Algorithms for Indoor Positioning Systems Using Ultra-Wideband Signals

Positioning systems and techniques have attracted more and more attention in recent years, in particular with satellite navigation technology as a tremendous enabler, and developments in indoor navigation. The work presented in this thesis has been conducted within the research project: \HERE: indoor positioning based on UWB radio signals", which aims at developing an alternative solution to the indoor positioning problem, since the Global Navigation Satellite Systems (GNSSs), e.g. the Global Positioning System (GPS), generally can not provide reliable positioning services in indoor areas, due to strong signal attenuation and dense multipath e ects. The project focuses on range-based technologies, which are mainly composed of two parts: 1) ranging based on information such as Time of Arrival (ToA), Time Dierence of Arrival (TDoA) and Received Signal Strength (RSS); 2) positioning using the obtained ranging results. This four-year project has been carried out in a team composed of two Ph.D. candidates and two supervisors. As one of the Ph.D. candidates, the author of this thesis focuses on the positioning part of the project, with the main covered issues summarized as follows. Iterative Descent Methods The majority of existing systems, e.g. GPS, solve the positioning problem using Iterative Descent (ID) methods based on non-linear least-squares. Applying these ID methods for indoor positioning purpose faces the following three major problems: It is more dificult to obtain a good initial guess, which is critical for the ID methods to converge to the correct solution and converge faster. For on-earth satellite navigation applications, a good initial guess can be very easily obtained by choosing the Earth's center since the other (local) solution (if any) usually lies far in space. On the contrary, for indoor positioning, it is not as easy to obtain a good initial guess since the information on the user position is rather limited beforehand. In this thesis, we propose to use the so called direct methods or simply the geometric center of the seen transmitters, for initial guess. A thorough study of the existing direct methods is also given. The non-linear least-squares estimator is inherently biased, even with unbiased range measurements, since the expectation of the higher order terms in the final estimator is non-zero. This bias is generally negligible for GNSSs, with extremely large satelliteuser distance, but can be problematic for indoor applications with reduced geometric system scale. Based on an analysis of the bias due to nonlinearity, a scheme is proposed to test the significance of the bias. The corresponding work is validated with measurements obtained using UWB acoustic testbed. The iterative nature of the ID methods may be computationally too heavy for indoor applications, which usually require low power systems. Aiming at reducing the computational load of traditional iterative descent algorithms, a new framework is proposed for position estimation. The multidimensional non-linear localization problem is first transformed to a lower dimension and then solved iteratively. In three dimensional positioning systems, the achievable reduction on the amount of computation in each iteration is 67%. On the other hand, accurate positioning results can be obtained with this low-complexity framework, especially with TDoA measurements. Direct Methods In general, strict direct (non-iterative) least-squares solutions to nonlinear problems do not exist. However, with some assumptions or simplifications, direct least-squares positioning algorithms can be developed. In fact, there is a large number of direct methods documented in literature, scattered across the fields of radar, aerospace engineering, oceanic engineering, (acoustic) signal processing and wireless communications. Some of the documented methods are, surprisingly, identical, though the derivations are often greatly different. A deep study and a proper classification of the methods helps to achieve a better understanding, which is one of the central contributions of this thesis. It can be used to assist researchers and developers in the field to find the right choice for their applications. The direct methods provide simple to compute estimates, but they are suboptimal with the introduced simplifications. Based on the survey of the existing direct methods, a new non-iterative algorithm has been developed to improve the positioning accuracy. Theoretical proof is given that the method provides a better estimator in the sense that it corresponds to an equal or smaller value of the original least-squares objective function. It does so by exploiting two similar fully constrained models. Meanwhile, the non-iterative nature makes the algorithm attractive for low cost, low power applications. NLoS Identification/Mitigation It is widely known that the Non-Line of Sight (NLoS) effect is one of the main degraders for the position estimation accuracy. Hence, NLoS identification and mitigation is another important and hot subject regarding indoor positioning. A review of several existing NLoS identification and mitigation schemes is provided, and four new schemes are described, which are based on systematic positioning model hypothesis testing. The idea is to combine the statistics of timing- and RSS-based range measurements, and in the mean time exploit the fact that all collected measurements are related to the same unknown position. The four proposed schemes all use the combination of timing and RSS measurements because 1) the timing measurements are usually very accurate compared to RSS measurements, 2) the distributions of RSS measurements under LoS and NLoS conditions are well separated. The computational load of the schemes decreases as more simplifications are introduced, and the performance, however, is also degraded in general, except the case where most of the links are NLoS. Validation results show that, under full UWB signal bandwidth of 7.5 GHz, up to 99% correct decision rate can be achieved.