Variational Bayesian PARAFAC Decomposition for Multidimensional Harmonic Retrieval
High resolution parameters estimation for Multidimensional Harmonic Retrieval problem is required in a variety of applications including radar, sonar, and communication, etc.. Recent approaches based on deterministic tensor decomposition show promising results. However, these methods raise difficulties to estimate the unknown number of targets. In this paper, we address this problem through reformatting it into a Bayesian framework. Since exact Bayesian estimation of the unknown parameters is intractable, an approximation scheme based on variational principle is developed. The significant features of this approach are that the unknown number of targets are efficiently estimated as a part of Bayesian inference process and moreover, it provides high estimation performance. Experimental results demonstrate the effectiveness of the proposed method.
Weiwei Guo Wenxian Yu
School of Electronic Science Enginering National University of Defence Technology, China School of Electronic, Information and Electrical Engineering Shanghai Jiaotong University
国际会议
2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)
成都
英文
1864-1867
2011-10-24（万方平台首次上网日期，不代表论文的发表时间）