Advancement in wireless technology and the oncoming of the Internet of Things (IoT) marked an incredible growth in the wireless connectivity, ultimately concluding to a major expansion in the mobile electronics industry. Today, around 3.1 billion users are reported being connected to the internet, along with 16.3 billion mobile electronic devices. The increasing connectivity has lead to an increase in demand for mobile services, consequently, increasing demand for location services and mobility analytics. The most common location tracking or direction finding devices are found in the form of Global Positioning System (GPS) which provides location data for a client device using satellites-based lateration techniques. However, the use of the GPS is fairly limited to large distances and often tend to fail when smaller distances are concerned. This thesis aims to dive into the study of different direction finding algorithms based on angle of arrival estimation specifically pertaining to the indoor location tracking and navigation, also known as hyperlocation. The thesis will go over the main elements used in direction finding systems while looking at some of the present research done in this respective field of interest. Afterwards, the thesis will focus on a specific angle of arrival estimation algorithm which is widely being used for hyerplocation solutions and propose an alteration in the algorithm in order to achieve a faster runtime performance on weaker processors. A comparison between the accuracies will be made between the original algorithm and the suggested solution, followed by a runtime comparison on different processing units.
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Computation Reduction for Angle of Arrival Estimation Based on Interferometer Principle
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