Estimating the K-distribution parameters based on fractional negative moments

Estimation quality of the K-distribution parameters can be improved using a low fractional moments. For noiseless situations and a single pulse processing, we resort in this communication to the fractional positive moments and the fractional negative moments of the received data to derive a new estimation method whose non linear estimates of the shape parameter are achieved using numerical computations. Regardless of these computational requirements, simulation comparison with the existing HOME (Higher Order Moment Estimator), FOME (Fractional Order Moment Estimator) and [zlog(z)] based estimator, show that the new estimator yields asymptotically lower MSE (Mean Square Error) of shape parameter estimates.