Emitter Location, DF, and Frequency Estimation

Seminar Overview

Learn how the MUSIC algorithm and related signal subspace algorithms allow improved performance in important ELINT and EW applications. Understand the problems and the benefits of applying these modern techniques.

Seminar Outline

Day 1

Beamforming vs High Resolution DF
The Signal Subspace (Geometric) Approach
The Array Manifold
Calibrating an Array
Including Polarization Diversity
The MUSIC Algorithm
Locating Multiple Cochannel Sources
Detection: Deciding the Number of Signals
Geometric Solutions as Eigen System Algorithms
Estimating Parameters of Cochannel Sources
Introduction to Bivectors and Array Manifold
A Practical Problem: Interpolating the Array Manifold

Day 2

Copying the Signals of Cochannel Sources
Hypersensitivity in Copy
Algorithms of Burg, Capon, Prony, Pisarenko
Wideband Extensions and Problems
Frequency Measurement of Multiple Sinusoids
The FFT is not a "High Resolution" Method"
"Root" Algorithms
Detection: Deciding the Number of Sinusoids
Theoretical Limits on Accuracy

Day 3

Range (Range Rate) Difference Location
TOA, TDOA/FDOA Emitter Location
Hyperbolic Lines of Position
LOCA: Straight Lines Locating the Emitter
Hyperbolic Intersections vs LOCA
2D/3D Emitter Location
N Receiver Arrays
Least Squares Solutions Using Multilinear Algebra

Seminar Materials Provided

Seminar notes and a certificate for 2.2 Continuing Education Units.

Who Should Attend

This seminar provides the systems engineer and analyst with an understanding of the geometry of a signal processing system for emitter location, direction finding, frequency estimation. The participant should have the benefit of some prior exposure to linear algebra and vector space ideas. The seminar will include a minimum of mathematics (equations) but a large dose of new (to the engineering community) mathematical concepts and ideas.

Instructor(s)

Ralph O. Schmidt, Ph.D., has been active in signal processing work for over 30 years. His work in emitter location and direction finding led to new and important algorithms such as Multiple Signal Classification (MUSIC) and Location on the Conic Axis (LOCA). Dr. Schmidt, the author of many technical papers and reports, has several patents issued and pending, and is a Fellow of the IEEE.