Sonoscatter: Long-Range, High-Resolution Underwater Object Detection & Imaging via Net-Zero-Power Backscatter Networks
Abstract
Approved for Public ReleaseThis project aims to explore, design, build, and test sonoscatter, a first-of-its-kind technology for underwater object detection, localization, and imaging. This technology aims to dramatically extend SONAR systems (including sonobuoys) to longer detection ranges, larger coverage areas, and higher resolution while simultaneously reducing the cost, power, and deployment requirements for existing underwater object detection, localization, and imaging systems. The technology builds on underwater Piezo-Acoustic Backscatter (PAB), a new underwater communication approach (developed by the PI#s lab at MIT with an ONR ECG) which is1 million times lower power than existing low-power underwater acoustic modems [5,7,8,15#17,22,34]. The proposed project aims to leverage the same communication technology but for ultra-low-power object detection, localization, and (acoustic) imaging. To realize the leap from communication to imaging, we will build on the PI#s pioneeringresearch in joint communication and imaging for RF networks [1, 4, 23, 26] and bring these advances to underwater backscatter networks. Throughout the project, we will collaborate closely with the WHOI co-PI, who has done seminal work in developing underwater acoustic modems and systems and transitioning them to the Navy.The proposed research will explore both passive and active sonoscatter # including their overall architecture, subcomponents (particularly backscatter localization), and extended MIMO designs. We will study these novel architectures theoretically and develop proof-of-concept prototypes. The success of this project can result in a new generation of SONAR systems (including passive and activesonobuoys) with first-of-their-kind capabilities in detection range, coverage area, resolution, and lifespan, providing unprecedented naval capabilities in submarine warfare, maritime situational awareness, and large-scale search and retrieval operations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2023
- Source ID
- N000142312838
Entities
People
- Fadel Adib
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy