Improved adaptive detection performance via subspace processing

Author

Burgess, Keith A. ; Van Veen, Barry D.

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

Volume

5

fYear

1992

fDate

23-26 Mar 1992

Firstpage

353

Abstract

The performance of subspace adaptive detection is examined for the generalized likelihood ratio detector of E.J. Kelly (1986) and Kelly and K.M. Forsythe (1989). The probability of false alarm (PFA) is independent of the subspace transformation, and depends only upon subspace dimension. The probability of detection depends upon the subspace transformation through a non-adaptive signal-to-noise ratio (SNR) parameter. Subspace processing results in an SNR loss that tends to decrease performance and a gain in statistical stability that tends to increase performance. It is shown that the statistical stability effect dominates the SNR loss for short data records and subspace detectors. A method for designing the subspace transformation to minimize the SNR loss is proposed and illustrated via simulations

Keywords

array signal processing; probability; signal detection; SNR; detection probability; false alarm probability; generalized likelihood ratio detector; sensor output processing; short data records; signal-to-noise ratio; simulations; statistical stability; subspace adaptive detection; subspace dimension; subspace processing; subspace transformation; Covariance matrix; Design methodology; Detectors; Noise reduction; Performance loss; Sensor phenomena and characterization; Signal to noise ratio; Stability; Testing; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226610

Filename

226610