2006
DOI: 10.1016/j.dsp.2006.05.009
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Matrix pencil method for simultaneously estimating azimuth and elevation angles of arrival along with the frequency of the incoming signals

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Cited by 33 publications
(39 citation statements)
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“…By using this data cube, one pole is found along each plane. After finding these poles, the corresponding elevation, azimuth angles and the wavelength of the signals (B, t/J and A) are obtained for each source [2]. The details of the formulation for the 3-D MP method can be found in [2].…”
Section: Brief Overview Of the Matrix Pencil Methods And Problem Fmentioning
confidence: 99%
See 1 more Smart Citation
“…By using this data cube, one pole is found along each plane. After finding these poles, the corresponding elevation, azimuth angles and the wavelength of the signals (B, t/J and A) are obtained for each source [2]. The details of the formulation for the 3-D MP method can be found in [2].…”
Section: Brief Overview Of the Matrix Pencil Methods And Problem Fmentioning
confidence: 99%
“…The voltages induced in the antenna elements of the three dimensional antenna array are used to estimate the signal parameters simultaneously using Matrix Pencil (MP) method. It has been shown that the method works very well for the isotropic omni-directional sensor elements [2]. The paper studies the performance of the estimator in which the real antenna elements are used.…”
mentioning
confidence: 99%
“…As illustrated in [1], [12], the Matrix Pencil algorithm can get good performance on DoA estimation when the environment exhibits high SNRs. On the other hand, as the SNRs decreases, the performance decreases dramatically.…”
Section: Proposed Wavelet De-noising Matrix Pencil Methods (Wdmpm)mentioning
confidence: 99%
“…The suffix s and n are symbols that demonstrate the signal subspace and noise subspace, respectively. Σ s is a square diagonal matrix involving the eigen- [12], [13] . In the same way, V can be separated into…”
Section: The Traditional Mpm Doa Estimation Techniquementioning
confidence: 99%
“…This implies that the signal eigenvalues are practically greater than the noise floor σ n 2 . The eigenvectors in the columns of U can be partitioned into U s = [u 1 , u 2 , … , u N ] for signal eigenvectors that correspond to the signal subspace and U n = [u N+1 , … , u M ] for noise eigenvectors that represent the noise subspace [8,9]. In the same way, V can be separated into…”
Section: Traditional Matrix Pencil Methodsmentioning
confidence: 99%