strict.Among them,the high-precision receiver plays an important role,which is related to the power operation efficiency and the safety of system operation.In this special environment,whether the receiver performance can meet the power requirements is particularly important.This paper takes three key indicators of the receiver-positioning,speed measurement and time accuracy as the main objects,and studies its specific test and evaluation methods.First of all,this paper establishes a mathematical model for the test simulation scenario.The stationary model,car motion model,sinusoidal motion model,and spiral rise model are used to simulate the actual scenario of the receiver in power applications..Data preprocessing is indispensable in the evaluation process.The quality of the processing will affect the subsequent evaluation.This paper studies the limitations and advantages and disadvantages of several traditional preprocessing methods.Based on this,a new gross error processing method based on k-means algorithm is proposed,which makes up for the shortcomings of traditional methods in limiting the sample size.During the processing,it was found that the sample was mixed with invalid data.In order to improve the processing efficiency,the number of visible satellites was normalized.The experimental test data was used to verify the feasibility of the method and the processing effect was good.Then,the positioning error data is evaluated.Considering that the dimensionality reduction process will lose information and affect the accuracy evaluation,a three-dimensional spherical probability error algorithm(SEP)is used for evaluation.Among them,three algorithms for calculating SEP are studied,and the maximum likelihood estimation algorithm(MLE)is improved.The KNN algorithm is introduced to divide the data into different domains.However,because of the speed comparison of KNN in the processing of large samples Slow,and the problem of inaccurate classification may occur.Therefore,the KNN and k-modes algorithm are fused.First,select a piece of data in the large sample for classification processing,and then calculate the remaining sample data based on the classification result.The obtained calculation result is passed MLE The algorithm realizes the estimation of SEP.The different sample size data in different simulation scenarios are evaluated,and the results of several methods are compared,which proves that the algorithm evaluation effect is better.Finally,an automatic receiver evaluation software was developed based on the Qt software platform.According to the needs of experimental testers,the software realized the functions of data import,accuracy evaluation and database management.The data import mainly completes the import of test data and the basic information of the receiver.The basic information includes the model of the receiver and the test scenario.In the accuracy evaluation,the corresponding evaluation method is selected according to the test indicators.After the evaluation,an evaluation report is generated as required.Finally,the completed evaluation task is recorded in the database to facilitate the data management of the experimenter.