Self-Localization via Circular Bluetooth 5.1 Antenna Array Receiver

Abstract

Future telecommunications aim to be ubiquitous and efficient, as widely deployed connectivity will allow for a variety of edge/fog based services. Challenges are numerous, e.g., spectrum overuse, energy efficiency, latency and bandwidth, battery life and computing power of edge devices. Addressing these challenges is key to compose the backbone for the future Internet-of-Things (IoT). Among IoT applications are Indoor Positioning System and indoor Real-Time-Location-Systems systems, which are needed where GPS is unviable. The Bluetooth Low Energy (BLE) 5.1 specification introduced Direction Finding to the protocol, allowing for BLE devices with antenna arrays to derive the Angle-of-Arrival (AoA) of transmissions. Well known algorithms for AoA calculation are computationally demanding, so recent works have addressed this, since the low-cost of BLE devices may provide efficient solutions for indoor localization. In this paper, we present a system topology and algorithms for self-localization where a receiver with an antenna array utilizes the AoAs from fixed battery powered beacons to self-localize, without a centralized system or wall-power infrastructure. We conduct two main experiments using a BLE receiver of our own design. Firstly, we validate the expected behaviour in an anechoic chamber, computing the AoA with an RMSE of 10.7°. Secondly, we conduct a test in an outdoor area of 12 by 12 meters using four beacons, and present pre-processing steps prior to computing the AoAs, followed by position estimations achieving a mean absolute error of 3.6 m for 21 map positions, with a minimum as low as 1.1 m.

An Experimental Evaluation Based on Direction Finding Specification for Indoor Localization and Proximity Detection

“…Additionally, in [19], authors measure an angular error of 2°b y using SDR hardware in ten locations. Paulino et al [20] This article has been accepted for publication in IEEE Journal of Indoor and Seamless Positioning and Navigation. This is the author's version which has not been fully edited and present a self-localization system, where a receiver with an antenna array utilizes the AoAs from fixed beacons to selflocalize without a centralized system.…”

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

“…Bluetooth devices have been widely applied in electronic devices, such as smart phones, laptops, wristbands and so on. Most commercial solutions calculated the target's location with measured angles and signal strengths [45,46]. Among them, the Spotlight algorithm was proposed [47], which utilized both the AoA and elevation of angle (EoA) of the signals to solve more accurate angle estimates.…”

Location Accuracy Optimization in Bluetooth Low Energy (BLE) 5.1-Based Indoor Positioning System (IPS)—A Machine Learning Approach

“…Positioning parameters refer to raw data that will be processed to determine the position of tags. Various positioning parameters used in IPS along with their respective advantages and disadvantages are shown in Table II [2,7,8]. Received Signal Strength (RSS) is a measure of power signal's strength measured in dBm or mW.…”

“…Angle of Arrival (AoA) is a measure of signal's angle from where it is received by the readers. In this work, we employ AoA as key parameter for positioning mainly for its less sensitivity towards variations in signal strength as compared to other parameters such as RSSI, ToA or TDoA [2]. As long as the signal is received by receiver, AoA computation for positioning is possible.…”

“…In BLE 5.0, the IPS used Received Signal Strength Indicator (RSSI) as parameter to compute positioning via trilateration method. The location accuracy that can be expected from BLE 5.0 is about 2-5m [1,2]. In 2019, BLE 5.1 was released which included new metrics for positioning, Angle of Arrival (AoA) and Angle of Departure (AoD), that enables Direction Finding feature 2 within BLE devices [3].…”