Adaptive Beamforming and Random Matrix Theory
Abstract
Summary Passive sonar is an important element of the Navy’s strategy for anti-submarine warfare (ASW). The Navy faces a constant challenge in detecting and localizing quiet contacts at tactical ranges in a wide variety of shallow and deep water environments. Adaptive beamforming offers the possibility of improved detection range and accuracy in target bearing estimation, however the performance limits of many adaptive algorithms are not well understood. This is particularly true for large arrays operating in non-stationary environments where it is difficult to obtain sufficient snapshots to estimate the signal statistics. Recent mathematical developments in random matrix theory (RMT) provide new tools for analyzing snapshotdeficient signal processing problems. The objectives of the proposed research are to develop novel adaptive beamformers (ABFs) for passive sonar using RMT and to apply RMT to characterize the performance of existing passive ABFs. We recently developed the unit-circle MVDR beamformer and established promising numerical evidence supporting a beta distribution for the signal-to-interferenceand- noise ratio (SINR) loss for the Dominant Mode Rejection (DMR) ABF. We propose to continue our RMT-based analysis for array processing through six focus areas over the next three years. First, we will extend our unit circle MVDR algorithm with null broadening. Second, we will pursue an analytic proof for the beta distribution of the DMR ABF. Third, we will explore RMT analysis of whitening filters based on sample covariance matrices in general. Fourth, we will investigate a variant of the DMR ABF using median filtering rather than averaging to establish the noise floor. Fifth, we will exploit concepts from universal prediction algorithms to formulate a rank adaptive version of the DMR ABF. Sixth, we will verify as many of these techniques as possible with real data sets. New ABFs have broad potential for transition to Navy systems, and improved performance predictions for adaptive passive sonar systems would provide important guidelines for both tactical and strategic planning in ASW. The proposed three year basic research project is a collaboration between John Buck (University of Massachusetts Dartmouth) and Kathleen Wage (George Mason University).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2016
- Source ID
- N000141512238
Entities
People
- John R. Buck
Organizations
- Office of Naval Research
- United States Navy
- University of Massachusetts