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摘要
The Ultra-Wide Bandwidth (UWB) signal has received much attention due to its penetrability and high positioning accuracy with the increasing demand for indoor positioning, in which Global Positioning System (GPS) signal is challenging. In practice, there are two main problems with indoor 3D positioning based on UWB. One is that the quality of Time Difference of Arrival (TDOA) measurements varies in different observation environments. Namely, the time delay generated by Non-Line-of-Sight (NLOS) causes an enormous deviation from the real distance and cannot be well distinguished from the measurement reducing the accuracy of positioning. The other problem is that the height estimates, which are calculated using the conventional least square method, are extremely unstable due to the limitation of the Base Station (BS) layout. To address these problems, this paper presents Robust Ridge Estimation (RRE) for UWB positioning. Firstly, NLOS errors are detected, and the weights of each measurement are automatically adjusted in accordance with their quality, which is represented by the residuals between the estimated measurements and real observations. Then, the ridge estimation algorithm is applied iteratively for position estimation based on a robust estimation framework, which updates the weight of the measurements at each iteration. This approach transforms unbiased estimation to biased estimation by adding constraints that minimize the weighted quadratic sum of some parameters. As a result, the impact of NLOS can be reduced. The experimental result shows an improvement of RMSE in positioning with 45.71% when compared with ridge estimation in an NLOS/Line-of-Sight (LOS) mixed environment and an increase of robustness to NLOS with 56.11%.
- 出版日期2017-12-15
- 单位中国人民解放军信息工程大学
