A Kalman Filtering Algorithm for Precision Real-Time Orbit Determination with Space-Borne GPS Measurements
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摘要: 在动力学模型补偿算法的基础上,推导了星载GPS实时定轨的卡尔曼滤波模型。以此为理论基础,自主研制了星载GPS实时定轨软件SATODS。使用CHAMP卫星上的星载GPS实测伪距数据以及GPS卫星广播星历来模拟实时定轨数据处理,并将实时定轨结果与JPL精密轨道进行比较分析。结果表明,在滤波收敛后,实时定轨的轨道精度和速度精度的3dRMS分别可达到1.0m和1.2mm/s,受观测数据的GPS卫星数、PDOP值、粗差数据和数据中断等因素的影响较小。Abstract: At present,space-borne GPS receivers have gradually evolved into a standard tracking system for low Earth orbiting (LEO) satellites.In order to produce high accuracy onboard navigation solutions continuously,an extended Kalman filtering model of real-time orbit determination with space-borne GPS measurements is firstly derived based on the dynamic model compensation method,and relevant software named SATODS is developed subsequently.Then a simulative test was carried out using broadcast ephemerides and space-borne GPS dual frequency pseudo-range data from CHAMP satellite with SATODS.The results compared with JPL RSO demonstrate that real-time orbital accuracy about 1.0 m for satellite position and 1.2 mm/s for velocity (3 d RMS) is feasible with dual-frequency code measurements.In addition,it is hardly subjected to data quality of GPS observation such as the number of GPS satellite and the value of PDOP,and so on.
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