Indoor And Complex Outdoor Environment Localization Based On Fingerprint Techniques

Since 1980s,the development of advanced communication technologies and the rapid evolution of mobile communication system standards,also with the diversification of mobile communication network architectures have made the communicative way be more convenient.On the one hand,it promotes the rapid development of business,which has inspired the demand of location based services.On the other hand,it also makes the radio resource allocation as one of the core issues for the research on mobile communication systems.The radio communication environment is becoming more and more complex.The illegal radio stations set up without authorization is a difficult problem that the radio management system must to face.Protecting the safety of radio environment has been related to the event in the national economy and people's livelihood.The location technology has become one of the key techniques in checking and locating interference of interference signal.Because of the complexity of the environment in indoor and dense urban areas,the signal receivers are unable to receive GPS signal.The existence of a large amount of multipath also makes it be difficult to obtain acceptable positioning accuracy when using traditional ranging or direction based localization methods.However,with the wide use of WLAN equipment,the fingerprint positioning technology based on WIFI signal has been developed rapidly,which greatly promotes the improvement of indoor positioning technology.But the high computational complexity and low robustness to the environment are still the problems that need to be solved in present fingerprint based positioning technology.The fingerprint based positioning technology used in indoor cannot be directly applied to outdoor scene for difference among indoor scene and outdoor scene.This paper intended to solve the problems mentioned above from the following three perspectives:First,based on the static segmentation method,the improved dynamic segmentation strategy is proposed in indoor scene.Not only can it reduce the complexity of computational complexity,but also it can reduce the error caused by the signal fluctuation.At the same time,a matching method based on the order of received signal strength is proposed to improve the robustness of the algorithm.Second,a two-step none-line-of-sight(NLOS)identification algorithm is proposed for the situation where both NLOS error distribution and channel model are not available.In order to make the threshold more reasonable,a threshold selection method for image processing is utilized.To increase the accuracy of estimated position when line-of-sight(LOS)paths are limited,we proposed a result reconstruction method.Third,this paper does research on the fingerprint based positioning technology used for outdoor location.Based on the theory and field experiment,the relationship between the channel characteristics and the position of the signal is analyzed.The knowledge of data mining is used to analyze and extract the core feature of channel characteristics.A fingerprint based outdoor location algorithm which uses both signal strength and signal channel characteristics is proposed to effectively reduce the ambiguity of estimated position.Eventually,conclusion for whole thesis is made.Also,in accordance with present situation and development of localization fields,future outlook gets arrived at.