Improvement of Resolution and Reduction of Computation in 2D Spectral Estimation Using Decimation,
PRINCETON UNIV NJ DEPT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE
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This paper is concerned with spectral estimation of a finite number of two dimensional siunsoids embedded in white noise. Closed form expressions are derived for estimates using the autoregressive AR prediction error filter approach, as well as using periodogram with Bartlett window, and the maximum likelihood ML method. These expressions are useful in the study of resolving closely spaced sinusoidal signals. Over a narrow frequency band, direct decimation can be applied to improve resolution andor to reduce computation. Simulation results demonstrate that decimation by D1, D2 with a support size N1, N2 yields approximately the same resolution as a support size D1 N1, D2 N2 used with the undecimated signal. The use of decimation also reduces significantly computation.
- Numerical Mathematics