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Bistatic/Multistatic Scattering for Autonomous Acoustic Target Characterization

Funding Agencies




Research Papers

  1. E. M. Fischell and H. Schmidt. “Supervised machine learning for estimation of target aspect angle from bistatic acoustic scattering.” IEEE JOE (2017). Doi: 10.1109/JOE.2017.2650759.

  2. E. M. Fischell and H. Schmidt. “Environmental effects on seabed object bistatic scattering classification.” J. Acoust. Soc. Am. 141, 28-37 (2017).

  3. E. M. Fischell and H. Schmidt. “AUV behaviors for collection of bistatic and multistatic acoustic scattering data from seabed targets.” 2016 IEEE International Conference on Robotics and Automation (ICRA), pp 2645-2650 (2016).

  4. E. M. Fischell and H. Schmidt, “Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.” J. Acoust. Soc. Am. 138, 3773-3784 (2015).

  5. E. Fischell, T. Schneider and H. Schmidt, “Design, Implementation and Characterization of Precision Timing for Bistatic Acoustic Data Acquisition.” IEEE JOE, ISSN: 0364-9059 (2015).