Skip to main content
eScholarship
Open Access Publications from the University of California

Biomimetic Electrostatics for Submerged Oceanic Sensing, Communication, and Coordination

  • Author(s): Friedman, Jonathan Katzenstein
  • Advisor(s): Srivastava, Mani B
  • et al.
Abstract

Navigation, localization, and targeting while completely submerged in the ocean are all extremely difficult due to the lack of a proficient sensor. The highly conductive nature of salt-water results in severe radio-wave attenuation precluding the use of RADAR. Naturally occurring noise sources, high energy costs, long-wavelengths, and surface turbidity restrict the use of SONAR imaging to low resolutions, depths, and far fields. The ocean's dark, turbulent, and silty disposition impedes optical imaging.

Nature knows another better way. Apteronotus Albifrons is a nocturnal oceanic fish that cannot rely upon optical notions of vision to navigate, hunt, or avoid predators. Instead, it relies upon an electroreceptive capability achieved through a dense grid of electric field (Voltage) sensors arrayed along both sides of the body and concentrated around the head. It emits an electric field into the water and senses the self-induced forces down its sides. Objects in the vicinity that differ in conductivity from the background ocean environment disturb the field, redistribute the current, and hence the spatial distribution of voltages measured by the fish.

This dissertation chronicles the effort to produce an engineered sensor which mirrors the biological phenomenon of electroreception and demonstrate its ability to "visualize" targets with different conductivities from the background ocean environment at very high resolution by detecting perturbations in a quasi-static electric field (electrostatics). This culminates in the first Biomimetic Electrostatic Images (BEI) and demonstrates the potential of the technology to provide significant advances in underwater scientific enterprises, military applications, as well as in medicine.

Main Content
Current View