摘要
A novel approach of unitarily interpolated array MVDR （UIA-MVDR） is proposed, aiming at avoiding the signal cancellation caused by broadband signal-correlated interferences. UIA-MVDR belongs to the classic approaches of spectral averaging. However, it is distinguished from the conventional interpolated array MVDR （IA-MVDR） by two points： 1） It imposes a unitary constraint on the transform matrices. 2） It only optimizes the worst-case performance of array manifold approximation. As a result, the restriction on the order of Bessel function expansion is released, so that very accurate approximation can be achieved even in the case of small or middle arrays. Compared with many related approaches, UIA-MVDR destroys the correlation more completely and then achieves better performance. Its excellent performance in both correlated and uncorrelated broadband interferences suppression is confirmed via a n umber of numerical examples.
A novel approach of unitarily interpolated array MVDR （UIA-MVDR） is proposed, aiming at avoiding the signal cancellation caused by broadband signal-correlated interferences. UIA-MVDR belongs to the classic approaches of spectral averaging. However, it is distinguished from the conventional interpolated array MVDR （IA-MVDR） by two points： 1） It imposes a unitary constraint on the transform matrices. 2） It only optimizes the worst-case performance of array manifold approximation. As a result, the restriction on the order of Bessel function expansion is released, so that very accurate approximation can be achieved even in the case of small or middle arrays. Compared with many related approaches, UIA-MVDR destroys the correlation more completely and then achieves better performance. Its excellent performance in both correlated and uncorrelated broadband interferences suppression is confirmed via a n umber of numerical examples.
基金
This work was supported by the Science and Technology Foundation of Sichuan Province under Grand No. 04GG21-020-02.
作者简介
Jing-Ran Lin was born in Sichuan Province, China, in 1978. He received the B.S. degree in computer communication and the M.S. degree in signal processing from University of Electronic Science and Technology of China （UESTC）, Chengdu, China, in 2001 and 2004, respectively. Currently, he is pursuing the Ph.D. degree in signal processing at UESTC. His research interests include statistical signal processing, array signal processing, adaptive beamforming, parameter estimation, and real-time signal processing.（e-mail： Jingranlin@ 163.com）.Qing-Cong Peng was born in Sichuan Province, China, in 1945 He received the B.S. degree from Tsinghua University, Beijing. China, in 1968, and the M.S. degree from UESTC in 1983. From 1986 to 1988 he was a visiting scholar with University of Missouri-St. Louis and University of Minnesota, USA. Now he is a professor of signal processing with UESTC. His current research interests include signal processing in communication systems, real-time signal processing, signal processing in automatic test system, and DSP technology.Huai-Zong Shao was born in Sichuan Province, China, in 1969. He received the Ph.D. degree in signal processing from UESTC in 2003. Now he is a vice professor of signal processing with UESTC. His research interests include digital processing algorithms in communication systems and modcling for wireless communication.Tai-Liang Ju was born in Sichuan Province, China, in 1974. He received the Ph.D. degree in signal processing from UESTC in 2006 His research interests include statistical signal processing, array signal .processing.
