Non-Rayleigh signal statistics in clustered statistically homogeneous rain

As the sample volume of a remote sensing instrument moves through sufficien tly variable conditions, recent work shows that the amplitudes and associat ed intensities can deviate significantly at limes from expectations based o n Rayleigh signal statistics because fluctuations in the number of scattere rs leads to a doubly stochastic measurement process. While non-Rayleigh dev iations yield average biases for both logarithmic and linear detectors, per haps of greater importance is the enhancement of the variance of the bias d istribution for square law detectors. In this work the authors explore the potential existence of non-Rayleigh effects even in the statistically homog eneous rain when fluctuations in the number of scatterers should be much le ss than for the inhomogeneous conditions used in earlier studies. Moreover, in contrast to previous work, recent advances now permit the simu lation of correlated rainfall structures having the statistical characteris tics of natural rain such as clustering intensity (N) and coherence length (chi(i)) consistent with observations. The primary objective of this work, then, is to clarify how El, chi(i), and the geometric parameters characteri stic of remote sensing observations such as the distance over which an esti mate is made (L), the beamwidth (B), and the spatial displacement between s uccessive independent samples (Delta) affect non-Rayleigh signals statistic s in statistically homogeneous rain. This work shows that non-Rayleigh effects can appear whenever Delta less th an or equal to chi(i) less than or equal to L, Moreover, the magnitudes of the non-Rayleigh deviations increase as N and Delta/B increase. Although no n-Rayleigh effects can be detected by monitoring of the signals, keeping bo th Delta/B and L as small as possible while increasing sample independence using chirp or signal whitening techniques, for example, should help to min imize non-Rayleigh effects for radars even in statistically inhomogeneous r ain.