Research And Implementation Of Urban Environment Outdoor Location Method Based On LoRa

Outdoor positioning has been studied for decades.With the rapid development of the Internet of Things technology,the positioning management of Internet of Things devices has also become a research hotspot in recent years.Although the currently widely used global positioning system GPS has made significant progress in positioning accuracy,the high energy consumption of its positioning components conflicts with the low power consumption characteristics of IoT devices.In addition,mobile smart phones often use positioning solutions based on cellular networks,but their positioning accuracy is not satisfactory.With the rapid development of the Internet of Things technology,the emergence of LoRa spread-spectrum communication technology has brought new choices and inspiration to the communication and positioning problems of Internet of Things devices.LoRa technology is characterized by low power consumption and wide transmission range,and its characteristics exactly meet the energy consumption and communication requirements of IoT devices.At the same time,in the dense urban environment,the LoRa signal also shows the sensitivity to the environment,that is,when the signal transmitting end is located in different geographical environment,its communication link shows different communication quality.Considering the above characteristics of LoRa,this paper proposes a LoRa-based outdoor positioning scheme in an urban environment to solve the positioning problem of urban IoT devices.In the positioning scheme in this paper,according to the anisotropy of LoRa communication link quality in different environments and the stability shown at the same location,the PRR of the gateway at different data sending points is used as the fingerprint associated with its location Information,combined with the improved particle filter algorithm proposed in this paper,the fingerprint information collected can be tracked and matched to locate the specific location of the mobile IoT device.Compared with the simple particle filter algorithm,the improved particle filter algorithm in this paper has made some innovations in the particle's motion model,calculation model and resampling model to adapt to the mobile scene of the IoT device and increase the reliability of the particle filter algorithm.In addition,this paper also proposes a new LoRa signal estimation model based on the COST-231 model,which is used to quickly generate a fingerprint database for matching algorithm operation.Finally,this paper conducted a real-world test experiment on the proposed positioning system LO-Loc.The experiment verified the positioning effect of the LO-Loc system under different experimental parameters.The experimental results show that the LO-Loc system's positioning accuracy can reach 5-10 m and the positioning error rate can be reduced to 5% in the environment with obvious landform changes the following.Compared with other positioning schemes,this LoRa-based outdoor positioning scheme can not only save energy and reduce COSTs,but also provide good positioning accuracy and an acceptable precision.