Return to search

Data Fusion of RSS and TOA Measurements for NLOS Mitigation and Wireless Location

The major problems encountered in wireless location are the effects caused by non-line of sight (NLOS) propagation and multipath interference. In the thesis, we propose an approach to mitigate NLOS error. First of all, we use improved biased Kalman filter (IBKF) based on time of arrival (TOA) measurement to identify and mitigate NLOS error. Applying the statistic characteristic that the standard deviation of the NLOS propagation errors is generally much larger than that of measurement noises in the LOS condition, we combine hypothesis test and sliding window to identify NLOS error. According to the feedback identification and the calculated standard deviation, IBKF switches biased or unbiased to process TOA measurement. Nevertheless, the performance of IBKF-TOA is still affected slightly by NLOS error. Since extended Kalman filter (EKF) based on received signal strength (RSS) measurement is designed for prespecified environments, the effect of NLOS mitigation is more obvious. Moreover, EKF-RSS not only exists higher error probability in NLOS identification, but also needs longer time to converge in the cases that start with NLOS. Comparing IBKF-TOA with EKF-RSS, we adopt interacting multiple model (IMM) in the proposed data fusion structure for processing TOA and RSS measurements. In the proposed scheme, we reserve the basic IMM structure and add the step of NLOS identification into basic IMM structure. By accurate NLOS identification results and soft decision of IMM, the proposed scheme will switch to adequate filter mode and obtain better estimation. With simulation in UWB channel, the analysis and performance evaluation show advantages and disadvantages of using IBKF-TOA, EKF-RSS, and proposed scheme. Simulation results reveal that NLOS error can be mitigated effectively by data fusion of TOA and RSS measurements and can achieve high accuracy in positioning and tracking.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0901110-004848
Date01 September 2010
CreatorsLiu, Jian-Ting
ContributorsKing-Chu Hung, Chin-Der Wann, Shiunn-Jang Chern, Hsin-Hsyong Yang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0901110-004848
Rightsnot_available, Copyright information available at source archive

Page generated in 0.0016 seconds