Navigation Algorithms Of F-SINS&GNSS Deep Integrated System

Strapdown inertial navigation system(SINS) which is self-contained can implementreal-time positioning in all weathers while the accuracy of the global navigation satellitesystem(GNSS) is independent of time although it have to rely on satellite signals to achievepositioning. Therefore, by integrating these two systems, the performance can be greatlyimproved. Specifically, the ultra-tight SINS/GPS integration can not only improve positioningaccuracy in the long run but also maintain high precision in situations of weak signals or highdynamic. This dissertation focuses on the closed loop algorithm and data fusion algorithm inultra-tight SINS/GPS integration system conducted the following discussions and researches.Firstly, the dissertation analyzes the navigation equations of fiber optical SINS. Thenavigation equations in the earth centered frame are selected based on the features of theultra-tight SINS/GPS integration system. The influences of fiber optical gyroscope on theaccuracy of SINS are also analyzed. Related simulation results are given in detail.Secondly, the dissertation elaborately explores the composition and structure of theultra-tight SINS/GPS integration system and compares systems in different deep integrations.Based on that, the mathematical models of different deep integrations are illustrated.Definition of deep integration system is concluded, and the reasons of Federal system areincluded in deep integration are provided.Thirdly, the observability of the SINS/GPS integrated navigation system has beenstudied. Due to the complexity of observability model in deep integration system, it ispreferred that the model is not involved in observability analysis. The dissertationdemonstrates the effects of observability matrix on observation matrix. Therefore, the systemobservability when the corresponding position of observation matrix is unit matrix areanalyzed and the system abservability when transform the observation matrix to the unitmatrix are analyzed, separately.Fourthly, the weak signal acquisition issue when SINS aids GPS receiver in highdynamic situations is studied. In order to efficiently capture GPS signal, the40ms coherentintegration is adopted. In order to break through the navigation data to the long coherent time,loop remove and flip method are adopted. The data synchronous issues in SINS/GPS deepintegrated system are studied by providing the same frenquency data to receiver channels, andforcing the outputs of each channel and the represent system state are strictly the same in time.Moreover, In order to finish the relative of signals, stripped the C/A code in receiver by adopting changed C/A code phrase in the internal of each channels.Fifthly, the navigation algorithm for ultra-tight SINS/GPS integrated system withunknown inertial sensors noise statistical properties is researched. First of all, the logarithmiclikelihood function containing systematic noise statistical properties is designed based on themaximum Likelihood criteria. Then by applying maximum expectations algorithm, the noiseestimation issue is turned into problem of maximizing the expectation of logarithmiclikelihood function. This leads to the adaptive sigma-points Kalman filter(SPKF) algorithm,which provides navigation information and estimates inertial sensor error variance on-line atthe same time. This further corrects and updates the integrated navigation system.Lastly, the dissertation studies the situation when sudden changes exist in ultra-tightSINS/GPS integrated system. Based on the restrain of matrix on the memory length offiltering algorithm and adjusting matrix adaptively, the augmented UKF with adaptive fadingmatrix can be obtained. This algorithm can effectively inhibit the adverse effects of systemstates mutation. The adaptive fading matrix is designed according to the orthogonality. Thecalculation is simplified based on the features of SINS/GPS integrated navigation system. Thefading matrix is applied to correct the corresponding variables, which makes the SINS/GPSintegrated navigation system immune to system states mutation. This algorithm can alsoimprove navigation accuracy when systematic noises statistical characteristics are uncertain.