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GPS-Based Real-Time Orbit Determination of Low Earth Orbit Satellites Using Robust Unscented Kalman Filter

机译:基于GPS的鲁棒无味卡尔曼滤波器确定低地球轨道卫星的实时轨道

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In this research, a novel algorithm for real-time orbit determination (RTOD) is presented using the robust unscented Kalman filter (RUKF) with global positioning system (GPS) group and phase ionospheric correction (GRAPHIC) observables. To increase the reliability of the solution, a robust approach is included in the UKF to cope with the bad, invalid, or degraded measurements leading to the divergence or inaccurate output of the filter. Robustness is provided by making the filter less sensitive to faulty measurements using a scale matrix that is multiplied with the covariance matrix of the observation noises. Real data collected during a massive solar storm are used in the algorithm. For external validation, the outputs of RUKF and classical UKF are compared with the precision orbit ephemerides of the Challenging Minisatellite Payload (CHAMP). The results show that RUKF slightly outperforms classical UKF and possesses the capability to be used as an efficient and reliable algorithm in case of bad observations or malfunctioning of the system. (C) 2017 American Society of Civil Engineers.
机译:在这项研究中,提出了一种新颖的实时轨道确定(RTOD)算法,该算法使用了鲁棒的无味卡尔曼滤波器(RUKF)和全球定位系统(GPS)组,并且可观测到相电离层校正(GRAPHIC)。为了提高解决方案的可靠性,UKF中采用了一种可靠的方法来应对不良,无效或性能下降的测量结果,从而导致滤波器的输出发散或不准确。通过使用比例矩阵乘以观察噪声的协方差矩阵,使滤波器对错误测量的敏感性降低,可以提供鲁棒性。该算法使用了大规模太阳风暴期间收集的实际数据。为了进行外部验证,将RUKF和经典UKF的输出与具有挑战性的微型卫星有效载荷(CHAMP)的精密轨道星历进行比较。结果表明,RUKF略胜于经典UKF,并且具有在观察不良或系统出现故障的情况下用作高效可靠算法的能力。 (C)2017年美国土木工程师学会。

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