针对非高斯噪声对卡尔曼滤波误差性能存在影响的问题，通过计算不同分布之间信息距离的方法来度量噪声分布序列的非高斯程度。分别针对符合高斯分布、均匀分布、伽马分布、瑞利分布的随机噪声序列，在噪声均值和方差相同的条件下，采用卡尔曼滤波算法进行仿真实验，考察其滤波结果的误差性能。实验结果表明：上述三种非高斯分布的非高斯程度不同；非高斯系统和高斯系统滤波结果的误差性能基本一致。

Non-Gaussian noise has effect on Kalman filtering accuracy, thus we measured the degree of some non-Gaussian noise distribution sequence by calculating the information distance between non-Gaussian and Gaussian distribution. Kalman filtering algorithm was used in simulation experiments for random noise sequence with different distributions，including Gaussian distribution，uniform distribution, Gamma distribution and Rayleigh distribution, which had equal mean value and equal variance. And the error performance of the filtering result was studied. The result of simulation showed that: 1) the non-Gaussian degrees of the three non-Gaussian distributions mentioned above are different with each other; and 2) the error performance of non-Gaussian system is basically the same as that of the Gaussian system.