Improving angle and time estimation for concurrent Ultra-wideband localization through transmitter-side techniques

Many internet of things (IoT) applications nowadays rely on positioning systems to optimize their decision making. GPS is one of the most used location providers in many of these systems. However, it lacks in accuracy and precision inside buildings. Ultra-wideband (UWB) is becoming a significant localization technology enabler for indoor environments with an accuracy of ∼10 cm. Recent approaches focused on scalability and efficiency by using anchor-side concurrent transmissions (TX) and extracting the time and phase information from the channel impulse response (CIR) of the UWB signal on the receiver side (tag). Concurrent time-based and phase-based localization represent the state-of-the-art techniques for UWB localization. However, when combined with concurrency, they can face many challenges. Concurrent time-based methods currently lack in accuracy due to hardware timing limitations related to channel impulse response (CIR) granularity and transmission (TX) scheduling uncertainty problem. Phase-based techniques solved the accuracy issue as they are independent from timing uncertainties. However, they require the localized targets to have dual-chip devices to calculate the Angle of Arrival (AoA). With a large number of targets to localize, the cost and complexity of the system are expected to increase. In this dissertation, we focus on three main challenges: (1) simplifying the tag complexity through designing a single-antenna tag AoA estimation system by measuring the phase difference from the CIR resulting from intra-anchor concurrency; (2) improving ToA-based concurrent solutions that use large transmission delays by mitigating the pairwise RX precision loss resulting from the TX scheduling uncertainty problem using new transmitter-side techniques in inter-anchor concurrency; (3) Combine inter-anchor and intra-anchor concurrency to provide an accurate, efficient and scalable phase-based and time-based estimation solution that offloads cost and complexity to anchors. In this research, we designed different algorithms and systems. We also proved their performance in real-world via implementation and evaluation on state-of-the-art platforms.