activity
20192026
most citedNew ECCM Techniques Against Noise-like and/or Coherent Interferers

98 citations · 298 across the 15 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

eess.SP2020★ 49 cited

Adaptive Radar Detection and Classification Algorithms for Multiple Coherent Signals

Sudan Han, Linjie Yan, Yuxuan Zhang +3

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…

eess.SP2020

Geostationary Real-Time 3D Polarimetric RADAR Imaging by Orbital Angular Momentum Interferometry and Multi-Chromatic Analysis

Filippo Biondi, Pia Addabbo, Carmine Clemente +2

We design the proof of concept for high-resolution (HR) real-time (RT), Geosynchronous and Geostationary (Geo) Polarimetric (Pol) using orbital angular momentum (OAM) interferometr…

eess.SP2020★ 24 cited

Novel Parameter Estimation and Radar Detection Approaches for Multiple Point-like Targets: Designs and Comparisons

Pia Addabbo, Jun Liu, Danilo Orlando +1

In this work, we develop and compare two innovative strategies for parameter estimation and radar detection of multiple point-like targets. The first strategy, which appears here f…

eess.SP2020

Monitoring of Critical Infrastructures by Micro-Motion Estimation: the Mosul Dam Destabilization

Filippo Biondi, Pia Addabbo, Carmine Clemente +2

In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures. Particularly, through the analysis of COSMO-SkyMed satellite data, a detai…

eess.SP2020★ 1 cited

A Sparse Learning Approach to the Detection of Multiple Noise-Like Jammers

Linjie Yan, Pia Addabbo, Yuxuan Zhang +4

In this paper, we address the problem of detecting multiple Noise-Like Jammers (NLJs) through a radar system equipped with an array of sensors. To this end, we develop an elegant a…

eess.SP2020

Learning Strategies for Radar Clutter Classification

Pia Addabbo, Sudan Han, Danilo Orlando +1

In this paper, we address the problem of classifying clutter returns in order to partition them into statistically homogeneous subsets. The classification procedure relies on a mod…