ATI's Sonar Signal Processing Course

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Sonar Signal Processing

3-Day Course


This intensive short course provides an overview of sonar signal processing. Processing techniques applicable to bottom-mounted, hull-mounted, towed and sonobuoy systems will be discussed. Spectrum analysis, detection, classification, and tracking algorithms for passive and active systems will be examined and related to design factors. Advanced techniques such as high-resolution array-processing and matched field array processing, advanced signal processing techniques, and sonar automation will be covered. The course is valuable for engineers and scientists engaged in the design, testing, or evaluation of sonars. Physical insight and realistic performance expectations will be stressed. A comprehensive set of notes will be supplied to all attendees.

Sample Videos

Watch course outline video here.

  • Fundamental algorithms for signal processing.
  • Techniques for beam forming.
  • Trade-offs among active waveform designs.
  • Ocean medium effects.
  • Shallow water effects and issues
  • Optimal and adaptive processing
  1. Introduction to Sonar Signal Processing. Introduction to sonar detection systems and types of signal processing performed in sonar. Correlation processing, Fournier analysis, windowing, and ambiguity functions. Evaluation of probability of detection and false alarm rate for FFT and broadband signal processors.

  2. Beamforming and Array Processing. Beam patterns for sonar arrays, shading techniques for sidelobe control, beamformer implementation. Calculation of DI and array gain in directional noise fields.

  3. Passive Sonar Signal Processing. Review of signal characteristics, ambient noise, and platform noise. Passive system configurations and implementations. Spectral analysis and integration.

  4. Active Sonar Signal Processing. Waveform selection and ambiguity functions. Projector configurations. Reverberation and multipath effects. Receiver design.

  5. Passive and Active Designs and Implementations. Design specifications and trade-off examples will be worked, and actual sonar system implementations will be examined.

  6. Advanced Signal Processing Techniques.Advanced techniques for beamforming, detection, estimation, and classification will be explored. Optimal array processing. Data adaptive methods, super resolution spectral techniques, time-frequency representations and active/passive automated classification are among the advanced techniques that will be covered.

This course is not on the current schedule of open enrollment courses. If you are interested in attending this or another course as open enrollment, please contact us at (410) 956-8805 or at and indicate the course name and number of students who wish to participate. ATI typically schedules courses with a lead time of 3-5 months. Group courses can be presented at your facility. For on-site pricing, request an on-site quote. You may also call us at (410) 956-8805 or email us at


James W. Jenkins joined the Johns Hopkins University Applied Physics Laboratory in 1970 and has worked in ASW and sonar systems analysis. He has worked with system studies and at-sea testing with passive and active systems. He is currently a senior physicist investigating improved signal processing systems, APB, own-ship monitoring, and SSBN sonar. He has taught sonar and continuing education courses since 1977 and is the Director of the Applied Technology Institute (ATI).

Dr. Bruce NewhallDr. Bruce Newhall has over 40 years experience in underwater acoustics, sonar, and signal processing. He was chief scientist for several large scale Navy experiments and the supervisor of the Acoustic and Electromagnetics Group at the Johns Hopkins Applied Physics Lab. He has served as Associate Editor for the IEEE Journal of Oceanic Engineering. In recognition of his innovative work, he is a fellow of the Acoustic Society, received the bronze medal from the NDIA and is the 2017 recipient of the Donald W. Tufts award in underwater acoustic signal processing from the IEEE.

G. Scott Peacock is the Assistant Group Supervisor of the Systems Group at the Johns Hopkins University Applied Physics Lab (JHU/APL). Mr. Peacock received both his B.S. in Mathematics and an M.S. in Statistics from the University of Utah. He currently manages several research and development projects that focus on automated passive sonar algorithms for both organic and off-board sensors. Prior to joining JHU/APL Mr. Peacock was lead engineer on several large-scale Navy development tasks including an active sonar adjunct processor for the SQS-53C, a fast-time sonobuoy acoustic processor, and a full scale.

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