The Study Of Uwb Wireless Positioning Technology

Ultra Wideband (UWB) technology, also known as impulse radio technology, has huge bandwidth up to a few GHz. The energy bandwidth of the UWB waveform is more than 0.20～0.25, its features include low power, anti-multipath, high data rate, excellent penetration ability etc. Over the last several years, there has been a great deal of interests in UWB wireless communications, especially after the approval of the UWB technology by Federal Communications Commission (FCC) in February 2002. UWB has become a research focus in wireless communications, and been considered as one of the key technologies of next-generation wireless communications.UWB technology displays great advantages in many applications, and it is superior to the traditional ways of wireless positioning schemes. The main purpose of this thesis is to study the positing and location of UWB technologies in line-of-sight (LOS) case. Chapter 4, UWB wireless positioning technology, is the focus of this thesis. This chapter introduces the superiority of UWB technology in wireless positioning and some typical wireless positioning methods for UWB technology. Following these, this work studies the LSE positiont estimation for TOA positioning method, and also makes more in-depth study for TDOA positioning method which is more practical. There are three typical TDOA hyperbolic positioning algorithms, that is, Fang algorithm, Chan algorithm and Taylor algorithm. We also make computer simulations to compare their positioning accuracy.Fang algorithm is one of TDOA algorithms which has the solution of one analytical expression, but it can not improve the positioning accuracy by using redundant information. Chan algorithm, another TDOA algorithm, which has solutions of one analytical expression, can make an approximate realization of maximum likelihood (ML) estimation in LOS, and it can achieve CRLB (Cramer-Rao low Bound) when the parameter errors are small. A feature of Chan algorithm has the smaller computation, and the algorithm has a high positioning accuracy when the noise obeys Gaussian distribution. But its performance will greatly reduce in NLOS. In addition, as a TDOA algorithm which has solutions of one analytical expression, Chan algorithm can improve the positioning accuracy by increasing the number of base stations. Taylor algorithm is a recursive algorithm for TDOA, and it is applicable to various wireless location environments. This algorithm can improve the estimated position by solving the TDOA measurement error of local linear LS solution in each recursion, so it has a large computation. And it must have an appropriate initial estimated position closed to the actual position in order to get the accurate results. If the initial estimated position is inappropriate it is difficult to ensure the convergence of the algorithm. However, it is difficult to determine the initial estimated position in practice, so the positioning accuracy of Taylor algorithm is limited.In order to solve the question of the selection of the initial position, we can carry out the first positioning of MS using one algorithm before the start of the Taylor algorithm. It is clear that the algorithm is required to have a small computation in order to avoid increasing the computation. And the most important is the positioning accuracy of this algorithm must be good enough to ensure the quality of the initial value. It is clear that Chan algorithm just to meet these two requirements.The thesis simulates and analyzes these algorithms, and compares their average positioning errors in the same ranging error variance. On this basis, we combined with the advantages of Chan algorithm and Taylor algorithm to wireless positioning in LOS. That is we can get an appropriate initial estimated position of of Taylor algorithm by Chan algorithm in order to ensure positioning accuracy and positioning speed. The results show that Chan-Taylor unity algorithm has the highest positioning accuracy.