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About

About

I got my graduation in Electrical and Computer Engineering in the Faculty of Engineering of the University of Porto in 1985. Since then, I was admitted as a teaching assistant in the Faculty of Engineering of the University of Porto and, at the same time, I entered in the recently created INESC in Porto. In the first years I have developed work in the areas of Operational Research, Computer Graphics and Microelectronics, the topic of my final graduation project. For several years I was with the group CAD & Microelectronics at INESC and more recently I joined the Center of Robotic and Autonomous Systems, where I have collaborated in the design and development of marine robotic systems, in particular high autonomy unmanned marine vehicles.

I concluded my PhD in Electrical and Computer Engineering in 1998, in the area of the design and development of custom computing systems. Presently I am Associate Professor in the Faculty of Engineering of the University of Porto, where I have been teaching in the areas of advanced digital design for integrated technologies, digital microelectronics and electric circuit analysis. My main R&D area is on the design and implementation of custom computing systems in reconfigurable digital systems, currently supported by FPGA technology (Field-Programmable Gate Arrays).

Interest
Topics
Details

Details

  • Name

    José Carlos Alves
  • Role

    Senior Researcher
  • Since

    27th June 1985
011
Publications

2023

Single Receiver Underwater Localization of an Unsynchronized Periodic Acoustic Beacon Using Synthetic Baseline

Authors
Ferreira, BM; Graça, PA; Alves, JC; Cruz, NA;

Publication
IEEE JOURNAL OF OCEANIC ENGINEERING

Abstract
This article addresses the 3-D localization of a stand-alone acoustic beacon based on the Principle of Synthetic Baseline using a single receiver on board a surface vehicle. The process only uses the passive reception of an acoustic signal with no explicit synchronization, interaction, or communication with the acoustic beacon. The localization process exploits the transmission of periodic signals without synchronization to a known time reference to estimate the time-of-arrival (ToA) with respect to an absolute time basis provided by the global navigation satellite system (GNSS). We present the development of the acoustic signal acquisition system, the signal processing algorithms, the data processing of times-of-arrival, and an estimator that uses times-of-arrival and the coordinates where they have been collected to obtain the 3-D position of the acoustic beacon. The proposed approach was validated in a real field application on a search for an underwater glider lost in September 2021 near the Portuguese coast.

2023

Sensor Placement in an Irregular 3D Surface for Improving Localization Accuracy Using a Multi-Objective Memetic Algorithm

Authors
Graca, PA; Alves, JC; Ferreira, BM;

Publication
SENSORS

Abstract
Accurate localization is a critical task in underwater navigation. Typical localization methods use a set of acoustic sensors and beacons to estimate relative position, whose geometric configuration has a significant impact on the localization accuracy. Although there is much effort in the literature to define optimal 2D or 3D sensor placement, the optimal sensor placement in irregular and constrained 3D surfaces, such as autonomous underwater vehicles (AUVs) or other structures, is not exploited for improving localization. Additionally, most applications using AUVs employ commercial acoustic modems or compact arrays, therefore the optimization of the placement of spatially independent sensors is not a considered issue. This article tackles acoustic sensor placement optimization in irregular and constrained 3D surfaces, for inverted ultra-short baseline (USBL) approaches, to improve localization accuracy. The implemented multi-objective memetic algorithm combines an evaluation of the geometric sensor's configuration, using the Cramer-Rao Lower Bound (CRLB), with the incidence angle of the received signal. A case study is presented over a simulated homing and docking scenario to demonstrate the proposed optimization algorithm.

2022

On the localization of an acoustic target using a single receiver

Authors
Ferreira, B; Alves, J; Cruz, N; Graca, P;

Publication
2022 OCEANS HAMPTON ROADS

Abstract
This paper addresses the localization of an unsynchronized acoustic source using a single receiver and a synthetic baseline. The enclosed work was applied in a real search of an electric glider that was lost at sea and later recovered, using the described approach. The search procedure is presented along with the localization methods and a metric based on the eigenvalues of the Fisher Information Matrix is used to quantify the expected uncertainty of the estimate.

2022

Multi-Objective Optimization of Sensor Placement in a 3D Body for Underwater Localization

Authors
Graca, PA; Alves, JC; Ferreira, BM;

Publication
2022 OCEANS HAMPTON ROADS

Abstract
Underwater acoustic localization is a challenging task. Most techniques rely on a network of acoustic sensors and beacons to estimate relative position, therefore localization uncertainty becomes highly dependent on the selected sensor configuration. Although several works in literature exploit optimal sensor placement to improve localization over large regions, the conditions contemplated in these are not applicable for the optimization of the acoustic sensors on constrained 3D shapes, such as the body of small underwater vehicles or structures. Additionally, most commercial systems used for localization with ultra-short baseline (USBL) configurations have compact acoustic sensors that cannot be spatially positioned independently. This work tackles the optimization of acoustic sensor placement in a limited 3D shape, in order to improve the localization accuracy for USBL applications. The implemented multi-objective memetic algorithm combines the Cramer-Rao Lower Bound (CRLB) configuration evaluation with incidence angle considerations for the sensor placement.

2022

Image segmentation and mapping in an underwater environment using an imaging sonar

Authors
Goncalves, PM; Ferreira, BM; Alves, JC; Cruz, NA;

Publication
2022 OCEANS HAMPTON ROADS

Abstract
Autonomous underwater vehicles (AUV) are increasing in popularity and importance for the realization of underwater explorations. Nowadays, these types of vehicles are implemented in underwater environments to accomplish tasks for military, scientific and industrial purposes. These vehicles can use imaging sonars that are effective in detecting the AUV's distance to an obstacle. The main goals of this paper were to extract meaningful information gathered by sonar, use it to map the surrounding environment, and locate the vehicle on the estimated map. To accomplish these goals, the system is composed of a constant false alarm rate (CFAR) algorithm to filter the sonar information, a feature extractor that filters the first obstacle for each sonar beam in a 360 degrees revolution, an Octomap to build the estimated map and a Particle Filter (PF) to locate the vehicle in the environment. This system was developed using a set of measurements in a rectangular tank where the AUV was in static positions and in motion.

Supervised
thesis

2022

Intelligent Auto Scalling (Dev Ops)

Author
Tiago Manuel Gonçalves Lameira

Institution
UM

2022

Advanced Analysis of Extracellular Potentials: Exploring the Generation of Local Field Potentials

Author
João Almeida Santiago

Institution
UP-FEUP

2022

Modular Architecture for 3D Game Environment Art with Photogrammetry

Author
Nataska Statham

Institution
UP-FEUP

2022

Autonomous Optimization for a Transactional Middleware

Author
Susana Vitória Sá Silva Marques

Institution
UM

2021

Previsão da Evolução do Covid-19 por Região

Author
MARCELO ZEFERINO VIEIRA FERREIRA

Institution
IPP-ISEP