Conference proceeding
Frequency diverse statistic filtering for clutter suppression
International Conference on Acoustics, Speech, and Signal Processing, pp 1349-1352 vol.2
1989
Abstract
By combining the conventional order-statistic filtering concept with the split-spectrum processing (SSP) technique, a method called frequency-diverse statistic filtering is obtained. Three types of frequency-diverse statistic filters, namely, weighted mean, median, and absolute-minimization, are examined. It is shown that if the target and the clutter spectra are known individually, the Weiner filter can be realized by frequency-diverse statistic filtering using a linear operation (i.e. weighted mean). However, if only the input signal is known, the frequency-diverse statistic filter with a nonlinear order-statistic operation (i.e. median or absolute-minimization) can be used, resulting in SNR (signal/noise ratio) enhancement. Both computer simulation and experimental data have been used to evaluate the performance of the filters and verify the theoretical analyses.< >
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Details
- Title
- Frequency diverse statistic filtering for clutter suppression
- Creators
- X Li - Drexel UniversityN.M Bilgutay - Drexel UniversityJ Saniie
- Publication Details
- International Conference on Acoustics, Speech, and Signal Processing, pp 1349-1352 vol.2
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Materials Science and Engineering
- Other Identifier
- 991019182776104721