Naval Undersea Warfare Center - Newport Division

Laboratory Coordinator:

Jacob O’Donnell
Chief Technology Office, Code 00T  
Naval Undersea Warfare Center Division, Newport 

Naval Undersea Warfare Center - Newport Division

Only U.S. citizens will be considered for positions at this lab. 

 Dual citizens are NOT eligible


The Naval Undersea Warfare Center Division, Newport (NUWCDIVNPT) is the Navy's full-spectrum research, development, test and evaluation, engineering and fleet support center for submarine warfare systems and many other systems associated with the undersea battlespace.  NUWC Division Newport is responsible, cradle to grave, for all aspects of systems under its charter, and is engaged in efforts ranging from participation in fundamental research to the support of evolving operational capabilities in the U.S. Navy fleet.

With approximately 2500 scientists and engineers, NUWCDIVNPT provides the technical foundation that enables the conceptualization, research, development, fielding, modernization, and maintenance of systems that ensure our Navy's undersea superiority.   NUWCDIVNPT is at the forefront of developing and maintaining the best scientific and technical facilities for underwater research, supporting many important Navy programs and helping to minimize risk and cost of operations.  Working closely with the Fleet, our scientists and engineers meet current and future operational requirements and solve technical problems. 

NUWCDIVNPT specific research and technology areas include:

  • Structural Mechanics
  • Structural Acoustics
  • Undersea Shock Pulse and Structural Response Modeling
  • Chemistry, Marine Materials and Material Behavior
  • Lasers and Optics
  • Signal and Information Processing including Tracking, Classification, and Image Processing
  • Array Signal Processing
  • Artificial Intelligence, Data Sciences and Machine Learning
  • Autonomy and Behavioral Decision Making
  • Acoustics and Acoustic Metrology
  • Ocean Acoustics and Modeling
  • Transduction and Advanced Sensor/Array Designs
  • Undersea Vehicle Technologies including Propulsion, Control, Autonomy, Battery Technology and Navigation
  • Flow Field/Noise Characterization
  • Communications and Electromagnetics
  • Hydrodynamics and Fluid-Structure Interactions
  • Cyber Technology and Security
  • Biological Inspired Technologies
  • Bioacoustics
  • Quantum Computing

Below are two specific examples of research visiting summer faculty performed recently at NUWCDIVNPT:

Optimal and Suboptimal Subspace Estimation for 1D and 2D Uniform Sensor Arrays

Subspace estimation is an implicit or explicit part of signal processing tasks such as adaptive beamforming or direction-of-arrival estimation.  A theoretical bound on the best achievable accuracy for subspace estimation and a new, closed-form, optimal subspace estimation (OSE) algorithm that achieves the bound has been derived.  Signal processing tasks that use the OSE subspace inherit the benefits of its best achievable accuracy.  However, the OSE calculations are prohibitive for arrays with a large number of sensors and the OSE subspace estimate is sensitive to perturbations such as array calibration errors.  A newly proposed estimation method based on subspace averaging (SSA), while suboptimal with respect to accuracy, can approach that of OSE with less computation. 

Sparse Array Processing Applications and Performance

Sparse arrays provide the capability to increase the signal to noise ratio of a weak signal without an exhaustive requirement of a fully-populated array surface. In many cases sparse arrays perform in situations that would be otherwise cost prohibitive. In other cases, sparse arrays provide potential opportunities for fully-populated arrays that have degraded performance due to random element failure over their lifecycle. Element failure raises sidelobe levels and introduces undesired artifacts in the array response. Alternative sparse array processing techniques such as min processing and product processing are designed to augment multiple sparse arrays in a manner that diminishes undesired grating lobes while preserving the desired mainlobe beampattern. However, careful consideration is required in subarray processing in order to mitigate aliasing artifacts present in each of the subarray results due to their respective undersampling of the spatial field. The optimization of a sparse array to given design constraints or an existing degraded array is proposed to improve array performance at significant cost savings.