Research On Radio Frequency Tomography Positioning Based On 433MHz Band Wireless Sensor Network

Device-free Localization(DFL)is a wireless localization method that does not require any electronic device to be carried by a location target.Currently,this localization method is widely used,such as personnel search and rescue,intrusion detection,special elderly care,etc..The positioning technology is through the monitoring radio frequency signal within the region to achieve changes in positioning.The low cost WSN node is used to set up a positioning system.The nodes receive the Received Signal Strength(RSS)of the corresponding link through one-to-one communications,and obtain the target location information according to the impact of the target on the radio link.Radio Tomographic Imaging(RTI)is a new type of RSS location technology that models DFL into a imaging problem with the help of industrial CT imaging principles.Building a reasonable signal weight model is an effective way to improve the RTI accuracy.Therefore,this thesis focuses on the RTI weight model and RTI imaging results in-depth discussion and research.The main work and research results include the following aspects:(1)Based on the existing Zigbee wireless network system,a new type of wireless network system has been developed.This system uses a 433MHz wireless sensor as a node to construct a wireless network to achieve positioning and make up for 2.4 GHz wireless node transmission distance more short,poor penetration and other deficiencies.(2)Based on the improvement of the RTI-based weight model,a new RTI weight model is proposed according to the first Fresnel zone theory of the antenna.The feasibility of the model is verified through experimental verification and digital simulation.Finally,the model is actually applied to RTI,to increase accuracy and reduce background noise.(3)In order to solve the problems of background noise and emergence of pseudo-targets in RTI,the target foreground extraction technology based on the maximum inter-class variance method in image processing has increased RTI positioning accuracy and eliminated background noise and false targets.Finally,the author firstly summarizes the work of this dissertation and sums up the shortcomings of this dissertation;then puts forward some suggestions on how to improve the dissertation,and make a better study in the future and gives a prospect of future research.