1. Interferogram Filtering vs Interferogram Subtraction
E. Rodriguez
Jet Propulsion Laboratory
California Institute of Technology

2. UHF Fringe Spectrum No Antenna Pattern
Interferogram spectra for signal to clutter ratio of 1, radar frequency of 430MHz, bandwidth of 6MHz, for the first 50 km of xb. The basal spectrum is colored orange. The remaining curves show the surface spectra for
D = 1 km (black),
D = 2 km (red),
D = 3 km (green),
D = 4 km (blue). Notice that the basal fringe spectrum depends very weakly on depth

3. Interferogram Spectrum and Angular Variations of Brightness
Complex interferogram
Surface interferometric phase difference
Basal interferometric phase difference
The effect of long wavelength variations (due to the antenna pattern or sigma0) is to convolve the interferogram spectrum with the envelope spectrum. This can lead to significant spectral overlap.

4. Observed Surface Sigma0 Angular Dependence at 120 MHz
Data obtained with the JPL Europa Testbed Sounder in deployment with the Kansas U. sounder over Greenland
Angular decay near nadir (>15 dB in 5 degrees) consistent with very smooth ice surface
Change in behavior at P-band is still unknown, but probably bounded by 1-3 degree slope models

5. Topographic Simulation Results
Topography Weighted by Gain
Surface Interferogram
Basal Interferogram
Distance (km)
Range
Range

6. Antenna Pattern Results: 2 km
Surface Return
Basal Return
Before filtering
After filtering

7. Antenna Pattern Results: 3 km What should be done about long wavelength brightness variations?
Basal Return
Surface Return
Before filtering
After filtering

8. Proposed Solution
Rather than do blind Fourier filtering, treat surface signal as known up to a multiplicative constant (or similar low order polynomial), which is estimated by fitting and the interferogram phase known up to a constant + slope terms. The fitted signal is removed by subtraction.
Known parameters: antenna gain, flat surface interferogram rate.
Unknown parameters: surface slope, precise sigma0 variation. First sigma0 estimate from azimuth averaged intensity data.
Validity of subtraction scheme has been shown to work on simulated data. Significantly better clutter reduction than Fourier filtering.
Needs to be verified with real data