Construction Of A Software-defined GPS And Research Of The Ability Of Positioning In Harsh Environment

Satellite navigation plays a significant role in modern national defense,industrial production,agriculture and transportation and other fields.In recent years,it has attached an increasing importance to the research of navigation receiver which is the user part of satellite navigation system.To facilitate the scientific personnel to conduct a research,the software satellite navigation receiver emerges at the right moment.In various software platforms,MATLAB is deeply favored by R & D institutions and universities so that it has an important practical significance to build software navigation receiver based on MATLAB platform.In terms of satellite navigation receiver,at least four channel navigation signals are required to conduct location solution.In reality,the signals actually received by receiver cut out every few seconds because buildings,trees and other objects block them.Also,the station-keeping ability of navigation receiver will be subject to appropriate impact.Therefore,the research that aims at satellite navigation station-keeping ability of intermittent signals has a very important significance.GPS is taken as the object in this study,then the software GPS receiver is built based on MATLAB platform.And the extended Kalman filter(EKF)algorithm is used to effectively reduce the errors in navigational positioning results.With respect to the intermittent navigation signal problems that may frequently occur in reality,the pseudo-linear Kalman filter(MKF)algorithm is used to effectively solve the problem that least square and EKF algorithm cannot estimate the position status under the condition of discontinuous signals.First,the intermediate frequency signal is regarded as the software receiver input through the analysis of GPS signal structure and baseband signal processing principles to divide the software GPS receiver into six module,i.e.data reading,acquisition,tracking,navigation message demodulation,navigation pseudo-range measurement and navigation calculation.Besides,it makes a detailed planning for the functions of six modules,and also designs procedure to achieve the single-frequency single-point location solution.Next,in allusion to two problems,one is the GPS signal is largely influenced by the ambient noise,another is the navigation solution based on least square has a larger error,EKF algorithm is used to filter the random noise in navigation results.The experiment shows that,compared with the least square method,EKF algorithm effectively reduces the random noise in location results.Finally,for the issue that both least square method and EKF algorithm cannot conduct a navigation solution of the discontinuous signals under some environment,the carrier-to-noise ratio of intermediate frequency signal is used as the observable judgment basis to determine if the signal is available.Also,MKF algorithm is used to estimate the position status under the condition of discontinuous signals.Experiments show that MKF algorithm is frequently interrupted in one of four channel navigation signals.Indeed,it can still effectively guarantee the estimation of position state variables in rare moments when two channel signals show a short time interruption.Based on the software GPS receiver built in this study,the following conclusions are reached by comparing the least square method,EKF algorithm and MKF algorithm: the least square method can achieve the basic navigation solution,but the results contain a larger error.EKF algorithm can effectively reduce the solution error in navigational positioning,but either least square method or EKF algorithm cannot conduct the navigation solution under the condition of discontinuous signals.MKF algorithm discards the unavailable measured value through the carrier-to-noise ratio of real-time measurement signals,thus effectively ensuring the success of navigation solution under the condition of discontinuous signals.