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ECE Course Syllabus

ECE6279 Course Syllabus


Spatial Array Processing (3-0-3)

Technical Interest
Digital Signal Processing

ECE 4270


Catalog Description
Introduce application areas where signals are sampled over space and time. Transfer knowledge of time-based techniques to spatial processing. Develop algorithms unique to spatial processing.

Johnson & Dugeon, Array Signal Processing: Concepts and Techniques, Prentice Hall, 1993. ISBN 9780130485137 (required)

Indicators (SPIs)
SPIs are a subset of the abilities a student will be able to demonstrate upon successfully completing the course.

Topical Outline
1.	Introduction
	a.	Propagating Waves
	b.	Wavenumber-Frequency Space
	c.	Apertures
2.	Conventional Beamforming
	a.	Delay-and-Sum Beamforming (Plane Waves and Spherical Waves)
	b.	Filter-and-Sum Beamforming 
	c.	Quadrature Demodulation
	d.	Conventional Narrowband Beamforming
	e.	Conventional Wideband Beamforming
3.	Second-Order Statistical Modeling
	a.	Stochastic Narrowband Models 
	b.	Signal to Noise Ratios
	c.	Time Averaging 
	d.	Spatial Averaging and Co-arrays 
4.	Subspace Methods
	a.	Constrained Optimization
	b.	MVDR Beamforming
	c.	Pisarenko Harmonic Decomposition
	d.	Subspace Methods: Eigenvalue Method and MUSIC
	e.	Root MUSIC 
	g.	Robust Constrained Estimation
5.	Estimation-Theoretic Methods
	a.	Introduction to Estimation Theory
	b.	"Stochastic? and ?Deterministic? Signal Gaussian Models 
	c.	Maximum-Likelihood Estimation
	d.	Introduction to Cramer-Rao Bounds 
	e.	Cramer-Rao Bounds for Arrays
	f.	Transformations of Cramer-Rao Bounds
	g.	Model Order Estimation 
	h.	Unconstrained Covariance Estimation