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Weak GPS Signal Processing And Autonomous Navigation Of High Earth Orbits Spacecraft

Posted on:2012-06-04Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y J XieFull Text:PDF
GTID:1112330368982464Subject:Navigation, guidance and control
Abstract/Summary:PDF Full Text Request
Autonomous orbit determin ition with GPS could provide the real time and high precision orbit data of LEO spacecraft. High earth orbit spacecraft's autonomous orbit determination with GPS has been in research internationally, it needs to further study. So to start the research of high earth or(?)it spacecraft's orbit determination with GPS can improve the precision of orbit determination, has important practical significance and high application value. It also will be the theoreti(?)al basis for future application. Based on high earth orbit determination with GPS, this article introduces signal performance of GPS signal on the HEO, GPS acquisition and tracking, the technique for using GPS to determining HEO and GEO orbits. The main work is as follows:This article analsis GPS sig(?)al characteristics in high orbit. This paper studies orbit altitude, orbit eccentricity, orbit inclination and the GPS receiver's sensitivity how to influencing GPS signal charactrist(?)s. According to the simulation result, at the perigee of the orbit, receiving signals has high (?)arrier to noise ratio and more visible star number, high dynamic, and the higher precisio(?) at the apogee of the orbit, receiving signal is weak, visibility is bad, the dynamics is no(?)better than the ground users, positioning accuracy is poor. Under the fixed number of orbit,(?)n order to improve the receiver of capture and tracking performance, it needs to improve the sensitivity of the receiver.In order to acquire the weak and high dynamic GPS signals in high earth orbit, this paper introduces a Doppler frequency shi(?)t assisted BAP algorithm. According to the spacecraft and GPS star orbits and velocity inforn ation calculated the orbits of the rough value of Doppler frequency shift, use this value c(?)py local C/A code for yards compensation, lower the influence of dynamic; On the rough value of Doppler frequency shift±10KHz around on carrier Doppler frequency shift sea. ch, effectively reduced the time that required to acquire. The simulation results show that th s algorithm can acquire GPS signal with earrier to noise ratio to 21dB-Hz in high dynamic c(?)nditions.For tracking GPS signals in (?)igh orbit, this article introduces an adaptive two stages improved square root extended Ka(?)nan filtering algorithm. The existing two stage extended kalman filter algorithm(AT-EKF) can solve the problem when pseudorange rate and pseudorange rate statistical parameter uncertainty change, but when there is large error in the observations and process covariar ce matrix is not positive definite will lead to low positioning accuracy, and even cause filtering divergence. Considering the above problems, this paper proposes using the last moments state to linear the nonlinear equations, to avoid the large observation error to influence of filtering, and using the method of square root filter Kalman. filtering is effective to prevent the filter divergence. This paper deduces formula of AT-MSREKF filtering algorithms. Simulation results show that AT-MSREKF algorithm obviously improved tracking precision in high dynamic conditionsFor processing large amount datas, the noise problem of input and output data, the large amount of calculation to the real-time updating sample, this article introduces an fuzzy clustering method based on the dynamic online NRLFSVR algorithm. It will be used for adapting the kalman filter. The simulation results show this algorithm can improve the calculation precision, but needs a little more time-cosuming.For the geostationary orbit (GEO), the received GPS signal is weak but the dynamic is not high, so this article introduces an adaptive interger filter for determining GEO orbit. For HEO orbit, this article introduces an HEO orbit determining method. This method uses fuzzy clustering method based on the dynamic online NRLFSVR algorithm to adjust noise of process and observation, in order to achieve the purpose of filter stability. The simulation results show that the above two kinds of schemes can determining GEO and HEO orbit effective.
Keywords/Search Tags:acquisition, tracking, high earth orbit, least square support vector, Kalman filter
PDF Full Text Request
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