自适应卡尔曼滤波器渐消因子选取方法研究

New method for selecting adaptive Kalman filter fading factor

分析了通过改变噪声和初始条件抑制Kalman滤波发散的方法,指出了造成Kalman滤波发散的原因和控制Kalman滤波发散的机理。推导了衰减记忆滤波方程并研究了衰减记忆滤波噪声阵和滤波初值的选取条件,分析了衰减记忆滤波条件下量测噪声阵遗忘因子权重变化的物理意义。给出了衰减记忆滤波不发散的自适应遗忘因子的新算法,仿真结果证明了所述方法的有效性。

A new algorithm of adaptively adjusting the fading factor for filter without divergence is presented. First the reason of Kalman filter divergence and the principles of divergence restraining schemes are discussed in detail, then the physical meaning of observation noise covariance matrix with an exponential weighting factor is analyzed, and a lemma is proved. The advantage of the new method is that fading factor adjusting simple and precise. Simulation results show the effectivencess of the new method.