摘要
Geomagnetic orbit determination fits for nanosatellites which pursue low cost and high-density ratio,but one of its disadvantages is the poor position accuracy introduced by magnetic bias.Here,a new method,named the fuzzy regulating unscented Kalman filter(FRUKF),is proposed.The magnetic bias is regarded as a random walk model,and a fuzzy regulator is designed to estimate the magnetic bias more accurately.The input of the regulator is the derivative of magnetic bias estimated from unscented Kalman filter(UKF).According to the fuzzy rule,the process noise covariance is adaptively determined.The FRUKF is evaluated using the real-flight data of the SWARMA.The experimental results show that the root-mean-square(RMS)position error is 3.1 km and the convergence time is shorter than the traditional way.
地磁定轨系统适合于对仪器复用率要求高的微纳卫星使用。考虑到地磁定轨系统的性能受限于地磁偏差,本文设计了模糊调节器,并构建了模糊调节无迹卡尔曼滤波器。将地磁偏差建模为随机游走,并将其变化率作为调节器的输入量,经模糊处理后,自适应调节滤波器的参数。SWARMA卫星的实测数据实验表明,该算法可有效提升地磁偏差的估计精度,从而提升地磁定轨系统的性能。相较于传统的无迹卡尔曼滤波器,该算法的收敛速度更快,精度也更高,其位置误差均方根值为3.1 km.
基金
supported by the National Natural Science Foundation of China(No.61673212).
