载波平滑伪距紧组合导航系统鲁棒自适应滤波算法

Adaptive robust filtering algorithm for tightly-coupled integrated navigation system based on carrier phase smoothing pseudorange

传统惯性/卫星紧组合导航系统采用载波相位平滑伪距可以有效提高伪距观测量精度,但平滑伪距后观测量噪声不符合白噪声特性而导致卡尔曼滤波器容易发散;同时由于周跳的存在会更加严重影响滤波器的稳定性。针对上述问题,分析了平滑伪距噪声特性并建立了噪声模型,在此基础上设计了鲁棒自适应滤波算法对观测噪声进行实时估计和补偿,结合抗差估计理论进行滤波以减小观测量噪声水平和模型不确定对滤波器带来的影响。理论分析和仿真结果表明,在复杂环境下,基于载波相位平滑伪距的鲁棒自适应紧组合导航系统定位精度提高了一倍以上。

Based on the phase smoothing pseudorange theory, the measuring accuracy of INS/GNSS tightly-coupled integrated navigation system can be significantly improved. However, the observation noise of smoothed pesudorange doesn't meet the requirement of white noise in Kalman filter, which could lead to filter divergency. Meanwhile, the stability of Kalman filter could be seriously affected due to the existence of cycle slip. In order to resolve the above problems, this paper presents a new robust adaptive filter. First, the noise characteristic model is built for estimating and compensating measurement noise; then the robust estimation theory is applied based on the noise model to reduce the influence of non-Gaussian measurement noise and model uncertainty. Theoretical analysis and simulation results show that the adaptive INS/GNSS tightly-coupled integrated navigation system based on carrier phase smoothing code pesudorange provides higher accuracy, better dynamic performance than traditional tightly-coupled system under complex environment. The proposed method has improved the accuracy by more than 100%.