Outdoor location method based on LoRa technology

Abstract

The present invention relates to an outdoor location method based on a LoRa technology, belonging to the field of wireless location. The method comprises the steps of: employing a BP neural network toperform correction of obtained RSSI (Received Signal Strength Indication) measurement values of LoRa signals; employing the corrected RSSI values, and performing dynamic optimization of parameters ofa LoRa path loss model Z to allow the Z to be suitable for different location environments; employing the trained Z to combine with a linear location model G based on the RSSI to establish a LoRa location linear model L3M based on the RSSI and obtain an initial location result set R of a target node; employing an L3M-C location model to perform clustering processing of the R and obtain a locationresult set R1; employing an L3M-MRE location model to perform minimum estimation RSSI error selection for the R and obtain a location result set R2; and employing an L3M-W selection strategy locationmodel to perform minimum mean estimation RSSI error selection for the R1 and the R2 and obtain the optimal estimation position of the target node. In an outdoor environment, the influence of NLOS errors and environment noise on signal propagation is reduced, and the location precision is improved.

Description

technical field [0001] The invention belongs to the field of wireless positioning, and relates to an outdoor positioning method based on LoRa technology. Background technique [0002] IoT applications increasingly require location, such as device tracking or smart cities, which require geolocation. According to Machina Research, the Internet of Things will have more than 1.5 billion connected devices by the end of 2020. About a third of these will rely heavily on geographic data, and 60% of applications will likely include geographic data. [0003] So far, the main technologies available for IoT object location are Bluetooth, GPS and GSM. At present, most positioning and tracking methods use Bluetooth technology for positioning and tracking, but the transmission distance of Bluetooth is only 10m to 100m, the transmission distance is too short, and at the same time, the power consumption is large, making it difficult to effectively track and locate. The common method of ge...

AI Technical Summary

Problems solved by technology

In the environment, there are two main factors affecting RSSI positioning accuracy: (1) There are a large number of obstacles in the actual positioning scene, and the propagation signal will be affected by non-line-of-sight propagation during positioning (2) Signal propagation characteristics in the positioning scene As the environment changes, it is difficult for fixed path attenuation module parameters to fully and accurately reflect the influence of the environment of the entire positioning area on the signal

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