| Mini-Uumanned Aerial Vehicle which concerned and researched more and more reflect the new technology combined many technology such as aerial, control, computer, navigation and communication. For the navigation of MUAV, GPS/MIMU becomes main trend gradually since it's accuracy and reliability.However, there are two factors effect the accuracy. First, MIMU would produce gross error while effect by the environment since it's finited accuracy, while the error function will show nonlinearity since zero offset and random noise. Then, residual series are normally distributed which is ideal in the navigation of GPS/MIMU based on normal kalman filter. Appearance of many gross error produced by model error and observed error would bring bad consequence to state estimate of MUAV.Therefore, the paper study on theory and method of dynamic data processing and integrated navigation.based on robust estimate and adaptive estimate.First, Robust and adaptive estimate are applied to kalman filter, and three-stage equivalent weight function are design based on of equivalent weight according to navigation of MUAV. Observed information are applied reasonable while the gross error are inhibit according to statistics. Also adptive factor are designed based on discrepancy, in order to balance the contribution and control the influence of state model error and observed error. Then, the paper produced UKF based on robust and adaptive estimate which improve the distribution of sigma points and reduce the state estimate error while improve the accuracy of state estimate. Also, robust adaptive UKF is designed based on interated observed update which the estimate value and covariance are applied to resample. This strategy improve the sigma points distribution.The simulation show that robust adaptive filter could inhibit the effect of gross error while the UKF could reduce the effects of model error, therefore improve the estimate accuracy of MUAV, test and verify the rationality and validity. |
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