Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4973982 | Digital Signal Processing | 2017 | 11 Pages |
Abstract
Multi-dimensional harmonic retrieval (HR) in white noise is required in numerous applications such as channel estimation in wireless communications and imaging in multiple-input multiple-output radar. In this paper, we propose two R-dimensional (R-D) extensions of the subspace-based MUSIC model order selection scheme, for Râ¥2, to detect the number of multi-dimensional cisoids. The key idea in the algorithm development is to utilize the principle angles between multilinear signal subspaces via the truncated higher-order singular value decomposition. The first method is designed for multiple-snapshot scenarios. It considerably outperforms existing algorithms in terms of both detection accuracy and identifiability particularly when a large number of snapshots are available. However, its computational cost is relatively quite high. The second method is computationally much simpler and performs almost as well as the first one when the number of snapshots is small. Simulation results are conducted to demonstrate the performance of the proposed estimators.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Kefei Liu, Hui Cao, Hing Cheung So, Andreas Jakobsson,