University Events

Description: TOPIC: SIGNAL DETECTION AND SPATIAL SPECTRAL ESTIMATION USING COPRIME SENSOR ARRAYS WITH THE MIN PROCESSOR

LOCATION: Lester W. Cory Conference Room, SENG-213A

ABSTRACT:
Sparse array design in array processing allows the possibility of achieving the resolution of a densely populated uniform linear arrays (ULA) using new array geometries with much fewer sensors. The coprime sensor array (CSA) is a newly proposed non-uniform sparse array geometry interleaving two undersampled ULAs with coprime undersampling factors (sharing no common divisor greater than 1). Conventionally beamforming each CSA subarray produces two spatial spectra with grating lobes due to the spatial undersampling. CSA commonly uses a product processor, which multiplies one CSA subarray scanned response with the complex conjugate of the other to resolve the spatial aliasing ambiguities. However, this product processor produces a spatial power spectral density (PSD) estimate with a peak sidelobe higher than the full ULA peak sidelobe. Moreover, the resulting spatial PSD estimate is not necessarily positive semi-definite. This dissertation proposes a new CSA processor, named CSAmin, which chooses the minimum of the two CSA subarray scanned responses at each bearing to resolve the spatial aliasing ambiguities. The min processor reduces the peak sidelobe height and total sidelobe area over a product processor for the same CSA geometry and moreover, preserves the positive semi-definite characteristic of a true PSD. Several applications of the min processor are presented in this talk for improving CSA's capabilities in signal detection, PSD estimation and super resolution direction-of-arrival (DOA) estimation.

NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.

Advisor: Dr. John R. Buck

Committee Members: Dr. David A. Brown and Dr. Paul J. Gendron, Department of Electrical & Computer Engineering; Dr. Kathleen E. Wage, Department of Electrical & Computer Engineering, George Mason University

*For further information, please contact Dr. John R. Buck at 508.999.9237, or via email at jbuck@umassd.edu.