Kernel Methods for Accurate UWB-Based Ranging With Reduced Complexity

Abstract

Abstract-Accurate and robust positioning in multipath environments can enable many applications, such as search-andrescue and asset tracking. For this problem, ultra-wideband (UWB) technology can provide the most accurate range estimates, which are required for range-based positioning. However, UWB still faces a problem with non-line-of-sight (NLOS) measurements, in which the range estimates based on time-of-arrival (TOA) will typically be positively biased. There are many techniques that address this problem, mainly based on NLOS identification and NLOS error mitigation algorithms. However, these techniques do not exploit all available information in the UWB channel impulse response. Kernel-based machine learning methods, such as Gaussian Process Regression (GPR), are able to make use of all information, but they may be too complex in their original form. In this paper, we propose novel ranging methods based on kernel principal component analysis (kPCA), in which the selected channel parameters are projected onto a nonlinear orthogonal high-dimensional space, and a subset of these projections is then used as an input for ranging. We evaluate the proposed methods using real UWB measurements obtained in a basement tunnel, and found that one of the proposed methods is able to outperform state-of-the-art, even if little training samples are available.

Experimental study of indoor tracking using UWB measurements and particle filtering

“…Then, motivated by our previous research results [6], [10], we consider four options for the likelihood model: 1) Direct TOA-based ranging: We assume that the measurement, also known as pseudo-range, is simply given by y n,t = cτ n,t where τ n,t is the time-of-arrival (TOA) between beacon n and the target at time t, and c ≈ 3·10 8 m/s is the speed of light. Then, the likelihood is given by:…”

Threshold selection method for UWB TOA estimation based on wavelet decomposition and kurtosis analysis

“…The important premise of these applications is to obtain the precise position of the targets [3][4][5]. Therefore, the precise positioning of targets becomes the key problem to be solved urgently.…”

“…UWB is the most promising technology for indoor positioning and tracking [3]. Compared with other shortrange communication technology, UWB has many advantages for short-range communication: first, UWB can provide up to GHz bandwidth; second, UWB can provide data rates of hundreds of megabits per second or even gigabits per second, so it is an ideal technology for wireless communication in wireless sensor networks [11,12]; third, continuous transmission carrier is not needed in UWB communication, and the intermittent pulse is used to transmit data, which make short pulse duration, low power consumption, and high multipath resolution.…”

“…However, obtaining the accurate ranging estimation is a very challenging problem due to the effects of thermal noise, multi-path fading, non-line of sight, and other factors in wireless transmission channel. For example, in non-line of sight (NLOS) environment, the range estimation based on TOA will typically be positively biased [3].…”

“…The second is machine learning method based on some selected channel parameters. In [3], a ranging method based on kernel principal component is proposed, where the channel parameters are projected onto a high-dimensional nonlinear orthogonal space, and then the subset from these projections is used for ranging. The third is energy detection (ED) algorithm based on non-coherent receiver with low sampling rate and low complexity [8,9,21].…”