Identification of Sources with Unknown Wavefronts.
Abstract
This paper concerns techniques for processing sonar array data to obtain information about the spatial distribution of acoustic sources. It presents a method for determining the spectral density and the signal wavefronts of several sources using a minimum of prior assumptions. The passive sonar problem is defined and the traditional approach to a solution using matched filters is presented. Maximization of the directivity factor for known signals with static, nonadaptive filters emerges as the prime goal of traditional processing. Care is then taken to properly introduce the cross spectral density matrix which plays a crucial role in adaptive processing. A realization of adaptive noise cancellation through the use of signal-free references is achieved with the development of a Correlo-Filtre. Adaptive noise cancellation leads to degradation when a supposedly known wavefront deviates from an expected shape. Robustness and the need for a processor which does not require prior knowledge of the wavefront is then discussed. Method of identifying completely unknown wavefronts is proposed. Using the eigenvalues of the cross spectral density matrix allows the number of sources to be determined. The wavefront shapes are then shown be scrambled within the eigenvectors by an unknown unitary matrix. Additional information needed to select a specific unitary matrix is introduced by modeling the sources as a coherent sum of conditional plane waves.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 31, 1988
- Accession Number
- ADA194288
Entities
People
- Henri Mermoz
Organizations
- United States Naval Research Laboratory