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The navigation accuracy in the aerobraking phase of Mars mission is limited by atmospheric drag uncertainty. In this paper, an adaptive kalman filter is presented to cope with this uncertainty based covariance-matching method. By matching the theoretical covariance with the sampling covariance of the residual of the measurement, the process noise covariance is estimated. In addition, a Chi-Square test is used to evaluate the effectiveness of the process noise covariance estimation. Another advantage of Chi-Square test is that it can improve the computational capability of adaptive kalman filter by avoiding unnecessary updating process noise covariance.

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