Robust sequential detectors employing an order statistic prefilter

Author

Lee, Y.-H. ; Kim, S.-J.

Author_Institution

Dept. of Electr. Eng., Seoul Nat. Univ., South Korea

Volume

145

Issue

2

fYear

1998

fDate

4/1/1998 12:00:00 AM

Firstpage

82

Lastpage

87

Abstract

The authors propose robust detection schemes for detecting signals corrupted by additive non-Gaussian noise by employing an order statistic filter (OSF) as a preprocessor. The OSF can effectively suppress non-Gaussian noise components, but its output characteristics are not easy for mathematical manipulation due to its nonlinear operation. To alleviate the difficulty in the analytical design of the detector, the variance of the OSF is approximated by a piecewise linear model. The sequential detectors are designed using the sequential probability ratio test (SPRT) and truncated SPRT (TSPRT) schemes. The performance of the proposed detectors is compared to that of other robust detectors in terms of the sample size required for given false alarm and miss detection probabilities. Finally, analytical results are verified by computer simulation

Keywords

filtering theory; median filters; noise; piecewise-linear techniques; probability; signal detection; signal sampling; additive nonGaussian noise; computer simulation; false alarm probability; impulse noise suppression; median filter; miss detection probability; nonGaussian noise suppression; nonlinear operation; order statistic prefilter; output characteristics; performance; piecewise linear model; preprocessor; robust sequential detectors; sample size; sequential probability ratio test; truncated SPRT; variance;

fLanguage

English

Journal_Title

Vision, Image and Signal Processing, IEE Proceedings -

Publisher

iet

ISSN

1350-245X

Type

jour

DOI

10.1049/ip-vis:19981706

Filename

682166