Computer simulation of weather radar signals

Multilag Correlation Estimators for Polarimetric Radar Measurements in the Presence of Noise

“…In the simulation, H and V channel signals are generated by the spectrum method (Zrnić 1975). Then, the copolar correlation coefficient and power differences are generated for the polarimetric radar parameters (Galati and Pavan 1995). The conventional estimator has the same standard deviation as the one-lag estimator because it is calculated here assuming that the noise power is accurately measured.…”

Bootstrap Dual-Polarimetric Spectral Density Estimator

“…Let V H (m) and V V (m) be the I/Q time-series signals of the H and V channels, respectively. As shown in Torres and Zrnić (2003), and by following the procedure in Galati and Pavan (1995), these can be obtained as: …”

“…The N i independent realizations are performed to assess the statistical characteristics of the DPSD. The weather-like I/Q time-series signals are simulated using the procedure described in Zrnić (1975), extended to dual-polarized signals with the procedure described by Galati and Pavan (1995), as presented in Torres and Zrnić (2003). This procedure is the same for all the methods evaluated hereafter.…”

Whitening of Signals in Range to Improve Estimates of Polarimetric Variables

“…Second, the well-known procedure for generating single-polarization time series by Zrnić (1975) is used to shape the autocorrelation along sample time. Finally, the procedure by Galati and Pavan (1995) for generating a pair of correlated time series is used to impose the cross-correlation between horizontal and vertical channel time series. Note that for bivariate Gaussian processes, the auto-and cross-correlation functions (or their equivalent power spectral densities) provide a complete description of the underlying processes.…”