Optimization of Enhanced Observing Payload System through characterization of calibration and historical data sampling
Northrop Grumman Electronic Systems (NGES) in Azusa is a leading systems integrator for Microwave payloads that supports many government programs like DWSS, NPOESS, JPSS, METOP, and others. NGES has developed imager and sounder payloads like AMSU, ATMS, and SSMIS which have been flying operationally for decades, providing successful data for weather forecasting over different frequency channels and data fusion for improved weather characterization.
In our presentation we would like to share, our conceptual instrument's capability (based on the SSMIS payload) for improved detection and forecasting through a highly evolved Noise injection calibration method. We will provide an overview of our instrument. Finally, we will show how low-cost improvements may be made to the design to significantly improve the weather forecasting capabilities of the sensor.