蓝牙相控阵辅助惯性导航的因子图方法：实验验证
Bluetooth Phased-array Aided Inertial Navigation Using Factor Graphs: Experimental Verification
AI总结：
本文通过多旋翼无人机实验数据，比较了基于因子图优化的稳健估计策略，评估蓝牙角测量在GNSS信号丢失情况下的导航性能。
摘要：
相控阵蓝牙系统已作为一种低成本替代方案，用于在GNSS受限场景如仓库物流、无人机着陆和自主对接中实现辅助惯性导航。基于商用组件构建导航系统可能降低相控阵无线电导航系统的进入门槛，但以显著更嘈杂的测量和相对较短的可行范围为代价。本文通过多旋翼无人机飞行收集的数据，比较了基于因子图优化的稳健估计策略。我们评估了在GNSS信号丢失情况下，通过蓝牙角测量、距离或气压辅助的导航性能。
英文摘要：
Phased-array Bluetooth systems have emerged as a low-cost alternative for performing aided inertial navigation in GNSS-denied use cases such as warehouse logistics, drone landings, and autonomous docking. Basing a navigation system off of commercial-off-the-shelf components may reduce the barrier of entry for phased-array radio navigation systems, albeit at the cost of significantly noisier measurements and relatively short feasible range. In this paper, we compare robust estimation strategies for a factor graph optimisation-based estimator using experimental data collected from multirotor drone flight. We evaluate performance in loss-of-GNSS scenarios when aided by Bluetooth angular measurements, as well as range or barometric pressure.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
