基于信息融合的大飞艇自适应姿态解算算法

现有计算大飞艇姿态角的平衡滤波算法虽然融合了加速度和角速度信息，但其未对加速度的适用条件进行分析，从而导致了积累误差和动态解算准确性问题.针对该算法的不足，提出了根据飞艇的不同运动状态来调整姿态解算算法的融合加速度和角速度数据的自适应姿态解算算法，并通过Matlab实验验证了算法的有效性.实验结果表明，该算法有效地解决了平衡滤波算法的不足，通过引入SMV(signalmagnitudevector，信号量向量)，使大飞艇的运动状态得到了准确判断，从而使积累误差问题得到了有效改善，同时提高了大飞艇的动态解算准确性.

The High Altitude Airship Self-adaption Gesture Calculating Algorithm Based on Information Fusion

Although the existing balance filtering algorithm for calculating the high altitude airship gesture angle has fused the acceleration information and the angular velocity information， it did not analyze the application conditions of the acceleration， resulting in accumulation errors and dynamic solver accuracy problems. In order to solve these problems， a self adaption gesture calculating algorithm was put forward. According to the airship’s different motion states， the proposed algorithm integrated the acceleration and angular velocity data to adjust the gesture calculate algorithm. The validity of this algorithm was verified by the Matlab experiments， and the experimental results showed that this algorithm had effectively solved the weakness of the existing balance filtering algorithm. As introducing the concept of SMV (signal magnitude vector)， the high altitude airships’ motion states were judged accurately， and it also improved the accumulation errors problem and enhanced the dynamic solver accuracy of the high altitude airship.