仅用标量测量实现稳定姿态估计,且能补偿陀螺仪偏差
Scalar-Measurement Attitude Estimation on $\mathbf{SO}(3)$ with Bias Compensation
- 基于SO(3)设计非线性观测器,融合陀螺仪偏差补偿
- 两个标量测量在激励条件下即可实现姿态估计,静态时三个足够
- 对部分传感鲁棒,实测误差小,适合传感器受限场景
姿态估计算法通常依赖加速度计和磁力计等惯性传感器的完整向量测量。本文表明,仅使用标量测量也能实现可靠估计,这些标量自然来自向量读数的分量或其它传感模态的独立约束。我们提出了在SO(3)上的非线性确定性观测器,集成陀螺仪偏差补偿,并在合适的可观测性条件下保证一致局部指数稳定性。该框架的关键优势是对于部分传感具有鲁棒性:即使仅部分向量分量可用,仍可保持精确估计。在BROAD数据集上的实验验证了其在逐步减少测量配置下的持续性能,即便信息严重丢失,估计误差依然很小。据我们所知,这是首个建立基本可观测性结果的工作:在适当激励下,两个标量测量足以完成姿态估计;静态情况下,三个标量测量足够。这些结果使基于标量测量的观测器成为传统向量方法的实用可靠替代方案。
原文摘要 · Abstract (English)
Attitude estimation methods typically rely on full vector measurements from inertial sensors such as accelerometers and magnetometers. This paper shows that reliable estimation can also be achieved using only scalar measurements, which naturally arise either as components of vector readings or as independent constraints from other sensing modalities. We propose nonlinear deterministic observers on $\mathbf{SO}(3)$ that incorporate gyroscope bias compensation and guarantee uniform local exponential stability under suitable observability conditions. A key feature of the framework is its robustness to partial sensing: accurate estimation is maintained even when only a subset of vector components is available. Experimental validation on the BROAD dataset confirms consistent performance across progressively reduced measurement configurations, with estimation errors remaining small even under severe information loss. To the best of our knowledge, this is the first work to establish fundamental observability results showing that two scalar measurements under suitable excitation suffice for attitude estimation, and that three are enough in the static case. These results position scalar-measurement-based observers as a practical and reliable alternative to conventional vector-based approaches.
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