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Found 19 papers, 0 papers with code
Classification Schemes for the Radar Reference Window: Design and Comparisons
In this paper, we address the problem of classifying data within the radar reference window in terms of statistical properties.
Multiple Sub-Pixel Target Detection for Hyperspectral Imaging Systems
Hyperspectral target detection is a task of primary importance in remote sensing since it allows identification, location, and discrimination of target features.
Innovative Cognitive Approaches for Joint Radar Clutter Classification and Multiple Target Detection in Heterogeneous Environments
The joint adaptive detection of multiple point-like targets in scenarios characterized by different clutter types is still an open problem in the radar community.
A Unified Theory of Adaptive Subspace Detection. Part II: Numerical Examples
If, instead, the signal subspace is known only by its dimension, the performance of GLR and EP detectors is very similar.
Clutter Edges Detection Algorithms for Structured Clutter Covariance Matrices
This letter deals with the problem of clutter edge detection and localization in training data.
Unsupervised Sparse Unmixing of Atmospheric Trace Gases from Hyperspectral Satellite Data
In this letter, a new approach for the retrieval of the vertical column concentrations of trace gases from hyperspectral satellite observations, is proposed.
Adaptive Radar Detection in Heterogeneous Clutter-dominated Environments
In this paper, we propose a new solution for the detection problem of a coherent target in heterogeneous environments.
A Unified Theory of Adaptive Subspace Detection. Part I: Detector Designs
The noises in these two channels share a common covariance matrix, up to a scale, which may be known or unknown.
EM-based Solutions for Covariance Structure Detection and Classification in Polarimetric SAR Images
This paper addresses the challenge of classifying polarimetric SAR images by leveraging the peculiar characteristics of the polarimetric covariance matrix (PCM).
Design and Experimental Assessment of Detection Schemes for Air Interface Attacks in Adverse Scenarios
In this letter, we propose three schemes designed to detect attacks over the air interface in cellular networks.
Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells
This letter addresses the detection problem of dim maneuvering targets in the presence of range cell migration.
Adaptive Radar Detection and Classification Algorithms for Multiple Coherent Signals
In this paper, we address the problem of target detection in the presence of coherent (or fully correlated) signals, which can be due to multipath propagation effects or electronic attacks by smart jammers.
Geostationary Real-Time 3D Polarimetric RADAR Imaging by Orbital Angular Momentum Interferometry and Multi-Chromatic Analysis
Each OAM fast-time RADAR image is separated in frequency by using MCA.
Novel Parameter Estimation and Radar Detection Approaches for Multiple Point-like Targets: Designs and Comparisons
In this work, we develop and compare two innovative strategies for parameter estimation and radar detection of multiple point-like targets.
Gait Recognition using FMCW Radar and Temporal Convolutional Deep Neural Networks
The capability of human identification in specific scenarios and in a quickly and accurately manner, is a critical aspect in various surveillance applications.
Radar Adaptive Detection Architectures for Heterogeneous Environments
In this paper, four adaptive radar architectures for target detection in heterogeneous Gaussian environments are devised.
A Unifying Framework for Adaptive Radar Detection in the Presence of Multiple Alternative Hypotheses
This analysis highlights that the architectures devised within the proposed framework represent an effective means to deal with detection problems where the uncertainty on some parameters leads to multiple alternative hypotheses.
Monitoring of Critical Infrastructures by Micro-Motion Estimation: the Mosul Dam Destabilization
In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures.
Learning Strategies for Radar Clutter Classification
The classification procedure relies on a model for the observables including latent variables that is solved by the expectation-maximization algorithm.
