tailieunhanh - Báo cáo hóa học: " Research Article Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities Chengpeng Hao,1 Bin Liu,2 Shefeng Yan,1 and Long Cai1"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: I Research Article Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities Chengpeng Hao,1 Bin Liu,2 Shefeng Yan,1 and Long Cai1 | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 375136 11 pages doi 2010 375136 Research Article Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities Chengpeng Hao 1 Bin Liu 2 Shefeng Yan 1 and Long Cai1 1 Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China 2 Department of Electrical and Computer Engineering Duke University Durham NC 27708 USA Correspondence should be addressed to Chengpeng Hao haochengp@ Received 12 August 2010 Accepted 2 November 2010 Academic Editor M. Greco Copyright 2010 Chengpeng Hao et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We consider the problem of adaptive signal detection in the presence of Gaussian noise with unknown covariance matrix. We propose a parametric radar detector by introducing a design parameter to trade off the target sensitivity with sidelobes energy rejection. The resulting detector merges the statistics of Kelly s GLRT and of the Rao test and so covers Kelly s GLRT and the Rao test as special cases. Both invariance properties and constant false alarm rate CFAR behavior for this detector are studied. At the analysis stage the performance of the new receiver is assessed and compared with several traditional adaptive detectors. The results highlight better rejection capabilities of this proposed detector for mismatched signals. Further we develop two two-stage detectors one of which consists of an adaptive matched filter AMF followed by the aforementioned detector and the other is obtained by cascading a GLRT-based Subspace Detector SD and the proposed adaptive detector. We show that the former two-stage detector outperforms traditional two-stage detectors in terms of selectivity and the latter yields more robustness. 1. .