Rajshekhar Gannavarpu, Rastogi Pramod
Applied Computing and Mechanics Laboratory, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
Appl Opt. 2012 Aug 20;51(24):5869-75. doi: 10.1364/AO.51.005869.
The paper introduces a multiple signal classification technique based method for fringe analysis. In the proposed method, the phase of a fringe pattern is locally approximated as a polynomial. The polynomial phase signal is then transformed to obtain signals comprising of only even- or odd-order polynomial coefficients. Subsequently, covariance matrix formulation is applied, and the two sets of coefficients are jointly estimated from the noise subspace of the covariance matrix using the multiple signal classification technique. The method allows simultaneous estimation of multiple coefficients and provides phase without the requirement of complex unwrapping algorithms. The effectiveness of the proposed method is validated through numerical simulation.
本文介绍了一种基于多重信号分类技术的条纹分析方法。在所提出的方法中，条纹图案的相位在局部被近似为一个多项式。然后对多项式相位信号进行变换，以获得仅由偶数阶或奇数阶多项式系数组成的信号。随后，应用协方差矩阵公式，并使用多重信号分类技术从协方差矩阵的噪声子空间中联合估计这两组系数。该方法允许同时估计多个系数，并且无需复杂的解包裹算法即可提供相位。通过数值模拟验证了所提方法的有效性。
