Accession Number:

ADA261565

Title:

Array Signal Processing Under Model Errors With Application to Speech Separation

Descriptive Note:

Annual progress rept. 1 Nov 1991-31 Oct 1992

Corporate Author:

NOTRE DAME UNIV IN DEPT OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

1992-10-31

Pagination or Media Count:

151.0

Abstract:

In recent years there have been increasing interest in eigenstructure based array signal processing techniques especially in the areas of radar and sonar processing and in signal separation applications as found in communications or speech acquisitionenhancement. However, model errors are not accounted for in these methods. Unfortunately, the problem of model error is a ubiquitous part of real systems they arise from such phenomena as non-ideal sensor characteristics eg., sensor calibration errors in phase and gain, etc., unknown source characteristics and locations, etc. This report is broadly divided into two parts. The first part examines the effects of model errors on the performance of existing eigenstructure based methods in array signal processing. A statistical analysis of the ESPRIT Estimation of Signal Param via Invariance Techniques algorithm under random model errors is performed. The analysis provides interesting insight into the sensitivity of ESPRIT to model errors in particular, for uniform linear arrays of sensors, it is found that the mean square error of DOA direction of arrival estimates found using ESPRIT is almost totally dependent on errors in sensor phases and not that of sensor gains.

Subject Categories:

  • Cybernetics
  • Acoustic Detection and Detectors
  • Miscellaneous Detection and Detectors
  • Active and Passive Radar Detection and Equipment
  • Radio Communications
  • Voice Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE