Advanced Signal Processing and Instrumentation Research Lab(ASPIRE)

Prof. (Dr.) Supriya M.H.

Faculty in Charge
  • Contact Info
  • Address:Cochin
  • Phone:+91 484 2862320/33

Welcome To Field of Signal Processing

A subsidiary of CUCENTOL with major focus on the signal processing aspects of acoustic data, especially underwater imaging, navigation and analysis of ambient noise field.

Lab setup

Set up with financial assistance from funding agencies like MHRD, UGC, DST, DoE,etc


Active MoUs with niche design and development companies in this domain as well as other prestigious national institutes.


Faculty members over the past years with highly cited research outputs and their research scholars often bagging best paper Awards


Visiting professorships to & from universities and centers of excellence abroad and academic/industry collaborations benefitting both the current students as well as the faculty members

Important facilities
  • DAQ System for Underwater Passive Acoustic Data Collection
  • Multi Element Hydrophone Array
  • USRP SDR System
  • Audio and Video Annotation Facility
Future Activities
  • Development of Biomimetic Sonar Systems
  • Passive Acoustic Target Localization and Tracking using Deep Learning
  • Spatial Filtering of Passive Acoustic Targets using ML Techniques
  • Development of Image Enhancement Techniques for SONAR images using AI Techniques

Research Scholars

Lots of Ph.D has been produced in the area of Signal Processing

Ph.D Produced

The department intends to further strengthen the research in the strategic area of the Underwater sector, which the Government of India is keenly exploring through the Deep Ocean mission.

Awardee Name Title Year
Binsu C. Kovoor Improved Biometric Authentication System using Multimodal Cue Integration 2016
Rithu James Blind Estimation of Sonar Images from Diverse Speckle-Scene Models 2018
Alex Raj S.M. Reconfigurable Platform Based Design in FPGA for Underwater Image Enhancement, Object detection and Pipeline Tracking 2018
Sherin B.M. Underwater Target Classifier with Improved Success Rate using Meta-Optimal Support Vector Machines 2019
Shameer K Mohammed HMM based Underwater Target Classifiers with Rayleigh Fading Compensation 2020
Suraj Kamal Passive Sonar Automated Target Classification using Deep Hierarchical Feature Learning Approaches Submitted 2021
Vijeesh P Development of a Crystallizer-Image Analyzer System and Its Application in Optical Bandgap Modification of Tri Glycine Sulphate Submitted 2021
Satheesh Chandran C Passive Acoustic Classification of Underwater Targets using Unsupervised Representation Learning Schemes Submitted 2021