MAP Estimation of the Ricean $K$ Factor

An estimator for the Ricean
$K$
factor is designed by approximating the maximum a posterior (MAP) probability. The performance of the approximate MAP estimator is examined. Numerical results show that the approximate MAP estimator outperforms the approximate maximum likelihood estimator. It also outperforms the best moment-based estimator at small sample sizes.