Multi-dimensional Capon spectral estimation using discrete Zhang neural networks
- 2.2k Downloads
The minimum variance spectral estimator, also known as the Capon spectral estimator, is a high resolution spectral estimator used extensively in practice. In this paper, we derive a novel implementation of a very computationally demanding matched filter-bank based a spectral estimator, namely the multi-dimensional Capon spectral estimator. To avoid the direct computation of the inverse covariance matrix used to estimate the Capon spectrum which can be computationally very expensive, particularly when the dimension of the matrix is large, we propose to use the discrete Zhang neural network for the online covariance matrix inversion. The computational complexity of the proposed algorithm for one-dimensional (1-D), as well as for two-dimensional (2-D) and three-dimensional (3-D) data sequences is lower when a parallel implementation is used.
KeywordsMulti-dimensional spectral estimation Covariance matrix Capon estimator Discrete Zhang neural network 3-D imaging
Unable to display preview. Download preview PDF.
- Benesty, J., Chen, J., & Huang, Y., (2007). Recursive and fast recursive Capon spectral estimators. EURASIP Journal on Advances in Signal Processing. doi: 10.1155/2007/45194.
- Lombardini, F., Cai, F., & Pardini, M. (2009). Parametric differential SAR tomography of decorrelating volume scatterers. In Proceedings of the 6th European Radar conference. doi: 270-273.978-2-87487-014-9.
- Lombardini, F., Pardini, M., & Verrazzani, L. (2008). A robust multibaseline sector interpolator for 3D SAR imaging. In Proceedings of the EUSAR 2008, Friedrichshafen, Germany.Google Scholar
- Marple, S. L., Jr. Adeli, M., & Liu, H. (2010). Super-fast algorithm for minimum variance (Capon) spectral estimation. In Conference on signals, systems and computers (ASILOMAR). doi: 10.1109/ACSSC.2010.5757893.
- Pan, V. Y., Rami, Y., & Wang, X. (2002). Structured matrices and Newton’s iteration: unified approach. In Linear algebra and its applications, (343–344), 233–265Google Scholar
- Raj P C. P., Pinjare S. L. (2009) Design and analog VLSI implementation of neural network architecture for signal processing. European Journal of Scientific Research 27(2): 199–216Google Scholar
- Zhang, Y., Cai, B., Liang, M. & Ma, W. (2008). On the variable step-size of discrete-time Zhang neural network and Newton iteration for constant matrix inversion. In Second international symposium on intelligent information technology application. doi: 10.1109/IITA.2008.128.
- Zhang, Y., Chen, K., Ma, W., & Xiao, L. (2007). MATLAB simulation of gradient-based neural network for online matrix inversion. In D. S., Huang, L., Heute & Loog, M. (Eds.), ICIC 2007, LNCS(LNAI), (Vol. 4682, pp. 98–109). Heidelberg: Springer.Google Scholar
- Zhang, Y., Ma, W., & Yi, C., (2008). The link between Newton iteration for matrix inversion and Zhang neural network (ZNN). In Proceeding of IEEE international conference on industrial technology, Chengdu, China. doi: 10.1109/ICIT.2008.4608578.