Research On The Information Matching Problem And Tracking Algorithm In GNSS/INS Deeply Integrated Navigation System

As independent GNSS receivers always face the dilemma in choosing a bandwidthto satisfy both anti-jamming capability and dynamics adaptation, so the applicationrange of which have been limited。 GNSS/INS deeply integrated navigation systeminherits the INS-aiding and vector-tracking concepts, and fuses the basebandinformation from GNSS receiver’s correlators and INS information in a deep level,which was actually proposed to solve the problems in independent GNSS receivers andgreatly extend the application range of them. Generally, the GNSS/INS deepintegration can be divided into central architecture, coherent federated architecture andnon-coherent federated architecture, the non-coherent federated architecture was mostcommonly investigated, which was also the focus of this dissertation. In thisdissertation, GPS L1frequency and BD B3frequency signals were considered,baseband I/Q information and INS information matching problem, baseband signalprefilter algorithm and deep integration architecture problem have been investigated,main conclusions are summarized as follows:(1) Different information processing modules, such as baseband signal prefilter,code/carrier NCO control information computation, satellite position and velocitycomputation, GNSS/INS integrated navigation filter, INS, etc., are included in coherentor non-coherent federated GNSS/INS deeply integrated navigation system, the updatedfrequency of which are different from each other, however, the synchronization ofwhich is the necessary condition for implementation. After a profound analysis ofrelationships between each two modules, the synchronization problem was boiled downto INS information estimated Doppler frequency online interpolation or up-samplingproblem, and an extrapolation plus CIC(Cascaded Integrate Comb) filter method wasactually proposed to solve this problem, the simulation results showed that:extrapolation improved the precision of INS information estimated Doppler frequency;the single-cascade CIC was sufficient for Doppler frequency interpolation requirementin deeply integrated navigation system.(2) In non-coherent federated GNSS/INS deeply integrated navigation system, thecode and carrier discriminators outputs are considered as measurement information, themeasurement noise of the two kinds of discriminators would not be independent anylonger thereby violating the a priori condition of the Kalman filter. In this dissertation,we have proposed a double-filter based prefilter model, a4-dimension state filter isresponsible for code tracking whereas a3-dimension state filter is responsible for carriertracking, and a modified Kalman filter algorithm has been investigated to furtherimprove the tracking performance of the carrier-tracking-filter, which is obtained bymodifying the measurement noise variance of the carrier-tracking-filter based on the conditional joint probability density function of normalized I/Q measurements andcarrier to noise-density ratio estimation periodically. Simulation results of static fieldtest showed that, compared with traditional prefilter model implemented vector-trackingbased receiver, the double-filter based prefilter model improved the Doppler frequencytracking precision, position precison and velocity precision by about50%,20%and30%respectively, the model with modified Kalman filter alogorithm improved about90%,48%and80%respectively. Simulation results with complex GNSS/INS signalsimulator showed that, compared with traditional prefilter model implementedvector-tracking based receiver, the double-filter based prefilter model improved theDoppler frequency tracking precision, position precison and velocity precision by about35%,20%and37%respectively, while the modified Kalman filter alogorithm improvedabout85%,53%and71%respectively.(3) Generally, the normalized signal amplitude, carrier phase tracking error, carrierfrequency tracking error, carrier frequency rate tracking error and code phase trackingerror are included in the state space of traditional prefilter. In this dissertation, wehave put forward a simplified prefilter model to replace the traditional one, the statespace of this simplified prefilter model consists of only carrier phase tracking error,carrier frequency tracking error and carrier frequency rate tracking error. Simulationresults showed a more or less identical tracking and navigation performance of this twoprefilter implemented GPS/INS or BD/INS deeply integrated navigation systems,however, the simplified one has been reduced the computational complexity by67.8%.(4) The measurement errors of discriminators increase very rapidly whencarrier-to-signal, correspondently, the measurement information of non-coherent deeplyintegrated navigation system would become invalid. An optimization based trackingmethod was investigated to solve this problem in this dissertation, which implementedcarrier and code tracking without using any discriminators. Simulation results showedabout2.7dB GPS carrier tracking and2.6dB BD carrier tracking sensitivityimprovement over traditional Kalman filter based tracking method.Although the discussions in this dissertation were based on two classical frequencies ofGPS and BD signals, the corresponding algorithms or models would be applicable toother frequencies(such as GPS L5, BD B1and B2, etc.) or GNSS(such as GLONASS,GALLIEO, etc.).