AoA and RSSI-Based BLE Indoor Positioning System With Kalman Filter and Data Fusion

IF 8.9 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Internet of Things Journal Pub Date : 2025-01-16 DOI:10.1109/JIOT.2025.3530866

Andrey Fabris;Ohara Kerusauskas Rayel;João Luiz Rebelatto;Guilherme Luiz Moritz;Richard Demo Souza

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引用次数: 0

Abstract

This work aims at improving indoor positioning systems (IPS) by integrating multiple radio frequency techniques, namely received signal strength indiction (RSSI), Angle of Arrival (AoA), and a combination of both, within the bluetooth low energy (BLE) 5.1 framework. While AoA stands out for its precision, low energy consumption, and cost-effectiveness, RSSI is characterized by its simplicity and widespread availability. By resorting to a database of real RSSI and AoA measurements from a BLE 5.1 target node in a

$14\times 8$

-m environment, our work employs the Kalman filter (KF) to improve the accuracy of multilateration, AoA combined with RSSI, and AoA-only algorithms. Moreover, we consider one more step in our IPS where the aforementioned KF-filtered outputs are then fused through a track fusion model. Results demonstrate that the proposed scheme, which we refer to as angle-RSSI fusion localization (ARFL), significantly improves localization accuracy compared to other techniques. In particular, it reduces up to 81.61% in the average position error when compared to multilateration with KF. This advanced IPS offers a cost-effective and precise solution suitable for various applications in industries, such as healthcare, commerce, and logistics.

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基于卡尔曼滤波和数据融合的AoA和rssi的BLE室内定位系统

本研究旨在通过在蓝牙低功耗（BLE） 5.1框架内集成多种射频技术，即接收信号强度指示（RSSI）、到达角（AoA）以及两者的结合，改进室内定位系统（IPS）。虽然AoA以其精度，低能耗和成本效益而脱颖而出，但RSSI的特点是其简单性和广泛可用性。通过在$14\ × 8$ m环境中使用BLE 5.1目标节点的真实RSSI和AoA测量数据库，我们的工作采用卡尔曼滤波器（KF）来提高乘法，AoA与RSSI结合以及AoA-only算法的准确性。此外，我们还考虑了IPS的另一个步骤，即通过航迹融合模型融合前面提到的kf滤波输出。结果表明，与其他定位技术相比，我们提出的角度- rssi融合定位（ARFL）方案显著提高了定位精度。特别是与KF法相比，其平均位置误差降低了81.61%。这种先进的IPS提供了一种经济高效、精确的解决方案，适用于医疗、商业和物流等行业的各种应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Internet of Things Journal Computer Science-Information Systems

CiteScore

17.60

自引率

13.20%

发文量

1982

期刊介绍： The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.