Research on Key Technologies of Passive Positioning System for Personnel under Intelligent Modeling

The frequent disappearance of outdoor explorers has made the research on outdoor positioning search and rescue systems more and more interesting. LoRa geolocation for outdoor tracking purposes has greatly improved the LoRa spatial positioning accuracy for high-precision differential algorithms under the machine learning model. In the process of improving the 5 sets of data to 8 sets., the positioning performance is the best when there are 5 sets of data. Considering the roadmap and under the condition of visual distance, if you want to continue to improve the accuracy, it is obvious to increase the number of groups, but the computing power of the Drone base station processor is relatively high, so a moderate group is the best.

I. Introduction

With the continuous deepening of the Internet of Things technology in the industry, positioning technology plays an indispensable role in many fields such as transportation, agriculture, and rescue. There is a demand for the Internet of Things, and positioning technologies such as Wi-Fi [2], Bluetooth, infrared, RFID [1], UWB [3] are aimed at indoor positioning, and have advantages and disadvantages in positioning accuracy, transmission distance and power consumption [4], and cannot fully meet the needs of the existing IoT industry. This paper designs a positioning system composed of LoRa ranging and RTK equipment on Drone [8] for the search and rescue of trapped people. Table I. Localization performance comparison

Algorithm	Precision	Distance	Demerits
Wi-Fi	General- precision	50m	It's easily affected by the environment and consumes lots of power.
Bluetooth	high- precision	20m	The system is strictly synchronized, the implementation cost is high.
Zig-bee	high-precision	200-1000m	Time synchronization between positioning base stations requires high
LoRa	General-precision	20km	hardware costs. greatly affected by the environment.