Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
The Spectrum-Time Estimation and Processing (STEP) framework integrates three novel algorithms addressing data quality at the lowest possible level: spectrum clutter identification, bi-Gaussian clutter filtering, and multi-lag moment estimation. Spectrum clutter identification is a technique to automatically identify ground clutter contamination, adapting to a changing clutter environment while minimizing unnecessary filtering. Bi-Gaussian clutter filtering is an adaptive spectral filter that separates clutter and weather signals in order to maximize clutter suppression while minimizing the degradation of weather information. Multi-lag moment estimation addresses noise effects in moment estimation by employing more of the signal's correlation.
Enterprise Electronics Corp. (EEC) has implemented this technique in real-time on its SDR series of solid-state X-band radar in order to maximize the system's data quality. We examine here the improvements gained over traditional signal processing, with a focus on effective sensitivity improvements for low-powered systems.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner