让无人机在空中也能精准定位，靠的是动态识别静止状态进行修正。
C-ZUPT: Stationarity-Aided Aerial Hovering
- 通过设定不确定性阈值，自动识别空中近似静止状态，实现非接触式零速度更新。
- 实测显示该方法显著降低惯性漂移，使飞行更稳定，续航时间大幅延长。
- 特别适合电池有限的微型无人机，提升悬停效率和长时间飞行能力。
自主系统在多个领域对抗漂移的状态估计需求日益突出。尽管卫星定位和摄像头广泛应用，但在许多环境中可用性受限。因此，定位只能依赖惯性传感器，导致因传感器偏差和噪声随时间快速退化。为应对这一问题，需引入替代更新源（即信息辅助）作为确定性锚点。其中，零速度更新（ZUPT）在平台静止时能提供高精度修正，但传统方法仅适用于地面平台。本文提出一种面向空中导航与控制的受控零速度更新（C-ZUPT）方法，无需依赖地面接触。通过设定不确定性阈值，C-ZUPT可识别准静态平衡状态，并向估计算法提供精确的速度更新。大量验证表明，这些机会性的高质量更新显著减少惯性漂移与控制能耗。结果表明，C-ZUPT有效缓解滤波器发散，增强导航稳定性，实现更节能的悬停，显著延长持续飞行时间——对资源受限的空中系统具有关键优势。
原文摘要 · Abstract (English)
Autonomous systems across diverse domains have underscored the need for drift-resilient state estimation. Although satellite-based positioning and cameras are widely used, they often suffer from limited availability in many environments. As a result, positioning must rely solely on inertial sensors, leading to rapid accuracy degradation over time due to sensor biases and noise. To counteract this, alternative update sources-referred to as information aiding-serve as anchors of certainty. Among these, the zero-velocity update (ZUPT) is particularly effective in providing accurate corrections during stationary intervals, though it is restricted to surface-bound platforms. This work introduces a controlled ZUPT (C-ZUPT) approach for aerial navigation and control, independent of surface contact. By defining an uncertainty threshold, C-ZUPT identifies quasi-static equilibria to deliver precise velocity updates to the estimation filter. Extensive validation confirms that these opportunistic, high-quality updates significantly reduce inertial drift and control effort. As a result, C-ZUPT mitigates filter divergence and enhances navigation stability, enabling more energy-efficient hovering and substantially extending sustained flight-key advantages for resource-constrained aerial systems.
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