Welcome! My name is Dr. Ramón Miralles, and I am an Electronic Engineer passionate about Science. I do research in Signal Processing & Machine Learning incorporating all aspects of the theory and practice in different areas: industry, acoustics, ecology and environment. You will find here an overview of the research I am doing as well as some Matlab libraries and manuscript drafts of scientific papers I have authored.
The two persons will join our interdisciplinary team composed by the Signal Processing Group and the Photonics Research Lab during the work done in the TED NextPAM project. The main objective of the NextPAM is to develop Fiber Optic Hydrophone (FOH) sensor system and its specific signal processing algorithms for Passive Acoustic Monitoring (PAM) applications. In order to achieve the main objective, we will: (i) study and develop fibre sensors that provide enough sensitivity and bandwidth to be employed in PAM, (ii) study and develop signal processing algorithms and acquisition systems capable of dealing with and exploiting these sensors' singular characteristics: low SNR and multichannel redundancy, (iii) build prototypes of the sensors, calibrate them, and measure them in a controlled environment, (iv) test some of the prototypes in two real PAM applications: 1/3 octave SPL measurement and cetacean calls detection. We are hiring a Machine learning and Signal processing specialist, and a Fiber Optic sensors specialist. The position is now OPEN and we will be accepting candidates until february 17th 2023. Details on how to apply cna be found here:
Machine learning and Signal processing specialist (Code 18053):
https://www.upv.es/entidades/SRH/conypi/1210276normalc.html"
and Fiber Optic sensors specialist (Code 18050):
https://www.upv.es/entidades/SRH/conypi/1210274normalc.html
We have received fundings to reduce the impact of underwater noise on the marine environment of the Port of Cartagena. To achieve this, some of the project objectives are: Identification and characterisation of underwater noise sources; Mapping and assessment of the impact of underwater noise on biodiversity, by monitoring the abundance, distribution and physiological state of three protected cetacean species: bottlenose dolphin (Tursiops truncates), striped dolphin (Stenella coeruleoalba) and long-finned pilot whale (Globicephala melas). Development and implementation of noise mitigation measures.
Our work explaining how to use a risk-based approach to asses the effect of continuous noise has been published in open access. You can read it here.
The fin whale (Balaenoptera physalus) is the second-largest species of whale and typically travel in the open seas, away from the coast, so they are difficult to track. We will study the behaviour of these amazing animals using acoustic techniques in our new project (CaboRorcual) Funded by the "Fundación Biodiversidad".
You can listen here to audio files and see visual representations of the sounds of different cetacean species: Sperm Whales, Fin Whales, etc. All the sounds have been recorded with our SAMARUC passive acoustic recorder in the Spanish coastal waters of the Mediterranean Sea.
Passive Acoustic Monitoring (PAM) surveys are appropriated for detection and monitoring of cetaceans and anthropogenic noises. We are using a system we have developed here at the UPV named SAMARUC. Read more here about our system and the long-term campaigns we are doing in the Mediterranean sea.
Measuring predictability in ultrasonic signals can provide information of the signal strength of the deterministic component of the time series in relation to the whole time series acquired. In this work we propose using this parameter in nondestructive testing for the characterization of scattering materials. Read more and download the supplementary MATLAB toolbox.