GISMO Simulation Status Objective Radar and geometry parameters Airborne platform upgrade Surface and base DEMs Ice mass reflection and refraction modeling.

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Presentation transcript:

GISMO Simulation Status Objective Radar and geometry parameters Airborne platform upgrade Surface and base DEMs Ice mass reflection and refraction modeling Airborne SAR and IFSAR processor Ice sounding processing P-band simulation results VHF simulation results

Objective Purpose is to perform analysis to validate a new technique for ice sounding in polar areas using a low frequency airborne SAR platform and interferometry technology and provide some guidances about the airborne SAR system design and ice sounding processing. Approach –simulation of phase history data using the geometry and characteristics planned for GISMO –processing phase history data to single look complex data and interferograms using VEXCEL’s Airborne SAR Processor and IFSAR processor –assessment of the novel sounding technique performance in clutter cancellation and mapping basal topography.

Radar and geometry parameters CharacteristicsP-BandVHF RF Carrier Freq430 MHz150 MHz RF Bandwidth20 MHz50 MHz Pulse Width20 usec PRF200 Hz Sampling Freq120 MHz Antenna Elements 44 Platform Height6000 m Baseline20 m

Airborne Platform upgrade Generate airborne sensor track –Scene center : S C (, , 0) –Orbit altitude : h –Track angle :  –Left or right looking –Look angle :  L Simulate air turbulence Along track :  x =  x a sin(2  f xa t +  xa ) +  x e sin(2  f xe t +  xe ) Horizontal :  y =  y a sin(2  f ya t +  ya ) +  y e sin(2  f ye t +  ye ) Vertical:  z =  z a sin(2  f za t +  za ) +  z e sin(2  f ze t +  ze ) Multiple slave antennas simulation

Surface and base DEMs (Greenland) Surface DEM Base DEM 62.5 km km

Ice mass reflection and refraction modeling n 1 =1 n 2 =1.8 n 3 =3 (for rocks) 11 2 2 basal DEM (land or water) surface DEM ice mass S A B C Fig. 1 ice mass reflection and refraction model H D h d s s xbxb xsxs

Space-borne SAR phase history data simulation Reflectivity map calculation for both reference and slave antennas Phase history data generation

Reflectivity map calculation 1 1 22 basal DEM (n 3 : land or sea water) surface DEM (n 1 ) ice mass ( n 2 ) S (sensor) A B C ground range grids Fig. 2 Implementation of reflectivity map calculation S 2 (sensor) B (baseline) All quantities: slant range, incidence angle, refraction angle and reflection coefficients, are calculated at each ground range grid. A slant range grid will lie between two neighboring ground range grids. The reflectivity coefficient for each slant range grid is calculated through interpolation of these two neighboring ground range bins. When calculating the reflection from the basal, we still start from the ground range grid on the surface. The refraction vector may or may not hit exactly the ground range grids. Bilinear interpolation is therefore used to calculate the refraction pointing vector from each surface ground grid to the basal. At each surface ground range grid the basal reflection coefficient and the slant range from the sensor to the basal are calculated. All the calculations for the second orbit are the same as for the reference orbit except the interferometric phase, which is the result of the non-zero baseline and DEMs, is added to the secondary reflectivity map for both surface and basal calculations.

Phase history simulation Inverse chirp scaling Phase history data H SAR (f) SLC data Reflectivity map H -1 SAR (f) Phase history data

Airborne SAR Processor Time-domain convolution-back-projection –Accurate but time consuming –Capable of 3D image generation –Accept any imaging plane Time-domain fast back-projection –Less accurate but much faster –Suitable for airborne large scale image processing –Accept any imaging plane

Airborne IFSAR Processor Image registration Create interferogram Filter interferogram Phase unwrapping –Only MiniMax is available Now –Need a better phase unwrapper even though it might be very slow

Ice Sounding Processing Interferometric ice sounding processing –Band-pass filtering to extract surface and basal interferogram –Derive surface topography –Derive base topography

P-Band simulation Antenna pattern used Surface and basal DEMs used Simulated reflectivity map and phase history data FBP processed images Interferograms without and with band-pass filtering Derived surface and basal topography

Antenna pattern with 4 elements

P-band simulation … DEMS in slant range geometry 6.5 km surface DEM 6.6 km (ground range) echo delay caused by the ice thickness at nadir basal DEM 6.6 km

P-band simulation … Reflectivity Map Amplitude images of the phase history data FBP processed SLC image

P-band simulation … 8-azimuth-look interferogram 2  ground range 6.6 km Azimuth (6.5 km) 0 Filtered interferogram

P-band simulation … ground range 6.6 km Azimuth (6.5 km) Derived surface DEM DEM error map

P-band simulation…… basal interferogram ground range 6.6 km Azimuth (6.5 km) Band-pass filtered 8-looks interferogram

P-band simulation…… basal interferogram ground range 6.6 km Azimuth (6.5 km) Goldstein  -filter filtered interferogram Unwrapped phase

VHF simulation Simulated reflectivity map and phase history data FBP processed images Interferograms without and with band-pass filtering

VHF simulation Reflectivity Map Amplitude images of the phase history data FBP processed SLC image

VHF simulation 8-look interferogram ground range 6.6 km Azimuth (6.5 km)

VHF simulation Band-pass filtered  -filtered

GISMO’s Potentials for Tomography Applications One flight track –track altitude : 10 km –4 ~ 6 receiving antenna elements –total aperture: 20 m Multiple flights –Assume 10 or more flights –Total 40 ~ 60 measuremes –total aperture: 400 m H (flight height) 11 22 Baseline D (ice thickness)