卫星导航定位卡尔曼滤波时延平滑方法研究

为进一步提高卫星导航定位精度和性能，介绍和讨论了卡尔曼滤波延时平滑方法，并建立了一种卡尔曼滤波延时平滑定位模型与算法。与经典卡尔曼滤波类似，该算法同样具有状态系统与测量系统两类方程，能够根据后续历元测量值及定位结果向前进行逆向预测与更新，从而达到对整体定位过程再次平滑的目的，更大程度地获得定位结果跟随性与平滑性之间的平衡。通过多种不同情况下的GPS实测试验，对方法的正确性和可行性进行了分析与验证。结果表明，卡尔曼滤波延时平滑定位方法能够适用于多种静态、动态导航应用领域，使输出结果更为平滑和准确，在有效提高定位精度的同时具有更强的抗多径和抗干扰性。

Study on Kalman Filtering Time-lag Smoothing Method in Satellite Positioning

In order to improve the accuracy and performance of satellite navigation positioning,a method of Kalman filtering time-lag smoothing was introduced and discussed,and a Kalman filtering smoothing positioning model and its algorithm were built in this paper.Similar to classical Kalman filteing,the algorithm also has two kinds of equations-status system and measuring system,which could help to predict and update backward on the basis of follow-up epoch measured values and positioning results,thereby the overall positioning process can be smoothed again so that we can obtain the balance between positioning result tracking and smoothing performance.The paper analyzed and verified validity and feasibility of the method on the basis of GPS field experiment in various circumstances.Experiment results indicate that Kalman filtering time-lag smoothing positioning method can be adopted in various static and dynamic state navigation application field,which could make position results more smooth and accurate.The method has better anti-multipath and anti-interference performance, and it could also effectively improve positioning accuracy.