Spatial Array Processing


CMPE Degree: This course is Not Applicable for the CMPE degree.

EE Degree: This course is Not Applicable for the EE degree.

Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Group(s) / Course Type(s): Digital Signal Processing

Course Coordinator:

Prerequisites: ECE 4270

Corequisites: None.

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.

Course Outcomes

Not Applicable

Student Outcomes

In the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.

1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. ( Not Applicable ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors

3. ( Not Applicable ) An ability to communicate effectively with a range of audiences

4. ( Not Applicable ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts

5. ( Not Applicable ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

6. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions

7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Strategic Performance Indicators (SPIs)

Not Applicable

Course Objectives

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