Knowledge-aided Adaptive Subspace Detection In Partially Homogeneous Environments

摘要：

In this paper, we consider the adaptive subspace detector for partially homogeneous environments. In this environment, the clutter covariance matrix (CCM) of secondary data is equal to the CCM of the cell under test (CUT), except for a real constant factor. We also suppose that we have some prior knowledge of the CCM, which is controlled by the parameters of the statistics distribution of the CCM. Based on the Bayesian framework, a knowledge-aided adaptive subspace detector (KA-ASD) is given, and can be used to detect the subspace signal in partially homogeneous environments. The computer simulation is used to validate that KA-ASD is outperform the conventional subspace detector, and especially within a small number of training samples and coherent pulses.

关键词： partially homogeneous environments knowledge-aided adaptive subspace detection clutter covariance matrix.

作者: Kun Zou Xiubin Zhao Wei Li

作者单位: Department of Navigation Engieering Airforce Engieering University Xi’an, Chian, 710077

会议类型: 国际会议

会议名称: 2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

会议地点: 成都

会议语种:英文

页码: 1708-1711

在线出版日期: 2011-10-24（万方平台首次上网日期，不代表论文的发表时间）