Impulse Radio Ultra-wideband (IR-UWB) is a newly emerged short range wireless technology which is quite different with traditional wireless techniques. It has attracted great intention by researchers from academy and industry, for its wide application in communication, precise ranging and positioning, detection, imaging and so on. Based on time difference of arrival (TDOA) method, indoor localization using UWB signals will be studied in this paper. Aiming at the difficult ies of anchor node synchronization for standard TDOA method, an improved TDOA method is proposed. Performance analysis and optimization of this method are made. The main contents of this paper are as follows:

Aiming at the problems of low accuracy , poor anti interference ability , and poor stability of traditional indoor Kalman filter positioning algorithm in complex indoor environments, a weighted adaptive Kalman filtering ( WKF )time difference of arrival ( TDOA ) positioning algorithm, based on ultra- wideband ( UWB) is proposed.Firstly, establish a four- anchor ultra- bandwidth positioning system, intrduce wireless clock synchronization technology to eliminate dlock erors. Secondly，compensate the original data to reduce positioning error caused by human reflection and multipeath effect and other influencing factors. Then，recursively update the noise covariance and dynamically adjust the weights to enhance the stability of the filter. Finally , dynamic real- time positioning of moving target is realized. The results show that WKF-TDOA can reduce positioning errors caused by multipath effet，and achieve dynamic real- time high-precision positioning of moving targets. Compared with other existing positioning methods，the experimental results show that this method has higher precision and better robustness.

UWB ( Ultra Wide Band) technology is a new indoor positioning technology which has been widely studied for its low power consumption， high positioning accuracy and strong penetration ability. In this paper， based on the TDOA ( time difference of arrival) measurement method， UWB tags are used to send signals to multiple base stations to obtain the time stamp difference between tags and each base station， and the movement position of the tag is solved in real time by the Chan algorithm. The “current” statistical model is established， the iterative process of Kalman filtering is improved by setting the threshold， and them the improved adaptive Kalman filter algorithm is used to eliminate the influence of non line of sight error and noise on TDOA location so that the indoor positioning accuracy of TDOA is more accurate. Experiments show that the TDOA positioning method based on adaptive Kalman filter has high accuracy.