Analytical Expression for the Posterior Distribution of Signals in Colored Gaussian Noise
Paper in proceedings, 2002
The paper describes a Bayesian approach to estimate
the amplitude, s, of a given signal embedded in complex
zero mean Gaussian noise with unknown covariance.
By employing Jefieys priors to unknown parameters,
the posterior distribution is derived analytically. While
the resulting estimates, B, are merely reproductions of
classical estimates, the Bayesian approach offers an enhanced
ability to predict the quality of estimates conditioned
on the measured data. This ability is further
highlighted by simulations using finite training sets.