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Passive Emitter Geo-Location

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Technical Training Short On Site Course Quote

This course covers the algorithms used to locate a stationary RF signal source, such as a radar, radio, or cell phone. The topics covered include: a review of vectors, matrices, and probability; linear estimation and Kalman filters; nonlinear estimation and extended Kalman filters; robust estimation; data association; measurement models for direction of arrival, time difference of arrival, and frequency difference of arrival; geo-location algorithms; performance analysis. Most of the course material is developed in planar Cartesian coordinates for simplicity; however, the extension to WGS84 coordinates is provided to equip the students for practical applications.


  • A course in statistics
  • A course in linear algebra / matrix theory



    Michael T. Grabbe is a Senior Staff Member in the Weapon and Targeting Systems Group at the Johns Hopkins University Applied Physics Laboratory. He has 20 years of experience working in the areas of ground emitter geo-location, target tracking, signal processing, and missile navigation. Prior to joining APL, he worked in these areas at L-3 Communications, Raytheon Missile Systems, and Texas Instruments. He received a B.S. degree in Engineering from the U.S. Naval Academy, an M.S. degree in Electrical Engineering from Southern Methodist University, an M.S. degree in Applied Mathematics from the University of Arkansas, and a Ph.D. in Mathematical Sciences from Clemson University. He holds three geo-location and tracking algorithm patents and is a Senior Member of the Institute of Electrical and Electronics Engineers.

    Contact this instructor (please mention course name in the subject line)

What You Will Learn:

  • Solve estimation problems using both batch processing and recursive algorithms
  • Develop mathematical models of quantities typically used for geo-location, such as Direction of Arrival (DOA), Time Difference of Arrival (TDOA), and Frequency Difference of Arrival (FDOA)
  • Predict geo-location performance for a given sensor-signal source geometry

Course Outline:

  1. Overview of geo-location systems

  2. Vectors and matrices

  3. Probability and statistics

  4. Linear estimation

  5. Optimal estimation

  6. Robust estimation

  7. Recursive estimation and Kalman filters

  8. Nonlinear estimation and extended Kalman filters

  9. Data association

  10. Measurement models for DOA, TDOA, FDOA

  11. Geo-location algorithms

  12. Geo-location performance analysis

  13. Geo-location in WGS84 coordinates


    Tuition for this three-day course is $1990 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to