Related papers: Tensor-based Space Debris Detection for Satellite …
Canonical polyadic decomposition (CPD) is at the core of fast matrix multiplication, a computational problem with widespread implications across several seemingly unrelated problems in computer science. Much recent progress in this field…
This study presents a novel multi-static radar technique for space debris characterisation using micro-Doppler signatures, developed within the Southern Hemisphere Asteroid Radar Programme (SHARP). The method employs C-band continuous…
Hyper spectral imaging is a remote sensing technology, providing variety of applications such as material identification, space object identification, planetary exploitation etc. It deals with capturing continuum of images of the earth…
Non-destructive testing is an important technique for detecting defects in multi-layer materials, enabling the evaluation of structural integrity without causing damage on test materials. Terahertz time-domain spectroscopy (THz-TDS) offers…
Space debris and inactive satellites pose a threat to the safety and integrity of operational spacecraft and motivate the need for space situational awareness techniques. These uncooperative targets create a challenging tracking and…
A chaser satellite equipped with robotic arms can capture space debris and manipulate it for use in more advanced missions such as refueling and deorbiting. To facilitate capturing, a caging-based strategy has been proposed to simplify the…
The CANDECOMP/PARAFAC (CP) decomposition is a leading method for the analysis of multiway data. The standard alternating least squares algorithm for the CP decomposition (CP-ALS) involves a series of highly overdetermined linear least…
Imaging Science Subsystem (ISS) mounted on the Cassini spacecraft has taken a lot of images, which provides an important source of high-precision astrometry of some planets and satellites. However, some of these images are degraded by…
The canonical polyadic (CP) tensor decomposition decomposes a multidimensional data array into a sum of outer products of finite-dimensional vectors. Instead, we can replace some or all of the vectors with continuous functions…
The CANDECOMP/PARAFAC (or Canonical polyadic, CP) decomposition of tensors has numerous applications in various fields, such as chemometrics, signal processing, machine learning, etc. Tensor CP decomposition assumes the knowledge of the…
A novel tensor decomposition framework, termed Tensor Star (TS) decomposition, is proposed which represents a new type of tensor network decomposition based on tensor contractions. This is achieved by connecting the core tensors in a ring…
The exponential increase in orbital debris and active satellites will lead to congested orbits, necessitating more frequent collision avoidance maneuvers by satellites. To minimize fuel consumption while ensuring the safety of satellites,…
Orbital debris is a constraint on the long-term health of any spacecraft and must be considered during mission planning. Varying mechanisms have been proposed to quantify the problem. Assessment of orbital debris employing ground-based…
This work utilizes a MobileNetV2 Convolutional Neural Network (CNN) for fast, mobile detection of satellites, and rejection of stars, in cluttered unresolved space imagery. First, a custom database is created using imagery from a synthetic…
In recent years, the application of tensors has become more widespread in fields that involve data analytics and numerical computation. Due to the explosive growth of data, low-rank tensor decompositions have become a powerful tool to…
This work considers low-rank canonical polyadic decomposition (CPD) under a class of non-Euclidean loss functions that frequently arise in statistical machine learning and signal processing. These loss functions are often used for certain…
Conducting surveillance of the Earth's orbit is a key task towards achieving space situational awareness (SSA). Our work focuses on the optical detection of man-made objects (e.g., satellites, space debris) in Geostationary orbit (GEO),…
Multi-connected universe models with space identification scales smaller than the size of the observable universe produce topological images of cosmic sources. We generalise to locally hyperbolic spaces the crystallographic method, aimed to…
There is growing demand for satellite swarms and constellations for global positioning, remote sensing and relay communication in higher LEO orbits. This will result in many obsolete, damaged and abandoned satellites that will remain…
Although vital for life on Earth, solar activity poses questions and increasing threats to humanity due to the Sun's unknown dynamics, intensified by our dependence on terrestrial and space-based infrastructure. This situation is compounded…