GISMO Team Meeting JPL January 31, February 1, 2007

GISMO Team Meeting Agenda January 31 Progress to date 1300 Status and Summary of Mid Year Review, Budget Issues - Jezek Planning for April 07 Experiment 1320 Science and Engineering Objectives for April 2007 (Jezek) 1330 Radar and antenna status (Gogineni) 1400 Vexcel Data processing Status, Interface and Readiness (Refraction, Motion Compensation, Calibration) (Wu) 1430 JPL Data processing status, Interface and Readiness (Refraction, Motion Compensation, Calibration) (Rodriguez) 1500 Navigation (Sonntag) 1515 Arctic 07 Planning Status and key milestones (Krabill) 1530 Proposed Flight Lines (Fahnestock and Sonntag) and Discussion 1600 April 07 Experiment Plan and Discussion (Jezek) (see May 06 vu-graphs for sample experiment plan form) 1730 Adjourn February 1 Algorithms 0830 Tomography Algorithm Status (Wu) 0900 InSAR algorithm status (Rodriguez) 0930 Update on Multiaperture beam processing (Gogineni) 1000 Plans for reducing May 2006 data to topography (Wu, Rodriguez, Forster) 1030 Break 1045 Plans for investigating ionospheric effects and corrections (Freeman) 11:15 Data management issues, schedule for delivery of April 07 data, action Items (Jezek) 1200 Adjourn

Objectives Briefly review project status Prepare draft experiment plan for April ’07; identify implementation issues Review algorithms; May 06 processing (topography); April 07 processing issues

Project Status

Project Accomplishments Theoretical concept well defined Phase history simulations confirm theoretical predictions Radar design trade completed Scaling study completed 150 MHz radar system deployed for May 06 test flight in Greenland For the first time, SAR data acquired from aircraft and successfully processed to SAR images and interferograms of glacier bed

Data Processing Lessons Learned Time reference functions In range compression the ideal chirp is used for each receive channel. We plan to measure the received chirp from each receive channel and use them to do range compression. These actual range reference functions may give us some improvement in focus and SNR in the range compressed images. Motion compensation We are quite sure the motion data are quite accurate for the 150 MHz carrier frequency data. But in April 2007 we are going to collect data using 450 MHz carrier frequency. Motion data may become less accurate relatively. We plan to use the current 150 MHz data to investigate motion compensation methods and try to find appropriate approaches to improve the azimuth compression for the special cases of the ice sounding SAR images. Imaging model with ice mass refraction Any image formation algorithms assume that the electromagnetic wave which carries the radar waveforms is traveling in the same homogeneous media like the air. It is not the case for ice sounding radars. For the data collection in May 2006 the ice thickness is about 2000m and the slant range between the radar sensors and the ice surface is only about 1000m long. There are two main differences between the ice sounding radar and the normal surface mapping radar. The first one is the refraction which happens at the air-ice boundary and changes the travel directions of the electromagnetic wave. The other is that the travel velocity within the ice is about 1.8 times slower than in the free air. We plan to model the ice mass with two layers and try to improve the azimuth compression results by taking into account the refraction and the different travel velocity. Tomography processing Try to verify tomography technique for generating 3D volumetric images of the regions of interest in Greenland and/or in Antarctica using the data acquired in May 2006 and the data yet to be acquired in April The methods to be tested include direct convolution back-projection from the phase history data and the method of creating 3D images from already-formed 2D complex images.

Multi-Aperture Lessons Learned Using multi-aperture arrays and spatial filtering, measured for the first time the ice thickness across Jacobshavn Glacier and to the calving front Analyses indicate that increasing the number of antenna elements from 4 to at 450 MHz improves spatial filtering sufficiently to develop an automatic clutter rejection algorithm

Navigation Lessons Learned from May GISMO flight used Soxmap / Twin Otter combination –Configuration more suitable for outlet glacier work –Steering within +/-50m, could be better 2007 GISMO flights will use CDI with P-3 –Better repeatability for straight flight lines –Soxmap backup More info: atm.wff.nasa.gov; click “Aircraft Navigation”

