A Simple Digital Signal Processing Method to Simulate Linear and Quadratic Responses from a Radar's Logarithmic Receiver

Deon E. Terblanche Bethlehem Precipitation Research Project, Weather Bureau, Bethlehem, South Africa

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Abstract

Due to the large range of power returns from meteorological targets, a receiver with a logarithmic transference function is commonly used in weather radars. The large variance in returned power from a specific meteorological sample volume necessitates the averaging of several samples, which introduces a bias. Commonly used averaging methods with an average bias correction can still introduce unacceptable errors in measured reflectivity fields, especially in intense convective storms. This has a detrimental effect on the ability of a radar to determine rainfall under these conditions. A simple digital signal processing method is described and tested whereby averages that simulate different receiver responses are obtained from a logarithmic receiver. This method is compatible with existing local hardware and computational time constraints. In the case of the quadratic simulation, unbiased averages are obtained, increasing the accuracy of meteorological radar observations.

Abstract

Due to the large range of power returns from meteorological targets, a receiver with a logarithmic transference function is commonly used in weather radars. The large variance in returned power from a specific meteorological sample volume necessitates the averaging of several samples, which introduces a bias. Commonly used averaging methods with an average bias correction can still introduce unacceptable errors in measured reflectivity fields, especially in intense convective storms. This has a detrimental effect on the ability of a radar to determine rainfall under these conditions. A simple digital signal processing method is described and tested whereby averages that simulate different receiver responses are obtained from a logarithmic receiver. This method is compatible with existing local hardware and computational time constraints. In the case of the quadratic simulation, unbiased averages are obtained, increasing the accuracy of meteorological radar observations.

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