Related papers: Genetic Optimization of a Software-Defined GNSS Re…
There is a growing need for vehicle positioning information to support Advanced Driver Assistance Systems (ADAS), Connectivity (V2X), and Automated Driving (AD) features. These range from a need for road determination (<5 meters), lane…
Autonomous unmanned aerial vehicle (UAV) inertial navigation exhibits an extreme dependency on the availability of global navigation satellite systems (GNSS) signals, without which it incurs in a slow but unavoidable position drift that may…
A reconfigurable intelligent surface (RIS) endows a wireless channel with programmability that can be leveraged to optimize wireless information transfer. While many works study algorithms for optimizing such a programmable channel,…
With the rapid expansion of low Earth orbit (LEO) constellations, thousands of satellites are now in operation, many equipped with onboard GNSS receivers capable of continuous orbit determination and time synchronization. This development…
Indoor positioning is one of the core technologies of Internet of Things (IoT) and artificial intelligence (AI), and is expected to play a significant role in the upcoming era of AI. However, affected by the complexity of indoor…
Low earth orbit (LEO) satellite navigation signal can be used as an opportunity signal in case of a Global navigation satellite system (GNSS) outage, or as an enhancement means of traditional GNSS positioning algorithms. No matter which…
In urban areas, the quality of global navigation satellite system (GNSS) signals deteriorates, leading to reduced positioning accuracy. To address this issue, 3D-mapping-aided (3DMA) techniques, such as shadow matching and zonotope shadow…
The integration of non-terrestrial networks (NTN) into 5G new radio (NR) has opened up the possibility of developing a new positioning infrastructure using NR signals from Low-Earth Orbit (LEO) satellites. Compared to existing Global…
The design of an indigenous Lunar Navigation Satellite System (LNSS) is receiving growing attention due to the surge in planned lunar missions and the limited accessibility of Earth-based Global Navigation Satellite Systems (GNSS) in the…
This paper proposes an optimization problem formulation to tackle the challenges of cislunar Space Domain Awareness (SDA) through multi-spacecraft monitoring. Due to the large volume of interest as well as the richness of the dynamical…
This work proposes a framework for the robust design of UAV-assisted wireless networks that combine 3D trajectory optimization with user mobility prediction to address dynamic resource allocation challenges. We proposed a sparse…
The global navigation satellite systems (GNSS) play a vital role in transport systems for accurate and consistent vehicle localization. However, GNSS observations can be distorted due to multipath effects and non-line-of-sight (NLOS)…
Although direct position estimation (DPE) has been demonstrated to offer enhanced robustness in GNSS receivers, its theoretical limits and performance in OFDM based positioning systems remain largely unexplored. In this paper, the…
Ultra-reliable and low-latency communication (URLLC) is one of the three major service classes supported by the fifth generation (5G) New Radio (NR) technical specifications. In this paper, we introduce a physical layer architecture that…
Due to their low cost and low power consumption, single-frequency GPS receivers are considered suitable for low-cost space applications such as small satellite missions. Recently, requirements have emerged for real-time accurate orbit…
The rapid development of technology has led to an increase in the number of devices that rely on position, velocity, and time (PVT) information to perform their functions. As such, the Global Navigation Satellite Systems (GNSS) have been…
Software defined radio (SDR) has become a popular tool for the implementation and testing for communications performance. The advantage of the SDR approach includes: a re-configurable design, adaptive response to changing conditions,…
Robust navigation in urban environments has received a considerable amount of both academic and commercial interest over recent years. This is primarily due to large commercial organizations such as Google and Uber stepping into the…
Modern machine learning often requires training with large batch size, distributed data, and massively parallel compute hardware (like mobile and other edge devices or distributed data centers). Communication becomes a major bottleneck in…
The emerging drone swarms are capable of carrying out sophisticated tasks in support of demanding Internet-of-Things (IoT) applications by synergistically working together. However, the target area may be out of the coverage of the ground…