Research And Simulation On The Ultra Wide Band Wireless Positioning Algorithms

The UWB (Ultra Wide Band) wireless location technology is mainly used in theshort-range wireless communication area, and UWB technology plays a moreirreplaceable role in positioning area than others due to its advantages. It is animportant exploration to research the positioning area, which is also important for thedevelopment of UWB in our country, and it will bring to the improvement of our dailylife. This paper makes a deep research on the positioning algorithms in the UWBenvironment and finds out how to obtain more precise estimates.At the beginning of this paper, it reviews and looks forward to the development ofUWB technologies, and then, it analyzes the current development status at home andabroad. Some important UWB applications are summarized. This paper compares andanalyzes the methods of ranging and positioning. In this paper, research is based onthe IEEE802.15.4a channel model, and the positioning algorithms are applied to therequired channel environments. The paper mainly focuses on two parts to the studies.For the first part, an improved Taylor series location algorithm is presented for IEEE802.15.4a channels. The indoor Line of Sight (LOS) channel model is considered.When the Taylor series location algorithm is used for position estimation, it is difficultto get an initial estimate of the mobile station (MS). After estimating the Time ofArrival (TOA) or Time Difference of Arrival (TDOA), the Chan algorithm is used asan initial estimate for the Taylor-series method. Performance results are presentedwhich indicate that this algorithm provides better position accuracy and is moreefficient than the Chan and Taylor series algorithms used separately. For the secondpart, a data fusion positioning algorithm is proposed. This method is a fusion ofseveral algorithms. The position of MS is calculated by TDOA positioning algorithmand Angle of Arrival (AOA) positioning algorithm, then the position of MS isdetermined by data fusion location algorithm. The simulation results indicate that thelocation accuracy is significantly improved and the performance of this algorithm is better than that of TDOA location algorithm and AOA location algorithm in LOSenvironment. This algorithm can provide relatively stable results for the positioningbetween the two methods results. The data fusion positioning algorithm is morepractical and efficient than the single algorithm. The studies will provide a necessaryreference for the further study of improving the positioning accuracy.