对比闭环与开环卡尔曼滤波在航空惯导中的性能优劣
Closed-loop vs. Open-loop Kalman Filter Architectures in Airborne Aided Inertial Navigation
- 用标准惯性导航机制比较开环与闭环架构的融合效果
- 高端传感器下开环滤波信息融合更平滑，低端则闭环更稳定
- 适合关注航空导航系统可靠性与设计权衡的研究者
闭环（或反馈）误差状态卡尔曼滤波器及其衍生结构是现代辅助惯性导航研究的主流。估计的惯性导航系统（INS）误差会持续反馈至INS，以修正后续预测的名义状态。相反，在安全关键的航空应用中，开环（或前馈）系统是公认的标准，其惯性解算严格解耦，以保障计算单元的操作独立性和故障隔离能力。本文使用标准的地心坐标系惯性解算和直接位置辅助，在多种惯性传感器误差特性（从消费级到导航级）下，评估该架构选择的性能影响。仿真结果展示了：在高端IMU下，开环滤波实现更平滑的信息融合；而在长期运行中，闭环架构表现出更强的稳定性。
原文摘要 · Abstract (English)
Closed-loop (or feedback) error-state Kalman filters with their relatives and offspring are the state-of-the-art in modern aided inertial navigation research. Estimated inertial navigation system (INS) errors are continually fed back to the INS to correct the nominal system state before subsequent predictions. Conversely, in safety-critical aeronautical applications, open-loop (or feedforward) systems are an undisputed standard, where the inertial mechanization is strictly decoupled to allow for operational independence and fault isolation of computing units. We assess the performance impacts of this architectural choice beyond qualitative system-safety justifications using a standard inertial mechanization in geodetic coordinates and direct position aiding. Simulations using a variety of inertial sensor error characteristics, ranging from consumer to navigation grade systems, showcase the trade-off between smooth information fusion for high-end IMUs using an open-loop filter and the inherent long-term stability of the closed-loop architecture.
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