The Research Of Sampling Model Method To Location Estimation And Location Estimation System

With the development of wireless network, location-based services in wireless networks provide more value. Methods based on signal arrival time technology need very complex hardware requirements. But the information of signal strength is provided in all the existing wireless network. This paper did research about location estimation based-on signal strength.This paper presents a sampling model to location estimation applied to the complex electromagnetic environment in 2.4G WSN. Model through the establishment of sampling the signal in the environmental impact caused by the attenuation and reflection of the surrounding environment is reflected in the model.With the method a systerm for location estimation are realized in WSN.The systerm contains two parts,hardware systerm in WSN and softawre in pc.With this systerm the location of the access point can be estimated.The main content in this paper:1.The status of positioning technology are researched, and analysis the existing positioning technology.The main location estimation methods are introduced, such as positioning method based on signal strength, positioning method based on time of arrival.2. The network signal strength model is researched in the physical environment; The sampling model to location estimation is proposed; the method is based on the spatial grid, and the template data is established through sampling methods. The accuracy of location is improved with the sampled data. This paper details the process of sampling model and theoretical basis, and how to use the sampling method of position estimation model;3. The building process and using effect are realized and tested in the WSN builded through ZigBee soc modules. Given positioning system software architecture and design and implementation of various parts of elements;Through the positioning software in PC,a positioning system is builded.And the sampling method is experited in this system.And the test data and analysis are provided.The test proved that location estimation can be realized in exsiting network, and has good flexibility and positioning accuracy.