机载雷达时变自回归自适应滤波

2007 IEEE Radar Conference Pub Date : 2007-04-17 DOI:10.1109/RADAR.2007.374296

Y. Abramovich, M. Rangaswamy, B.A. Johnson, P. Corbell, N. Spencer

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引用次数: 6

摘要

基于有限算子值矩阵的Dym-Gohberg带扩展技术，引入了m阶多元时变自回归模型(TVAR(m))。对于特定的侧视机载雷达场景(基于kasper - ii数据集)和新颖的最优时变发射天线方向图控制，我们证明了与相对较小的TVAR阶m (m ~ 4 ~ 8)相关的模型失配损失在方位角-多普勒感兴趣范围内相当低(1.5 ~ 3db)，并且允许显著降低训练样本支持度。

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Time-varying autoregressive adaptive filtering for airborne radar applications

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.

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2007 IEEE Radar Conference

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