Bias Compensation for UWB Ranging for Pedestrian Geolocation Applications

Abstract

We present an effective bias compensation method to process none-line-of-sight (NLoS) and long-distance lineof-sight (LD-LoS) Ultra-Wideband (UWB) range measurement signals used to aid a pedestrian inertial navigation system (INS). The common UWB bias compensation techniques use machine learning methods to identify and remove the bias in the measurements. These techniques are computationally expensive and require extensive prior data. Here, we propose to use an algorithmic compensation technique that accounts for the bias by estimating it using the Schmidt Kalman filter. Next, we exploit the positivity of the error in the UWB range measurements to propose a novel constrained sigma point based correction filtering that can be used atop the Schmidt Kalman filter for further improvement in the positioning accuracy of the UWB aided pedestrian inertial navigation. Experiments demonstrate the effectiveness of our methods.

Single UWB Anchor Aided PDR Heading and Step Length Correcting Indoor Localization System

“…Hence, most researchers concentrate on correcting pedestrian location by fusing MEMS and UWB system localization results directly [5], [26], [27], [31], which need high density UWB anchor deployment accompanied with high costs. It is the tradeoff between set costs and localization accuracy.…”

“…Jianan Zhu's team presented a hybrid filter, the Schmidt Kalman filter followed by a novel constrained sigma point based filter, for UWB-aided pedestrian location estimation under None Light of Sight (NLoS) and long-distance Light of Sight (LoS) situations [25]. After that, this team also proposed an adaptive localization based on the first-order Generalized Pseudo Bayesian (GPB) method to improve the localization accuracy under LoS and NLoS, which has achieved good localization accuracy [26]. Qigao Fan et al designed a Double-State Adaptive Kalman Filter (DSAKF) algorithm based on Sage-Husa adaptive Kalman filter and fading adaptive Kalman filter to fuse INS and UWB localization results [27].…”

“…According to the relation (17), it can be used to constrain the heading angle and provide better localization result. A constrained sigma-point based filter [25], [34] is selected as the optimal estimation process, it is divided into three stages: where k  is used for turning the size of sigma point distribution. s…”

Variational-Based Non-linear Bayesian Filtering with Observations Subjected to Gross Errors

“…Ultra-wideband (UWB), Global Positioning System (GPS) or Universal Mobile Telecommunications System (UMTS) signals can get affected in non-line-of-sight (NLOS) settings in this manner. Filtering with bias compensation finds applications in diverse fields [12], [13], [14], [15]. In this work, we keep our focus only on the appearance of gross errors in the measurements and how these can be compensated within the filtering framework.…”

Clock and Power-Induced Bias Correction for UWB Time-of-Flight Measurements

“…Nonetheless, large positive errors can occur in non line-of-sight (NLoS) configurations, when the direct path between transceivers is blocked by an obstacle and the receiver detects instead a reflected signal. As a result, much of the literature on UWB-based localization focuses on detecting and mitigating the effect of NLoS measurements, see, e.g., [3], [12]- [14].…”