← Search

Angelo Coluccia

6 accepted papers

2026

OPTIMAL PLACEMENT OF MOVABLE ANTENNAS FOR ANGLE-OF-DEPARTURE ESTIMATION UNDER USER LOCATION UNCERTAINTY

ICASSP 2026oral

Movable antennas (MA) have gained significant attention in recent years to overcome the limitations of extremely large antenna arrays in terms of cost and power consumption. In this paper, we investigate the use of MA arrays at the base station (BS) for angle-of-departure (AoD) estimation under unce…

Cited by 0SourcePDFScholar
2023

Drone-vs-Bird Detection Grand Challenge at ICASSP2023

ICASSP 2023accepted

This paper presents the 6th edition of the "Drone-vs-Bird" Detection Grand Challenge, organized within the 48th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). Taking video samples recorded by commercial RGB cameras as input, the challenge stimulates the design of…

Cited by 0SourceScholar
2021

RIS-Aided Joint Localization and Synchronization with a Single-Antenna Mmwave Receiver

ICASSP 2021accepted

MmWave multiple-input single-output (MISO) systems using a single-antenna receiver are regarded as a promising solution for the near future, before the full-fledged 5G MIMO will be widespread. However, for MISO systems synchronization cannot be performed jointly with user localization unless two-way…

Cited by 0SourceScholar
2020

Low-Complexity Accurate Mmwave Positioning for Single-Antenna Users Based on Angle-of-Departure and Adaptive Beamforming

ICASSP 2020accepted

The problem of position estimation of a mobile user equipped with a single antenna receiver using downlink transmissions is addressed. The advantages of this setup compared to the classical MIMO and uplink scenarios are analyzed in terms of achievable theoretical performance (Cramér-Rao bounds) cons…

Cited by 0SourceScholar
2019

Online Estimation and Smoothing of a Target Trajectory in Mixed Stationary/moving Conditions

ICASSP 2019accepted

A novel maximum likelihood trajectory estimation algorithm for targets in mixed stationary/moving conditions is presented. The proposed approach is able to estimate position and velocity of the target over arbitrary complex trajectories, while explicitly taking into account the possibility of stop&g…

Cited by 0SourceScholar