Research On Indoor High-precision Positioning Method Based On The Terminal And The Network Side

Wi-Fi indoor positioning methods based on currently available, due to the dynamic positioning transform the environment, such as changes in the placement of interior items,changes in the wireless network environment, changes in the flow of people, etc., it is difficult to maintain in a dynamic environment for stable positioning accuracy problems. This paper presents an adaptive fingerprint indoor location positioning method. The method of locating the reference point signal acquisition and multi-dimensional, real-time positioning and fusion using the status information of the user terminal, so that the positioning stability to a large extent improved. In this method, a certain way of positioning reference point explicit calibration, and can help the user during use of the data, to dynamically adaptive update existing location fingerprint database. Experimental results show that the proposed method than the traditional targeting methods are easy to maintain, more accurate, more stable advantage. Meanwhile, the paper combined with the actual needs of the project for environmental characteristics and special needs of the commercial real estate traffic statistics of a survey research, the traffic statistical method based on Wi-Fi signal attenuation model,compared to the conventional method dependent on additional special hardware or manually statistics, low cost, high efficiency and comprehensive information advantage. Finally, on the basis of a comprehensive prior study, we present a demand for commercial real estate indoor positioning, based on the state transition network side positioning Matrix. Compared to the positioning method based on the terminal side, the method does not require the user terminal can be directly involved in the realization of the terminal positioning, and positioning the user terminal location area to locate and record statistics. Not only it can provide real-time location services to end users, but also can provide scientific reference data for commercial real estate operations management. Experiments show that by testing, based on Wi-Fi signal attenuation model traffic statistical methods presented in this paper and the network side positioning method based on the state transition matrix has good positioning performance, and can well meet the actual application requirements.