Application of Matrix Pencil Algorithm to Mobile Robot Localization Using Hybrid DOA/TOA Estimation

Abstract

Localization plays an important role in robotics for the tasks of monitoring, tracking and controlling a robot. Much effort has been made to address robot localization problems in recent years. However, despite many proposed solutions and thorough consideration, in terms of developing a low-cost and fast processing method for multiple-source signals, the robot localization problem is still a challenge. In this paper, we propose a solution for robot localization with regards to these concerns. In order to locate the position of a robot, both the coordinate and the orientation of a robot are necessary. We develop a localization method using the Matrix Pencil (MP) algorithm for hybrid detection of direction of arrival (DOA) and time of arrival (TOA). TOA of the signal is estimated for computing the distance between the mobile robot and a base station (BS). Based on the distance and the estimated DOA, we can estimate the mobile robot's position. The characteristics of the algorithm are examined through analysing simulated experiments and the results demonstrate the advantages of our method over previous works in dealing with the above challenges. The method is constructed based on the low-cost infrastructure of radio frequency devices; the DOA/TOA estimation is performed with just single value decomposition for fast processing. Finally, the MP algorithm combined with tracking using a Kalman filter allows our proposed method to locate the positions of multiple source signals.

Localization of Autonomous Robot in an Urban Area Based on SURF Feature Extraction of Images

“…A localization method using the Matrix Pencil (MP) algorithm for hybrid detection of the Direction of Arrival (DOA) and Time of Arrival (TOA) was presented in (Trinh et al, 2012). Huang, Tsai, & Lin (2012) published two techniques for mobile robot localization for the indoor environment.…”

“…However, it (Saurer et al, 2015) may not be applicable in city streets (particularly old town streets) where there may have too many obstacles for visibility. Moreover, RF has been utilized in (Trinh et al, 2012) and ultrasonic sensors, encoder methods, artificial landmarks, etc. have been used in (Shwe & Win, 2017).…”

Geometric model based directional sensing of electromagnetic waves and prototype implementation

“…, , , (Malajner, et al, 2012) (Menegatti, et al, 2009), (DoA) (Viciana-Abad, et al, 2014)( , 2007, (ToA) (Priyantha, et al, 2005) (Trinh,et al, 2012), (TDoA) (Xu, et al, 2013) (Prorok, et al, 2012), (FDoA) (Widodo, et al, 2013) (Chestnut, 1982) .…”