针对GNSS/SINS紧组合定姿定位系统在非高斯有色噪声环境下直接使用高斯混合扩展卡尔曼滤波（Gaussian mixture extend Kalman filter, GMEKF）出现的随机模型失配现象，提出一种顾及非高斯有色噪声影响的GMEKF优化算法。该算法在高斯混合模型对非高斯噪声近似的基础上，通过状态扩增和量测组差对非高斯噪声序列中的有色噪声成分进行白化处理，从精化随机模型的角度改善了GMEKF算法的性能。实验结果表明，在非高斯有色噪声环境下，相比于GMEKF，该算法对随机模型建模更准确，将其用于受非高斯有色噪声影响的定姿定位场合中可进一步提高导航解算精度。

We propose a Gaussian mixture extend Kalman filter (GMEKF) algorithm for non-Gaussian colored noise processing to solve the random model mismatch problem caused by non-Gaussian colored noise in GNSS/SINS tightly-coupled system. We discuss the approximation of non-Gaussian noise by the Gaussian mixture model and the principle of GMEKF. To further improve the performance of the GMEKF algorithm, we use state amplification and measurement difference to process the colored noise components in non-Gaussian noise. The experimental results show that the proposed algorithm outperforms GSEKF algorithm in terms of random model, and its estimation accuracy is better improved in GNSS/SINS tightly coupled integrated system under non-Gaussian colored noise environment.