Calibration Plans for the SMAP Radar

This presentation will describe the calibration and validation plans for the Soil Moisture Active Passive (SMAP) radar. The SMAP radar will supply high resolution backscatter measurements using synthetic aperture (SAR) processing that will aid higher resolution soil moisture retrievals in combination with coincident passive radiometry measurements. Science requirements lead to a backscatter accuracy requirement of 1-dB (one-sigma) at a resolution of 3 km. The errors in backscatter come from speckle noise which can be averaged down in time and/or space, and from calibration errors. Calibration errors are expected due to uncertainties in measuring and modeling of internal performance parameters and external effects. Internal performance parameters include the antenna gain pattern, pointing knowledge, receiver gain, and transmit power. Variations in these are expected due to temperature variation and component aging. External effects include Faraday rotation, and radio frequency interference (RFI). Short term variations in instrument parameters will be tracked by internal calibration measurements that are expected to be stable on a time scale up to one month. Long term variations and biases will be removed using measurements of stable reference targets such as parts of the Amazon rain forest, the oceans and possibly the ice sheets. Faraday rotation effects will be modeled using GPS based total electron content measurements and a forward model of the SMAP radar. These data will be compared with Faraday rotation estimates obtained directly from the SMAP radiometer using the third stokes parameter. RFI will be detected with a threshold technique applied right before range compression. RFI contaminated data are removed and replaced by neighboring uncontaminated data. Discarding contaminated data degrades resolution and increases speckle noise, but avoids the larger errors associated with RFI. In this presentation, we will discuss the expected performance of these correction algorithms. This work is supported by the SMAP project at the Jet Propulsion Laboratory, California Institute of Technology.