In the next generation of Bluetooth standard, the Bluetooth SIG wants to incorporate multiple antenna systems into the Bluetooth Low Energy specification to enable direction-finding features. The features are aimed to improve the accuracy of off-the-shelf Asset Tracking Profile (ATP) and Indoor Positioning Service (IPS) including two modes – Angle-of-Arrival (AoA) mode and Angle-of-Departure (AoD) mode. In this thesis, we only focus on the AoA mode. The new standard raises several challenges. First, the direction finding algorithm shall be derived sincethe standard gives only the framework. The algorithm shall cope with dense multipath effects in indoorenvironments and identify the angle of Line-of-Sight (LOS) component. Second, the new standard specifiesthe usage of an RF switch such that a single receiver can access multiple antennas. This mechanism reducesthe device cost and complexity but poses difficulties to the array processing. There are inevitably informationloss during antenna switching. It also raises requirements of channel stationarity and efficient compensationof CFO. Third, towards the system implementation, practical considerations that deviate the ideal datamodelshall be taken into account. These considerations include the effect of mutual coupling (MC), and the phase imbalance of the RF switch. During this project, these effects have been studied to obtain insight on theinfluence on algorithmperformance and compensation techniques. In this thesis, we formulated the data model for a single receiver using a uniformlinear multiple antennasystem with an RF switch. The importance of CFO compensation, channel stationarity, and the color of noiseare addressed. A maximum likelihood (ML) based CFO estimation algorithm is proposed. Furthermore, we modeled the effect of mutual coupling and imbalance of switch. Next, we analyzed why the delay estimation is not feasible within the context of Bluetooth LE. We proposed two Line-of-Sight direction identification (LOS-Id) algorithms based on the power signature in the data covariance matrix, which are referred to as MUSIC LOS-Id and CLEAN-MUSIC LOS-Id. Further performance improvements are achieved by making use of the frequency hopping feature of Bluetooth. By aggregatingmore than one packets at different frequencies, the performance can be improved substantially. This technique is called the multi-tone technique, or packet aggregation (PA). For evaluating the effectiveness of the proposed methods and models, a Bluetooth LE simulator is built. The performance verification is divided into two phases that differentiate themselves by the channel model. In the first phase, a simulated channel model, which is obtained by applying the ray tracer in an empty rectangular room, is used. The mutual coupling effect is simulated using the Antenna Toolbox in Matlab. The switch characteristics are verified by measurements using a Vector Network Analyzer (VNA). In the second phase, the real channel is measured with the VNA. Three campaigns of measurements are carried out with a 1x4, 1x8, and 2x4 antenna array respectively. Performance is evaluated by applying both channel models. The simulations reveal that the multipath effect is the dominant influencing factor of the performance in our indoor scenario, while the mutual coupling and the switch imbalance have little influence. The results also show that both proposed LOS-Id algorithms yield satisfying accuracy. However, we paid less attention to the CLEAN-MUSIC algorithm because of its complexity even though it indeed performs better than MUSIC LOS-Id in our simulated scenario. Finally, the usage of multi-tone technique improves the LOS-Id performance substantially. With an 8-element ULA and aggregating 8 tones, the MUSIC LOS-Id algorithm can achieve 10 degrees of RMSE for 90% of transmission positions with measured channels, and 3 degrees of RMSE for 50% of transmission positions.

This research investigates the impact of multipath signals in UWB communications and explores their potential to improve localization accuracy of tags using the additional information captured in the Channel Impulse Response (CIR). While traditional localization typically relies on multiple anchors, this study focuses on using a single anchor and creating multiple Virtual Anchors (VAs) through MultiPath Components (MPCs). The research proposes algorithms such as likelihood, algebraic, and fminsearch methods, and tests their performance through simulations in environments with anchors, tags, and reflective surfaces. After confirming the feasibility of using reflection multipath signals for localization through the simulations, experiments were conducted with NXP's SR150 UWB tags, which collect CIR data via two antennas. An indoor environment was set up with two MPCs and a strategically placed anchor. Data was collected from various tag locations and analyzed using the different localization methods. The collected CIR data revealed additional reflections, notably from the ceiling and ground, which sometimes interfered with the desired MPC reflections. To address this, data cleaning techniques were implemented for the likelihood method, and the two antennas were used to approximate the AoA in the fminsearch and multilateration methods. The final results demonstrated that the likelihood method achieved an average localization error of 26 cm, the fminsearch method 20.7 cm, and the algebraic method 24 cm. While the fminsearch method provided the best accuracy, it required data from two antennas, unlike the likelihood method, which only needed one. The fminsearch method showed improved accuracy near MPCs, though its performance declined as the tag moved further away. This suggests its potential for applications where AoA is large, as traditional methods become less accurate beyond 60-degree angles.