This module can only be taken as part of the Expeditionary Warfare Systems Engineering and Technology MSc (USA).

To provide the students with an understanding of various processing algorithms and methods that are applicable to modern sensor systems.

At a glance

  • Dates
    • 13 - 17 Jun 2022
  • Duration5 days
  • LocationNSWC Crane, Indiana, USA

Course structure

Lectures, tutorials, computer based practical’s; video practical

What you will learn

On successful completion of this module a student should be able to:


Knowledge and Understanding

- Describe and analyze the principles, capabilities and limitations of a number of different sensor processing methods, algorithms and schemes
- Critically assess performance of neural network models
- Evaluate computational models for dealing with uncertainty; discern the utility of Bayesian and Fuzzy models


Skills and Other Attributes:

- Compare and contrast different estimation methods and tools when applied to a specific problem and devise a distributed or centralized processing scheme based on this comparison
- Design, develop and implement models in MATLAB



Core content

• Adaptive Signal Processing: Adaptive FIR and spatial filters, error surface, Newton’s method, gradient search method, LMS algorithm, practical examples
• Multi-layer perceptrons: Architecture, Back-propagation algorithm, performance of the algorithm, Unsupervised learning, Hebbian learning, Kohonen maps, Neural network design in Matlab
• Overview of deep learning algorithms
• Sonar signal processing: Beamforming, passive analysis, active processing
• Fuzzy logic: fundamentals, fuzzy associative matrix, fuzzy inference
• Adaptive linear elements: Tapped delay lines, Noise cancellation, Time series prediction, 
• Sensor fusion: distributed sensor systems, sensor coverage, distributed vs centralised systems
• Sensor processing: Genetic algorithms, evolutionary algorithms, artificial neural nets
• MATLAB: practical sessions, demonstrating the above concepts in Matlab


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