This letter explores covariance matching-based adaptive robust cubature Kalman filter (CMRACKF). In this method, the innovation sequence is used to determine the covariance matrix of measurement noise that can overcome the limitation of conventional CKF. In the proposed algorithm, weights are adaptively adjusted and used for updating the measurement noise covariance matrices online. It can also enhance the adaptive capability of the ACKF. The simulation results are illustrated to evaluate the performance of the proposed algorithm.

中文翻译：

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基于协方差匹配的鲁棒自适应 Cubature 卡尔曼滤波器

这封信探讨了基于协方差匹配的自适应鲁棒体积卡尔曼滤波器 (CMRACKF)。该方法利用创新序列确定测量噪声的协方差矩阵，克服了传统CKF的局限性。在所提出的算法中，权重被自适应地调整并用于在线更新测量噪声协方差矩阵。它还可以增强ACKF的自​​适应能力。仿真结果被说明以评估所提出算法的性能。