Adaptive signal processing in non-Gaussian noise backgrounds

Author

Rangaswamy, Muralidhar ; Michels, James H.

Author_Institution

ARCON Corp., Waltham, MA, USA

fYear

1998

fDate

14-16 Sep 1998

Firstpage

53

Lastpage

56

Abstract

This paper discusses the problem of adaptive radar target detection in non-Gaussian noise backgrounds which can be modeled as a spherically invariant random process (SIRP). The estimated covariance matrix is used in an adaptive processing method for signal detection. It is shown that the resulting processor is equivalent to a generalized estimator correlator. Performance analysis is presented in terms of probability of detection versus signal-to-noise-ratio (SNR) for the case of a K-distributed SIRP. A performance comparison of our technique with that of the adaptive matched filter (AMF) of Robey et al (1992) is presented. The method developed in this paper affords considerable performance improvement in non-Gaussian noise backgrounds

Keywords

adaptive signal processing; array signal processing; correlation methods; covariance matrices; noise; probability; radar detection; radar signal processing; random processes; K-distributed SIRP; SIRP; SNR; adaptive processing method; adaptive radar target detection; adaptive signal processing; antenna array elements; detection probability; estimated covariance matrix; generalized estimator correlator; non-Gaussian noise backgrounds; signal detection; signal-to-noise-ratio; spherically invariant random process; Adaptive signal processing; Correlators; Covariance matrix; Matched filters; Object detection; Performance analysis; Radar; Random processes; Signal detection; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on

Conference_Location

Portland, OR

Print_ISBN

0-7803-5010-3

Type

conf

DOI

10.1109/SSAP.1998.739332

Filename

739332