Dr. Kevin R. Ford earned the B.S. degree in Mechanical Engineering in 2010, the M.S. in Electrical Engineering in 2011 from Lehigh University in Bethlehem, PA, and the Ph.D. degree in electrical engineering from the University of Maryland at College Park in 2022. Dr. Ford is a lecturer in the Applied Mathematics Department at the Johns Hopkins University Engineering for Professionals. He is also a member of the Senior Professional Staff at the Johns Hopkins University Applied Physics Laboratory (JHU/APL), where he has worked since 2011.
Dr. Ford is an active member of the Institute of Electrical and Electronics Engineers (IEEE), where he has published multiple journal articles. He is also a member of the Association of Old Crows (AOC), an organization specializing in electronic warfare, tactical information operations, and associated disciplines. His research interests include complex system optimization, nonlinear filtering, target tracking, and radar modeling and simulation.
Education History
- B.S., Mechanical Engineering, Lehigh University
- M.S., Electrical Engineering, Lehigh University
- Ph.D, Electrical Engineering, University of Maryland, College Park
Work Experience
Instructor, JHU Whiting School of Engineering, Engineering for Professionals
Publications
Ford, Kevin R.. “Nonlinear Target Tracking Methods for Near-Radially Inbound Targets”, PhD Dissertation, University of Maryland at College Park, 2022.
Ford, Kevin R., Haug, Anton J.. “The Probability Density Function of Bearing Obtained from a Cartesian-to-Polar Transformation”, Institute of Electrical and Electronics Engineers (IEEE), vol. 10, pp. 32803-32809. 2022, Available: https://doi.org/10.1109%2Faccess.2022.3161974.
Ford, Kevin R., Haug, Anton J.. “A Study of Endpoint-Constrained Nonlinear Tracking Filters”, IEEE Transactions on Aerospace and Electronic Systems, vol. 57, no. 6, pp. 3952-3961. 2021.
Haug, Anton J., Ford, Kevin R.. “An end-point-constrained extended Kalman filter for tracking maneuvering near-radially inbound targets”, 2016 19th International Conference on Information Fusion (FUSION), pp. 312-318. FUSION, Heidelberg, Germany, August, 2016.
Professional Organizations
IEEE
Association of Old Crows
Courses
General Applied Mathematics
625.201
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