| Summary: | 碩士 === 元智大學 === 電機工程學系乙組 === 107 === Research on the wireless fingerprint-based positioning and wireless channel modeling have become the significant topics recently. However, those two research area usually require huge time-series measured data, either received signal strength (RSS) or channel state (CS). It is quite difficult to obtain enough data by employing human to accomplish the measurements. Therefore, an iRobot-based automation measurement system (AMS) of wireless signal strength is established in this thesis. In an area smaller than 5mx5m, one unmanned surveillance AMS can measure RSS of WiFi and 4G signals with a charging station and virtual boundaries. The time of measurement, calculated coordinates, SSID of WiFi access point, and WiFi or 4G RSS are sent back to backend data server automatically as the iRobot comes back to the charging station. In order to obtain more accuracy physic coordinates, a light detection and ranging (LiDAR) device is used as an external position sensor to estimate the position of the vehicle carrier. The error characteristics of the calculated position against the actual position is analyzed and minimized. In the future, the physical coordinates using LiDAR can be integrated into the AMS system and form a useful wireless signal measurement system to obtain the data required by ireless fingerprint-based positioning and wireless channel modeling researchers.
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