Combining Aiding Sensors with Multiple IMUs for Navigation Optimization (CAMINO)

The Navy is procuring many small unmanned underwater vehicles (UUVs) to augment battlespace awareness in complex littoral environments. Effective deployment of these assets requires highly accurate navigational capabilities, but current high accuracy underwater navigation techniques have size, weight, power consumption, and cost (SWAP-C) requirements that exceed platform limits. Therefore, widespread deployment of small UUV assets depends on the development of navigation solutions that provide accurate navigation at low SWAP-C. To enable high accuracy navigation on small UUVs, we propose a system for Combining Aiding Sensors with Multiple IMUs for Navigation Optimization (CAMINO). CAMINO uses a novel hierarchical particle filter to combine noisy measurements from multiple IMUs and direct observations of platform state from secondary sensors, including depth sensors, compasses, and inclinometers. This approach allows CAMINO to model complex uncertainties from a variety of sensors while leveraging the strengths of each sensor to maintain an accurate estimate of UUV geolocation and orientation. During Phase I, we will identify promising low-SWAP-C sensors through a trade study and leverage our unique access to UUV testing resources under existing ONR programs to build a functional CAMINO prototype with integrated hardware and software components to demonstrate the feasibility of the CAMINO system through in-water testing.