附加运动学约束的BDS抗差UKF导航算法

针对城市复杂环境中单一BDS导航受多路径（multipath，MP）和非视距（non-line-of-sight，NLOS）信号干扰导致精度下降的问题，提出一种附加运动学约束的抗差无迹卡尔曼滤波（unscented Kalman filter，UKF）算法。该算法基于新息向量构造等价权函数，克服了位置及接收机钟差初值不准确引起的抗差性能下降问题。同时，利用载体的近似运动方向和高程约束，进一步增强滤波解。实测车载试验结果表明，本文方法可有效抑制MP和NLOS信号的干扰，提高城市环境中的BDS导航精度。

Robust UKF algorithm with motion constraint in BDS navigation

In a complex urban environment,navigation based on single BeiDou navigation satellite system (BDS) will be interfered by multipath (MP) and non-line-of-sight (NLOS) signals, which degrades the accuracy of positioning. In order to solve this problem, a robust unscented Kalman filter (UKF) with motion constraint is proposed. The algorithm constructs an equivalent weight function based on the innovation vector, which will overcome the problem of performance degradation of conventional robust method caused by inaccurate initial values of the position and receiver clock offset. In addition, the approximate moving direction and elevation of the carrier are used to further enhance the filtering solution. The actual on-board experiment results show that this method can effectively suppress the interference of MP and NLOS signals, and improve the accuracy of BDS navigation in urban environments.