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Satellite networks are recognized as an effective solution to ensure seamless connectivity worldwide, catering to a diverse range of applications. However, the broad coverage and broadcasting nature of satellite networks also expose them to…
Satellite networks are emerging as vital solutions for global connectivity beyond 5G. As companies such as SpaceX, OneWeb, and Amazon are poised to launch a large number of satellites in low Earth orbit, the heightened inter-satellite…
Synthetic Aperture Radar (SAR) images contain a huge amount of information, however, the number of practical use-cases is limited due to the presence of speckle noise in them. In recent years, deep learning based techniques have brought…
In the context of 6G ubiquitous connectivity, the space-air-ground-sea integrated network (SAGSIN) emerges as a new paradigm to provide critical services for resource-limited ocean environments. To realize this paradigm efficiently, we…
In this paper, we investigate joint 3-dimensional (3D) trajectory planning and resource allocation for rotary-wing unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) sensing. To support emerging real-time SAR applications and…
Satellite Laser Ranging (SLR) is an established technique providing very accurate position measurements of satellites in Earth orbit. However, despite decades of development, it remains a complex and expensive technology, which impedes its…
In this paper, we study the trajectory and resource optimization for lightweight rotary-wing unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR) system. The UAV's mission is to perform SAR imaging of a given area…
The Agile Earth Observation Satellite Scheduling Problem (AEOSSP) entails finding the subset of observation targets to be scheduled along the satellite's orbit while meeting operational constraints of time, energy and memory. The problem of…
We consider a joint scheduling-and-power-allocation problem of a downlink cellular system. The system consists of two groups of users: real-time (RT) and non-real-time (NRT) users. Given an average power constraint on the base station, the…
The reconstructed images from the Synthetic Aperture Radar (SAR) data suffer from multiplicative noise as well as low contrast level. These two factors impact the quality of the SAR images significantly and prevent any attempt to extract…
This paper focuses on the optimal design of a modulated retroreflector (MRR) laser link to establish a high-speed downlink for cube satellites (CubeSats), taking into account the weight and power limitations commonly encountered by these…
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent in satellite data, most of the current object classification…
Satellite imaging generally presents a trade-off between the frequency of acquisitions and the spatial resolution of the images. Super-resolution is often advanced as a way to get the best of both worlds. In this work, we investigate…
Satellite remote sensing is playing an increasing role in the rapid mapping of damage after natural disasters. In particular, synthetic aperture radar (SAR) can image the Earth's surface and map damage in all weather conditions, day and…
As low Earth orbit (LEO) satellite communication systems are gaining increasing popularity, new theoretical methodologies are required to investigate such networks' performance at large. This is because deterministic and location-based…
Synthetic aperture radar (SAR) on unmanned aerial vehicles (UAVs) enables high-resolution sensing in low-altitude wireless networks, while requiring reliable uplink data backhaul to ground base stations under dynamic channel conditions.…
Synthetic aperture radar technology is crucial for high-resolution imaging under various conditions; however, the acquisition of real-world synthetic aperture radar data for deep learning-based automatic target recognition remains…
The integration of Low Earth Orbit (LEO) satellite constellations into 5G and Beyond is essential to achieve efficient global connectivity. As LEO satellites are a global infrastructure with predictable dynamics, a pre-planned fair and…
As the important component of the Earth observation system, hyperspectral imaging satellites provide high-fidelity and enriched information for the formulation of related policies due to the powerful spectral measurement capabilities.…
In this paper, we introduce an innovative super resolution approach to emerging modes of near-field synthetic aperture radar (SAR) imaging. Recent research extends convolutional neural network (CNN) architectures from the optical to the…