Prediction of inverse covariance matrix (PICM) sequences for STAP

Author

Lim, Chin Heng ; Mulgrew, Bernard

Author_Institution

Sch. of Eng. & Electron., Edinburgh Univ., UK

Volume

13

Issue

4

fYear

2006

fDate

4/1/2006 12:00:00 AM

Firstpage

236

Lastpage

239

Abstract

In this letter, we study issues associated with applying least-squares estimation to predict the inverse covariance matrix in bistatic airborne radar systems. For the bistatic ground moving target indication radar, the clutter Doppler frequency depends on the range for all array geometries. This range dependency leads to problems in clutter suppression through space-time adaptive processing (STAP) techniques. This paper proposes a new method of obtaining an estimate of the inverse covariance matrix using linear prediction techniques. Simulation results show a significant improvement in processor performance as compared to conventional STAP methods.

Keywords

Doppler radar; airborne radar; covariance matrices; interference suppression; least squares approximations; radar clutter; radar signal processing; space-time adaptive processing; STAP; array geometry; bistatic airborne radar system; clutter Doppler frequency; clutter suppression; ground moving target indication radar; inverse covariance matrix; least-squares estimation; linear prediction technique; space-time adaptive processing technique; Airborne radar; Covariance matrix; Doppler radar; Frequency; Geometry; Navigation; Radar clutter; Radar detection; Spaceborne radar; Statistical analysis; Bistatic radar; inverse covariance matrix; linear prediction; space–time adaptive processing (STAP);

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2005.863654

Filename

1605247