Research On GPS Software Simulator And Positioning Solution Algorithm

GPS simulator study has entered the simulation of complex scenarios abroadat present, such as high dynamic, urban environment, trees dense and aircraft attitudechanged complexity. Although many domestic manufacturers and universities areresearching GPS simulator, its achievements is few on special scene. Due to theblockade of technology on simulator from foreign, it directly restricts the research andapplication of the navigation and positioning. On the other hand, many applicationssuch as Location Based Service (Location Based Service, LBS), mobile AugmentedReality application (Augmented Reality, AR), military command exercises and theactual combat, and target tracking and attacking, accurate position information is keyto realize these applications. The error of traditional positioning solution algorithm islarge on high dynamic scene, urban environment and intensive scene, even couldn’tposition.Therefore, this paper has two aspects of work, developing on GPSintermediate frequency signal source and researching GPS positioning solutionalgorithm, the main work is as follows:The development of GPS intermediate frequency signal source.Introducing theprinciple and structure of GPS signal. Analyzing signal model from signal emission,transmission, reception and the process of receiver handling. Expounding the detailedparameters of the first, second, third data blocks which are constituted navigationmessage. The simulation realization of C/A code, carrier and navigationmessage,prediction of visible stars,which is based on MATLB platform.Completingmodulo-2addition between the navigation message and C/A code.Furthermore,realizing the BPSK modulation of carrier, producing simulated1.405MHzintermediate frequency signal.Validation of the GPS intermediate frequency signal source. Completingvalidation of capture, tracking, bit synchronization and frame synchronization aboutintermediate frequency signal. Selecting captured NO.10,20satellites, compared withpresetted chips and doppler, it shows that the code and doppler are correct.Contrast tothe tracking output of in-phaseI pand quadratureQ pbranch, the results show thatthe datas exist in the navigation message.By process of bit synchronization and framesynchronization, compared the original ephemeris files with demodulated ephemerisdata among various parameters, the results show that the extrapolation ephemerisdatas are correct. Therefore, completing the validation of code, carrier and thenavigation message on intermediate frequency signal source. The study of nonlinear filtering algorithm in positioning solution. On the basis ofanalyzing,simulating and contrasting Least Square to Extended Kalman Filter(Extended Kalman Filter,EKF) algorithm. As for problems of EKF filtering modelinaccurate or dynamic mutation frequency of the object, which lead to largepositioning error and even divergence, hence, putting forward fading EKF (AFEKF)algorithm based on adaptive system noise, and using Strong Track Extended KalmanFilter (STEKF) algorithm and Unscented Kalman Filter (UKF) algorithm inpositioning solution. Under the condition of the smaller observation noise covarianceR and smoothness of EKF algorithm, by experiments based on Visual C++platform,compared to FEKF and EKF,AFEKF can inhibit mutation better. Meanwhile,STEKFinhibit the object mutation more obviously than EKF, although there is a bigpositioning error instantaneously, it converges quickly.The case of setting larger R, byexperiments with object frequent movement mutations, the results show thatcompared with FEKF algorithm, AFEKF algorithm can suppress mutation better.STEKF can track object movement strongly when divergence appears in EKF.Finally,by setting the complex circular motion experiments, the results show that UKFpositioning accuracy and stability are better than EKF when object is mutating.