| A ROBUSTNESS ANALYSIS OF THE MUSIC AND THE MINIMUM－NORM ALGORITHMS WITH RESPECT TO CORRELMED NOISE |
| |
| 引用本文： | JIA Peizhang(Institute of Systems Sctence,Academia Sinica,Beliing 100080,China). A ROBUSTNESS ANALYSIS OF THE MUSIC AND THE MINIMUM－NORM ALGORITHMS WITH RESPECT TO CORRELMED NOISE[J]. 系统科学与复杂性, 1994, 0(1) |
| |
| 作者姓名： | JIA Peizhang(Institute of Systems Sctence Academia Sinica Beliing 100080 China) |
| |
| 作者单位： | Institute of Systems Sctence，Academia Sinica，Beliing 100080，China |
| |
| 摘 要： | ＡＲＯＢＵＳＴＮＥＳＳＡＮＡＬＹＳＩＳＯＦＴＨＥＭＵＳＩＣＡＮＤＴＨＥＭＩＮＩＭＵＭ－ＮＯＲＭＡＬＧＯＲＩＴＨＭＳＷＩＴＨＲＥＳＰＥＣＴＴＯＣＯＲＲＥＬＭＥＤＮＯＩＳＥ￥ＪＩＡＰｅｉｚｈａｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＳｙｓｔｅｍｓＳｃｔｅｎｃｅ，Ａｃ...
|
A ROBUSTNESS ANALYSIS OF THE MUSIC AND THE MINIMUM-NORM ALGORITHMS WITH RESPECT TO CORRELMED NOISE |
| |
| JIA Peizhang. A ROBUSTNESS ANALYSIS OF THE MUSIC AND THE MINIMUM-NORM ALGORITHMS WITH RESPECT TO CORRELMED NOISE[J]. Journal of Systems Science and Complexity, 1994, 0(1) |
| |
| Authors: | JIA Peizhang |
| |
| Abstract: | A robustness analysis of the MUSIC and the MiniNorm algorithms with respect to spatially correlated noise in array processing is presented in this paper. Let thecovariance matrix of correlated noise be the correlated noise introduces a bias into the direction-of-arrival estimates , producedby the two algorithms. For the else of two closely spaced sources, the influence functions of the two algorithms and the resolving power as a function of e of the two althms are derived. The results show that the above two robust performances of theMiniNorm algorithm are slightly better than those of the MUSIC algorithm, but both algorithms have poor robustness with respect to correlated noise. The analysis assumes thatthe exact covariance matrix of array element outputs is known (the infinite data case). |
| |
| Keywords: | Array processing direction of arrival estimate robustness analysis. |
| 本文献已被 CNKI 等数据库收录！ |
