Performance of two-dimensional parametric STAP: KASSPER airborne radar data analysis

被引：0
|
作者：
Abramovich, Yuri [1 ]
Rangaswamy, Muralidhar [2 ]
Johnson, Ben [3 ,4 ]
Corbell, Phillip [2 ]
Spencer, Nicholas [5 ]
机构：
[1] DSTO, ISRD, POB 1500, Edinburgh, SA 5111, Australia
[2] SNHE AFRL, Hanscom AFB, MA 01731 USA
[3] RLM Management Pty Ltd, Edinburgh Raaf Base, SA 5111, Australia
[4] Univ South Australia, Edinburgh Raaf Base, SA 5111, Australia
[5] Adelaide Res & Innovat Pty Ltd, Edinburgh, SA 5111, Australia
来源：
2008 PROCEEDINGS INTERNATIONAL RADAR SYMPOSIUM | 2008年
关键词：
D O I：
暂无
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
We investigate anew class of 2-D parametric models for space-time adaptive processing (STAP) of ground clutter in airborne radar using KASSPER Dataset 1. The signal-to-interference-plus-noise (SINR) degradation with respect to the optimal receiver is analyzed for various parametric models, regularizations and training sample volumes. We show that a very small training sample volume (5-15 training range bins), with a suitable parametric model and estimation technique, can give acceptable STAP performance for the KASSPER scenario.
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页码：27 / +
页数：2
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