Research On The Key Technology Of High-Accuracy Positioning Based On Mobile Communication System

With the development and application of the Third Generation (3G) mobile communication systems, positioning based on mobile communications networks will achieve fast and high-precision location as well as combining and communicating with other systems. Positioning based on mobile communications networks may have mass users with mobile phone, and that give it a broad application and market prospects on service based on location, such as personal service and traffic information extraction.In order to achieve higher accuracy and greater environmental adaptability of mobile communication network navigation for satisfying the needs of ubiquity positioning and navigation and enhancing the level of location based services. Method, theory and technology of high-precision positioning based on the mobile communication networks are studied in this paper to improve the accuracy of positioning based on mobile communications networks from the research on weaken the impact of non line of sight (NLOS) error in time of arrival (TOA) based positioning style, the novel method of the location for mobile communications networks based on the feature of grids in communications environment and mobile integration positioning between satellite and mobile communication networks. The main research work and contributions are stated as follows:A. According to the main rule of measurement error of radio propagation delay in different environment, a NLOS elimination algorithm based on Kalman filter with state fuzzy feedback is provided. In the algorithm, the fuzzy control matrix is tuned according to the statistics of real-time observation of NLOSerror, so that the Kalman filter is more robust referring to the NLOS error disturbance. In a complex environment of the wireless communication, the new algorithm with automatic adjustment of the function of NLOS reduction for the TOA based location methods can greatly improve the accuracy of location based on the mobile communication networks.B. Characteristics of the wireless environment can be changed if the position is changed. In order to extract the feature value of the radio propagation environment, the outliers are removed from feature values in measurement data. Two feature extraction algorithms are proposed to dispose the datas measuring in the fixed position or move along the road. According to mobile measurement, a algorithm using a feature extraction method based on fuzzy degree of neighborhood difference summation is proposed, which not only effectively peer off the outliers from the features of radio propagation environment, but also keep the continuous transmission added delay due to the NLOS or else element stable with the certain spread environment. The proposed method on feature extraction is simple, practical and effective, verifying by the simulation. It overcomes the problem that the assumptions of the model do not meet the reality environment in the traditional method.C. In the complex environment, the accuracy of TOA measurement is not easy to improve because of the NLOS error. After the collection and analysis of the wireless signals propagation time delay values, a location method based on the feature of grids in service area is proposed. The values of the wireless signals propagation time delay from the base station nearby to the mobile terminal is used as the feature of grids. The grids are plotted, depending on the distance between the feature values of grids, and locating by matching the feature values to the feature database according to the weighted distance between theirs feature values from same base stations. The complexity of the wireless communication environment is taken fully into account in the proposed algorithms. Therefore, when their variation of feature values is less than a certain degree, they can be combined into one grid. Multilayer search method is used to speed up the process of matching locating. A numerical example shows that grid feature based location method can make the NLOS error which had been very difficult to eliminate in ordinary methods favorable for location in the complex environment of wireless communication.D. The technology on syncretic locating can be provided with mobile communication network and GPS. On the research basis in the second chapter, the joint positioning algorithm based on the estimation results of two systems is given. The algorithm is presented based on Fuzzy-Weighted Kalman Filter. It realizes not only the joint positioning with the estimation results of mobile communication networks and GPS, but also smooth swiching between two systems. Simulation results show that the fuzzy-weighted Kalman filter algorithm has good performance on continuous locating and smooth switching on navigation mode in the case of GPS is not visible. Syncretic locating method does a very good complement on positioning during the time from unlock to reaquired the GPS signals again.At last, the conclusions and expectations are presented in the last part of this paper. The creative views and the shortcomings are induced. The way to study the positioning based on mobile communication network and the direction of further research is discussed.