Overview

Included in degrees & certificates

• 124
• 535

Prerequisites

• PH3452

Learning Outcomes

Upon successful completion of this course, a student will:

• Understand how to apply the SONAR equation for single and multiple sensors in realistic environments using the decibel scale
• Understand, calculate, and convert levels between Power and Power Spectral Density with temporal and spatial windows (including Equivalent Noise Bandwidth ENBW) for a sinusoid received at an array of sensors
• Understand how to convert from microPascal to A/D counts for sinusoidal power given a typical set of transfer functions
• Understand the difference between auto- and cross-correlation and convolution for matched-filtering approaches with single sensors
• Understand beamforming principles and implement phase delays in the time- and frequency-domain for a linearly spaced array of N sensors for a single source
• Calculate conventional weights and implement a conventional beamforming (CBF) algorithm in the frequency domain for source parameter estimation (location, source level)
• Calculate adaptive weights and implement an adaptive beamforming (ABF) algorithm (MVDR) in the frequency domain to localize multiple sources
• Understand the principles and requirements for ABF (uncorrelated sources, full rank and invertible sample covariance matrix)
• Implement and evaluate additive white gaussian noise defined for single-sensor or array SNR in the frequency domain
• Execute and demonstrate learning objectives via a programming language (e.g., MATLAB) in simulations and with data