Physical Sciences Inc. (PSI) has been awarded a contract from the U.S. Navy to develop an advanced algorithm suite for data translation across the various sensing modalities integrated with unmanned underwater vehicles. The Deep Diffusion Sensor Translation tool will produce synthetic sensor measurements to aid in the development of automated target recognition algorithms. The resulting imagery will be accurate with respect to acoustical and optical reflectivity at Peak Signal-to-noise Ratios of 30dB and 25dB respectively.
PSI, in collaboration with a university partner, is developing an advanced algorithm suite for data translation across sensing modalities to support the development of automated target recognition and classification algorithms for Unmanned Underwater Vehicles. The Deep Diffusion Sensor Translation (DDST) leverages recent advancements in generative artificial intelligence, and latent diffusion models in particular, to enable highly realistic data synthesis to supplement these underwater ATR datasets. The DDST tool will be capable of translating between sidescan sonar, forward looking sonar, synthetic aperture sonar, imaging magnetometry, and visible sensing modalities. The DDST incorporates advancements in underwater image enhancement and three-dimensional scene reconstruction to normalize variability across instruments, environments, and sensing conditions. The DDST will also leverage PSI’s computer vision and image fusion expertise developed under multiple DoD programs, through customization of an in-house super-resolution technique to the task of enhancing DDST inputs and outputs. The DDST technology will produce synthetic sensor outputs with quantifiable accuracy, achieving acoustical and optical reflectivity accuracies with PSNRs of 30dB and 25dB respectively.
For more information contact:
Dr. Bogdan Cosofret
Vice President, Detection Systems
Physical Sciences Inc.
Office: (978) 689-0003
Acknowledgement of Sponsorship: This work is supported under a contract with the Naval Sea Systems Command. This support does not constitute an express or implied endorsement on the part of the Government.