On estimating the phase of periodic waveform in additive Gaussian noise, part 2
Abstract
Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.
- Publication:
-
The Telecommunications and Data Acquisition Report
- Pub Date:
- November 1984
- Bibcode:
- 1984tdar.nasa...17R
- Keywords:
-
- Algorithms;
- Random Noise;
- Signal Processing;
- Waveforms;
- Hyperspaces;
- Phase-Space Integral;
- Power Spectra;
- Probability Density Functions;
- Signal To Noise Ratios;
- Communications and Radar