【作者】 谢燕军；

【导师】 袁赣南；

【作者基本信息】 哈尔滨工程大学 ， 导航、制导与控制， 2011， 博士

【摘要】 GPS自主定轨技术可以为各类中低轨航天器提供实时的、高精度的轨道数据,至于基于GPS的高轨道航天器自主定轨技术目前国际上尚处于探索之中,有待进一步深入研究。因此开展高轨道航天器GPS自主定轨技术的研究,对于改善定轨精度,提高航天器自主导航能力具有重要的现实意义和应用价值,也为将来的实际应用打下理论基础。本文主要从基于GPS的高轨航天器自主定轨技术出发,对高轨道GPS信号特征、高轨道GPS捕获及跟踪技术、基于GPS的地球静止轨道和高偏心率轨道技术进行了研究,主要工作如下：研究了高轨道上GPS信号的特征。本文详细研究了轨道参数中的轨道高度、轨道偏心率、轨道倾角及接收机灵敏度对GPS信号的可见性、动态性及定轨精度的影响。仿真分析表明,在航天器运行轨道的近地点处,GPS信号强度较强、可见性好、动态性较高、定位精度高；在航天器运行的远地点处,信号强度微弱、可见性较差、动态性较低、定位精度差。在航天器运行轨道确定的情况下,为提高可见性需提高接收机的灵敏度。为捕获高轨GPS信号,提出了一种多普勒频移辅助的BAP(Block Averaging Pre-processing)算法。该算法根据航天器和GPS星的轨道及速度信息计当前的多普勒频移值,用该估计值对本地复制C/A码进行码补偿,以降低信号动态性的影响；围绕当前估计值±10KHz的范围搜索载波多普勒频移值,以降低捕获所需的时间。仿真结果表明,该算法可捕获高动态条件下载噪比低至21dB-Hz的GPS信号。为跟踪高轨位置处高动态、微弱GPS信号,提出了一种自适应两阶段改进平方根扩展卡尔曼滤波算法(AT-MSREKF)。现有的两阶段扩展卡尔曼滤波算法(AT-EKF)可以很好的解决高动态环境下伪距率及伪距率变化率统计参数不确定性的问题但当观测结果存在较大误差以及滤波过程中协方差阵的不正定将会导致定位精度不高,甚至会导致滤波发散。本文针对上述问题,提出采用在前一状态时刻线性化非线性方程,从而避免观测误差较大对滤波的影响,采用平方根卡尔曼滤波方法有效的防止滤波发散的情况。仿真结果表明在高轨位置处AT-MSREKF算法明显提高了跟踪的精度。本文针对大规模样本数据、模型不稳定、模型输入输出均存在噪声及在线实时更新样本计算量大等问题,提出了一种基于核模糊聚类在线NRLFSVR算法。该算法将对高轨航天器定轨中的卡尔曼滤波器进行自适应调整。仿真结果表明该算法相对于基于聚类动态LSSVM算法可有效提高计算的精度,但耗费时间稍微增多。针对地球静止轨道(GEO),因动态性不高,只是所接收信号较微弱,提出一种自适应积分滤波的GEO定轨算法。对高偏心率轨道(HEO)航天器,提出一种HEO轨道定轨策略,该策略利用基于核模糊聚类在线NRLFSVR算法来自适应的修正卡尔曼滤波器的过程噪声与观测噪声方差,以达到滤波稳定的目的。仿真结果表明上述两种方案可有效的为GEO和HEO轨道定轨。更多还原

【Abstract】 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.更多还原