RSS-Based Localization using A Single Robot in Complex Environments
RSS-Based Localization using A Single Robot in Complex Environments
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DOI：
10.1109/dcoss54816.2022.00065
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Hongzhi Guo;Irvin Quartey;Cameron Green
中科院分区：
文献类型：
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作者：
Hongzhi Guo;Irvin Quartey;Cameron Green
本文研究了在未知的复杂环境中，利用具有单接收天线和单通信信道的机器人定位静态发射机的问题。使用到达时间（TOA）和到达角度（AOA）的现有解决方案依赖于具有多个接收天线或多个通信信道的复杂无线通信系统，这对于具有现成的低成本无线电的机器人是不可用的。本文提出了一种利用接收信号强度（RSS）估计未知信道模型参数的定位框架，该框架考虑了多径衰落和空间相关阴影效应。机器人沿着预定义的轨迹移动以收集RSS数据。AOA信息也被估计并与机器人SLAM（同时定位和地图构建）结果相结合，以提高定位精度。在室内环境中进行了数值模拟和实验。结果表明，在10 × 10m2的区域内，对任意放置的发射机，90%的估计误差小于2m。
This paper considers the problem of localizing a static transmitter using a robot with a single receiving antenna and a single communication channel in unknown complex environments. Existing solutions using Time-of-Arrival (TOA) and Angle-of-Arrival (AOA) rely on complex wireless communication systems with multiple receive antennas or multiple communication channels, which are not available for robots with off-the-shelf low-cost radios. This paper develops a localization framework using Received Signal Strength (RSS) to estimate unknown channel model parameters considering multipath fading and spatial-correlated shadowing effects. The robot moves along a predefined trajectory to collect RSS data. AOA information is also estimated and integrated with the robot SLAM (Simultaneous Localization and Mapping) results to improve the localization accuracy. Numerical simulations and experiments in an indoor environment are conducted. Results show that 90% of the estimation error is smaller than 2 m to localize a randomly placed transmitter in a 10 × 10 m2 area.