Daniel Neamati
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View article: Satellite Autonomous Clock Fault Monitoring with Inter-Satellite Ranges Using Euclidean Distance Matrices
Satellite Autonomous Clock Fault Monitoring with Inter-Satellite Ranges Using Euclidean Distance Matrices Open
To address the need for robust positioning, navigation, and timing services in lunar environments, this paper proposes a novel onboard clock phase jump detection framework for satellite constellations using range measurements obtained from…
View article: gnss_lib_py: Analyzing GNSS data with Python
gnss_lib_py: Analyzing GNSS data with Python Open
This paper presents gnss_lib_py, a Python library used to parse, analyze, and visualize data from a variety of GNSS (Global Navigation Satellite Systems) data sources. The gnss_lib_py library’s ease of use, modular capabilities, testing co…
View article: Autonomous Constellation Fault Monitoring with Inter-satellite Links: A Rigidity-Based Approach
Autonomous Constellation Fault Monitoring with Inter-satellite Links: A Rigidity-Based Approach Open
To address the need for robust positioning, navigation, and timing services in lunar environments, this paper proposes a novel fault detection framework for satellite constellations using inter-satellite ranging (ISR). Traditionally, navig…
View article: Mosaic Zonotope Shadow Matching for Risk-Aware Autonomous Localization in Harsh Urban Environments
Mosaic Zonotope Shadow Matching for Risk-Aware Autonomous Localization in Harsh Urban Environments Open
Risk-aware urban localization with the Global Navigation Satellite System (GNSS) remains an unsolved problem with frequent misdetection of the user's street or side of the street. Significant advances in 3D map-aided GNSS use grid-based GN…
View article: Learning-based methods to model small body gravity fields for proximity operations: Safety and Robustness
Learning-based methods to model small body gravity fields for proximity operations: Safety and Robustness Open
Accurate gravity field models are essential for safe proximity operations around small bodies. State-of-the-art techniques use spherical harmonics or high-fidelity polyhedron shape models. Unfortunately, these techniques can become inaccur…
View article: A machine learning algorithm for identifying and tracking bacteria in three dimensions using Digital Holographic Microscopy
A machine learning algorithm for identifying and tracking bacteria in three dimensions using Digital Holographic Microscopy Open
Digital Holographic Microscopy (DHM) is an emerging technique for three-dimensional imaging of microorganisms due to its high throughput and large depth of field relative to traditional microscopy techniques. While it has shown substantial…