Hybrid UWB-Inertial TDoA-Based Target Tracking With Concentrated Anchors

Abstract

In this paper, hybrid radio/inertial mobile target tracking for accurate and smooth path estimation is considered. The proposed tracking approach builds upon an Ultra Wide-Band (UWB)-based positioning algorithm, based on the Linear Hyperbolic Positioning System (LinHPS), with Time Difference of Arrival (TDoA) processing and anchors concentrated on a single hotspot at the center of the environment where the target moves. First, we design an Adaptive Radio-based Extended Kalman Filter (AREKF), which does not require a priori statistical knowledge of the noise in the target movement model and estimates the measurement noise covariance, at each sampling time, according to a proper LookUp Table (LUT). In order to improve the performance of AREKF, we incorporate inertial data collected from the target and propose three "hybrid" radio/inertial algorithms, denoted as Hybrid Inertial Measurement Unit (IMU)-aided Radio-based EKF (HIREKF), Hybrid Noisy Control EKF (HNCEKF), and Hybrid Control EKF (HCEKF). Our results on experimentally acquired paths show that the proposed algorithms achieve an average instantaneous position estimation error on the order of a few centimeters. Moreover, the minimum target path length estimation error, obtained with HCEKF, is on the order of 6% and 1% for two paths with lengths equal to approximately 17 m and 46 m, respectively.

Trustworthy Localization in IoT Networks: A Survey of Localization Techniques, Threats, and Mitigation

“…This challenge is overcome by a strategy based on selecting subsets of anchors and fusing estimations across multiple subsets. Building upon this, the research is further expanded in [66], where the proposed algorithm is applied to applications associated with mobile target tracking. The study in [67] demonstrates the feasibility of TDoA-based localization with low-power, low-cost technologies such as LoRa, in indoor and outdoor scenarios.…”