Time-varying autoregressive adaptive filtering for airborne radar applications

Author

Abramovich, Yuri I. ; Rangaswamy, Muralidhar ; Johnson, Ben A. ; Corbell, P. ; Spencer, Nicholas

Author_Institution

DSTO, Rockingham

fYear

2007

fDate

17-20 April 2007

Firstpage

653

Lastpage

657

Abstract

Multivariate time-varying autoregressive models of order m (TVAR(m)) are introduced based on the Dym-Gohberg band extension technique for finite operator-valued matrices. For particular side-looking airborne radar scenarios (based on the KASSPER-II data set) and novel optimal time-varying transmit antenna pattern control, we demonstrate that model mismatch losses associated with relatively small TVAR order m (m ~ 4 to 8), are quite low (1.5 to 3 dB) inside the azimuth-Doppler range of interest, and allow for significant reduction in training sample support.

Keywords

airborne radar; antenna radiation patterns; autoregressive processes; covariance matrices; filtering theory; radar antennas; radar clutter; radar signal processing; space-time adaptive processing; time-varying filters; Dym-Gohberg band extension technique; airborne radar space-time adaptive processing; antenna pattern control; azimuth-Doppler range; finite operator-valued matrices; multivariate time-varying autoregressive adaptive filtering; radar clutter; Adaptive arrays; Adaptive filters; Airborne radar; Australia; Clutter; Finite impulse response filter; Propagation losses; Radar antennas; Radar countermeasures; Transmitting antennas;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference, 2007 IEEE

Conference_Location

Boston, MA

ISSN

1097-5659

Print_ISBN

1-4244-0284-0

Electronic_ISBN

1097-5659

Type

conf

DOI

10.1109/RADAR.2007.374296

Filename

4250390