May 06 Experiment Summary Lessons Learned 1) Single pass, across track SAR imaging from aircraft is possible even in areas where the base of the ice sheet appears to be relatively smooth. 2) Across track interferometry is possible in the area where backscatter is relatively weak. This is consistent with theory. The fringe rates we observe are reasonable for the short (~7 m) baseline we achieved on the Twin Otter aircraft. 3) Given the measured fringe rate patterns, we expect to retrieve across track measurements of basal topography. 4) Data processed so far steer the beam 20 degrees off nadir. Depending on the product of the beam pattern with the backscatter falloff, this may or may not be optimum. We will analyze the data with different degrees of beam steering. 5) We did not observe fringes from the ice sheet surface in the most recently processed data. Yet we can clearly see internal layers, which should have a much lower backscatter value than the surface return. We will investigate how beam steering angle influences the measured backscatter from the ice sheet surface. 6) We observe detailed internal layers in the range and azimuth compressed data. We also observed the frequently described internal layer free zone near the base of the ice sheet. 7) 150 MHz backscatter strength is sufficient to yield a measurable signal. We will test and compare 150 MHz and 450 MHz systems. 8) The May 23 data collected observations along the same in and out bound track. We will investigate how longer baselines derived from repeat pass data effect data quality. 9) We observed a systematic noise pattern in the amplitude and interferometric data. The noise artifacts in the InSAR data will be an additional complication for interferogram filtering. The noise source is not always on and we will attempt to identify the origin of the noise source. 10) We must measure the time reference functions prior to the experiment.

Project Tasks (green: complete; orange: in progress) Year 1 Science and Management (OSU): Convene Science Team; conduct initial design review; refine project plan compile information on ice dielectric properties and ice sheet physical properties such as surface roughness and slope. Prepare reports as required by NASA Radar Development (University of Kansas: a) Design of new set of optimized antennas: We will build a model structure and measure its electrical performance. We will identify and work with a contractor to build the antenna installation mounted under the wings and flight test it in collaboration with engineers at NASA Wallops. b) End-to-end simulation of the system including antennas. (work completed for Twin Otter – flight testing in progress for P-3) Algorithm Development: Develop a motion compensation processor and a time-domain (back-propagation) IFSAR processor. Use legacy code from the GeoSAR and MOSS IIP projects. (JPL planned for April 07): b) Prototype first version of the interferogram filtering code (JPL); c) Modify simulation software and generate simulated IFSAR returns from basal and surface layers (Vexcel) and evaluate the filter performance on the simulated data.

Project Tasks Year 2 Radar Development : Build sub-system and assemble the complete system.(150 MHz complete, 450 MHz in progress) Perform laboratory tests using delay lines to document loop sensitivity,radar waveforms and impulse response. System Integration (KU, WFF, Aircraft Operator) a)Install the radar and navigational equipment on P-3 or similar aircraft and conduct flight tests over the ocean. (Planned for April 07) Algorithm Development. Develop a strip IFSAR processor and compare against the results of the exact time-domain processor. Iterate the clutter removal algorithm based on experimental results (JPL)(awaits Arctic 07 data). Develop software and apply software to process multiple 2-D complex SAR images coherently (Vexcel). Data acquistion and Analysis : Field experiments over the ice sheet; Finalize interferometric SAR processor and pre-processor and process data from first campaign (JPL). Extract basal topography from result. Iterate interferometric filter design based on assessment of the results. Science and Management : Participate in field measurements; Conduct design and performance review; assess quality of results in context of science requirements. (Completed for Twin Otter; In progress for P-3)

Project Tasks Year 3 Data Acquisition and analysis: Conduct second airborne campaign; Reduce and analyze data. Develop software and apply software to process multiple raw data acquisitions tomographically. Apply linear beam forming techniques (Demonstrated with twin otter). Extract basal topography from result. (Vexcel) Mission Design: Spaceborne mission design based on the experimental results. Science and Management: Participate in final field experiment; convene final review; develop mission concept in terms of science requirements and experimental results; prepare final reports.

Additional Issues After discussion with ESTO, JPL and Vexcel, $50k will be transferred from the OSU budget to Vexcel for additional effort as specified in a workstatement provided in Year 2. $50k will be deducted from the JPL budget in Year 3 and added to the OSU budget. A short proposal to ESTO will be required during the annual resubmit. The Year 3 airborne experiment will occur near the end of the project. Given current spending projections, a no-cost extension is anticipated to allow for analyzing data from the experiment. OSU will provide budgetary details on all project expenditures. However, this is complicated by the fact that monies are transferred directly from ESTO to Wallops (aircraft support Year 2) and to JPL (processor development). It is proving challenging for OSU to get this information through formal channels. That said, OSU is aware of under-spending at JPL. OSU closely works with Wallops on flight costs for Arctic ’07 and will monitor expenditures. An issue is whether to again transfer aircraft costs directly from ESTO to Wallops or whether there can be more exact accounting if monies are sent directly to OSU as originally planned.

Cummulative Spending – ESTO Requirement to Update for All Projects Expenditures