Abstract
In order to improve the accuracy of attitude of unmanned aerial vehicle (UAV) navigation system in dynamic environment, an attitude calculation algorithm based on acceleration correction model is proposed. First, the acceleration correction model is established to calculate the estimated non-gravitational acceleration and external non-gravitational acceleration to modify the output value of the accelerometer, which reduces the influence of non-gravitational acceleration on the attitude calculation in dynamic environment. Then, the attitude calculation model based on Kalman filter is built, attitude angle calculated by corrected acceleration and magnetometer as measurement of filtering model, and the attitude calculation algorithm based on the acceleration correction model is designed. The experimental results show that the algorithm can reduce the interference of non-gravitational acceleration to attitude calculation, which avoids attitude angle divergence of UAV navigation system in dynamic environment, and improves the accuracy and anti-interference ability of UAV navigation system in dynamic environment.
Highlights
In order to improve the accuracy of attitude of unmanned aerial vehicle ( UAV) navigation system in dy⁃ namic environment, an attitude calculation algorithm based on acceleration correction model is proposed
The acceleration correction model is established to calculate the estimated non⁃gravitational acceleration and external non⁃gravitational acceleration to modify the output value of the accelerometer, which reduces the influence of non⁃ gravitational acceleration on the attitude calculation in dynamic environment
The attitude calculation model based on Kalman filter is built, attitude angle calculated by corrected acceleration and magnetometer as measure⁃ ment of filtering model, and the attitude calculation algorithm based on the acceleration correction model is de⁃ signed
Summary
西北工业大学学报 Journal of Northwestern Polytechnical University https: / / doi.org / 10.1051 / jnwpu / 20213910175 通过图 4 可以看出,加速度计原始模值 G1 相对 标准重力加速度模值 Gideal 偏差程度最大,波动范围 为 8 ~ 13 m / s2,说明非重力加速度不为 0,无人机在 该段时间内做变加速运动。 比较 G2,G3 和 G4 的偏 离程度,由于 GPS 更新频率低,G2 数值跳变剧烈,G3 曲线在初始阶段与 G4 曲线重合,但 G3 的误差在 1 s 后逐渐大于 1 m / s2,说明估计非重力加速度仅能在 短时间内修正非重力加速度的干扰,G4 的偏离程度 最小,对非重力加速度估计最为准确。 选取时长为 105 s 的实验数据对本文所设计的 基于加速度修正模型的无人机姿态解算算法进行验 证,并与 参考姿态角进行对比。 参考姿态角记为 αref,本文所设计算法输出姿态角记为 αProp。 加速度 计原始模值如图 5 所示,姿态角对比图如图 6 所示。
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