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Solar-powered unmanned aerial vehicles usually fly at high altitudes, and they are mainly powered by the photocells covering the body of unmanned aerial vehicles. Considering that the solar vector cannot be affected by the disturbing magnetic field and harmful acceleration, a unit solar vector solving method based on photovoltaic array is proposed in this paper. The photocells with different installation angles are selected to form the photovoltaic array. The solar vector is solved by the least-squares method on the basis of normalization by using the output currents of the photovoltaic array. For eliminating the influence of faults and reflected light on the solving of the solar vector, an adaptive least-squares unit solar vector solving method is proposed. In addition, a solar vector measuring device is designed in order to verify the effectiveness of the proposed methods. By employing the structural advantages of the device, the current generated by the reflected light of the sky can be solved according to the currents generated by all photocells of this device. Thus, the solved current generated by the reflected light of the sky is more accurate. Moreover, strapdown inertial navigation system/solar vector/global positioning system integrated navigation Kalman filtering algorithm is proposed, in which the adaptive least-squares unit solar vector solving method is applied to the measurement update of the filter. The effectiveness of the methods proposed in this paper is illustrated by some numerical and physical simulations.

The attitude measurement systems composed of magnetic, angular rate and gravity sensors in the navigation system of an unmanned aerial vehicle are vulnerable to disturbed magnetic field observations. In this paper, an anti-interference integrated navigation federal Kalman filter is designed with fusing the information of microelectromechanical-system-based strapdown inertial navigation system, gravity field, geomagnetic field and solar vector (direction of sun). The filter works in the mode of fusion reset or no reset according to environmental conditions or manual setting. In addition, the characteristic is discovered that disturbed magnetic field observations can interfere with the state estimation covariance matrixes of quaternions, which in turn affect the fusion update of estimated quaternions in no reset mode of the federal filter. In order to eliminate the effect of magnetic field observations on the attitude information of pitch and roll angles, a method of correction update for a yaw angle component in quaternions using the magnetometer is designed, and an Euler angle information fusion method is developed by constructing a pseudo-covariance matrix of Euler angels in fusion update of the filter. Thus, when there exist disturbed magnetic field observations and the filter is in no reset mode, the estimated pitch and roll angles of the main filter after fusion update are not affected, and the yaw angle estimation errors of the main filter decrease relative to the estimation errors of the sub-filter which is corrected by a magnetometer. The effectiveness of the algorithm is illustrated by a numerical simulation and a semi-physical simulation.