DocumentCode :
3482958
Title :
Multichannel parametric detectors for airborne radar applications
Author :
Sohn, Kwang June ; Li, Hongbin ; Himed, Braham ; Markow, Joshua S.
Author_Institution :
Stevens Inst. of Technol., Hoboken
fYear :
2007
fDate :
4-8 June 2007
Firstpage :
178
Lastpage :
182
Abstract :
We consider the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbances. The parametric Rao and GLRT detectors, recently developed by exploiting a multichannel autoregressive (AR) model for the disturbance, have been shown to perform well with limited or even no range training data. The performance of the parametric detectors, however, has been evaluated through the limited computer simulations. The disturbances were generated to follow the exact multichannel AR processes and independently from each other with the same distribution whereas the disturbances in an airborne radar environment do not follow the exact multichannel AR model. In this paper, we evaluate the detection performance of the parametric Rao and GLRT detectors using airborne data obtained from the multi-channel airborne radar measurement (MCARM) database. This data contain typical clutter found in airborne radar systems, and cover a variety of scenarios including dense-target or heterogeneous environment Numerical results show that the parametric Rao and GLRT detectors work well with limited or even no range training data in an airborne radar environment.
Keywords :
airborne radar; autoregressive processes; database management systems; digital simulation; radar clutter; radar signal processing; signal detection; space-time adaptive processing; telecommunication computing; airborne radar measurement database; airborne radar system clutter; computer simulation; multichannel autoregressive model; multichannel parametric signal detector; parametric GLRT detector; parametric Rao detector; space-time adaptive processing; Airborne radar; Clutter; Computer simulation; Covariance matrix; Databases; Detectors; Parameter estimation; Radar detection; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Waveform Diversity and Design Conference, 2007. International
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-1276-1
Electronic_ISBN :
978-1-4244-1276-1
Type :
conf
DOI :
10.1109/WDDC.2007.4339405
Filename :
4339405
Link To Document :
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