双重自适应UKF在SINS初始对准中的应用

Application of Dual Adaptive UKF in Initial Alignment of SINS

对无迹卡尔曼滤波(UKF)算法进行了改进,提出一种双重自适应UKF算法.该算法能缩放噪声、平抑模型噪声;通过监测基于新息特性的自适应矩阵的迹并进行实时修改,达到抑制观测干扰的目的.仿真结果表明,双重自适应UKF算法对于模型噪声和观测干扰十分敏感,同时具有较强的鲁棒性,能快速对其进行平抑.

An improved unscented Kalman filter （UKF） algorithm is called dual adaptive UKF. It could not only stabilize model noise by the method of resizing noise, but also inhibit observation interference by monitoring the trace of the adaptive matrix based on innovation characteristics and amending the adaptive matrix in time. Simulation results show that the dual adaptive UKF algorithm is very sensitive to model noise and observation interference. And it has strong robustness which could stabilize the model noise quickly.