1. Road-mapping the Way Forward for Sentinel-3 Topography Mission SAR-Mode waveform Re-tracking over water surfaces
J Benveniste, P Cipollini, C Gommenginger, C Martin-Puig, D Cotton, S Dinardo, NOC (UK), Starlab (Spain), SatOC (UK), ESA/ESRIN (Italy)

2. Introduction
This talk deals with findings and challenges relevant to the Sentinel-3 Radar Altimeter over ocean
We will see:
What is special about the Sentinel-3 Altimeter
What are the challenges
Validation Exercise: height inter-calibration with Jason-2 and SWH calibration w.r.t. wave buoys
Conclusions

3. Conventional Low Resolution Mode (LRM)
Vs/c
PRF: ~2 kHz
In LRM, the pulse-limited footprint moves across the surface pulse by pulse as the satellite passes overhead
The footprint of a conventional pulse-limited altimeter moves along the surface at (essentially) the same rate as the progress of the satellite along its orbit. Typically, the altimeter transmits a pulse 1000 to 2000 times per second (the so-called pulse repetition frequency). Since the speed of the satellite (projected onto the surface) is about 6.7 km/s, the effective along-track length of the footprint is increased in proportion to the number of pulses so averaged.
The half-power width of the antenna beamwidth projected onto the surface is (typically) about 15 km, which is several times larger than the pulse-limited footprint.
3-7 km depending on sea state
Courtesy: K. Raney, APL/JHU

4. SAR altimeter (Cryosat-2, Sentinel-3): fundamentally different!
Vs/c
PRF: ~20 kHz
SAR altimeter uses Doppler frequency effect to spotlight a small area along-track ( m) resolved by each burst as the satellite passes overhead
A delay-Doppler radar altimeter uses signal processing techniques to resolve a small along-track footprint. The altimeter in effect “stares” at each resolved surface location for as long as that particular cell is illuminated by the antenna as the spacecraft passes over head. The minimum size of such a delay-Doppler-resolved cell is about 250 meters, which is a constant (determined by system parameters and viewing geometry). Note that each cell is viewed over a larger fraction of the antenna beam than the pulse-limited; thus more data is gathered, which leads to substantial benefits (reviewed in subsequent materials).
If only one such cell were illuminated, the measurements could not keep up with the forward velocity of the antenna footprint. The system gets around this objection by operating many of these spotlight beams simultaneously. A typical design would generate 64 parallel Doppler beams, but not all of these fall within the main lobe of the antenna. Thus, in practice there will be date from ~40 beams combined in the processor to generate the final (averaged) waveform from each resolved cell.
Courtesy: K. Raney, APL/JHU
meters

5. At t=0, the SAR footprint is no longer circular but rectangular !!
At t=0, the Across Track Resolution is the same as Pulse-Limited Altimetry (Pulse-Limited Diameter) but the footprint size reduces with the time delay
RED LRM
GREEN SAR
t<0
t=0
t>0
The footprint area is no longer constant with time delay

6. Multi-looking
Doppler-beam selection/weighting & incoherent integration of beams from multiple bursts starting at the same ground cell (to reduce the speckle noise) i.e. multilooking
128 gates
1D multi-looked
20Hz waveform
Note the peaky waveform shape and the long decaying tail due to varying footprint area in SAR Mode

7. Predicted advantages of SAR over LRM
More independent looks  improved retrieval precision
Two-fold improvement according to numerical studies by Jensen & Raney (1998)
Finer spatial resolution along track
~300 meters along-track
Higher SNR
~10 db more
Better performance close to land
especially for track ~90° to coastline
Less sensitivity to sea state
..to investigate these and other things, ESA has setup…SAMOSA!! (next slide)

8. THE FUTURE: Sentinel-3 Surface Topography Mission
THE PRESENT: Cryosat-2
LRM: most of open ocean + most of land
SAR: some oceanic & coastal regions + sea ice
SARIN: few pilot regions (ocean & land) + land ice
THE FUTURE: Sentinel-3 Surface Topography Mission
LRM: open ocean
SAR: global coastal ocean + sea ice
SAR open loop: ice sheet margins
SAR open/closed loop: land & inland waters

9. The ESA SAMOSA Project:
Study funded by ESA STSE, led by David Cotton (SatOC)
Starlab, NOC, De Montfort University, DTU Space & expert support from Keith Raney (JHU/APL)
Objectives & Methodology
Quantify range retrieval accuracy in pulse-limited and SAR mode as a function of significant wave height
Develop physically-based models for SAR altimeter ocean waveforms
Apply physically-based models to SAR ocean waveforms
Done for both simulated and real Cryosat SAR waveforms over ocean
Investigate method to reduce SAR mode data to pseudo-LRM
Applications to airborne SAR altimeter data, SAR waveforms over inland water (DMU), coastal regions, sea floor mapping (DTU Space),…
Development and Validation of SAMOSA SAR re-tracker with Cryosat-2 SAR mode data over ocean

10. Next-generation SAMOSA models
SAMOSA1 gives acceptable fit to Cryosat-2 SAR waveforms BUT…
Circular antenna beam, no across-track mispointing
Non-physical behaviour for large mispointing angles
Over-estimates significant wave height (Hs)
Next generation model: SAMOSA2
entirely new physically-based formulation developed by Starlab
Accounts for asymmetric antenna beam, ellipticity of the Earth, along- AND across-track mispointing, non-linear ocean wave effects
Physically correct response to mispointing
Improved fit to Cryosat-2 SAR waveforms
BUT… not fully-analytical & computational expensive

11. SAMOSA3 model
Simplification of SAMOSA2 while keeping its advanced features
fully-analytical, robust and computationally fast !!

12. Comparing SAM1, SAM2 and SAM3
With SYMMETRIC antenna beam and no Earth ellipticity effects:
SAM3 and SAM1 are equivalent !!
These two entirely independent theoretical models converge !

13. SAMOSA 3 Project:
Study funded by ESA STSE, led by David Cotton (SatOC)
Starlab, NOC,
Objectives & Methodology
Develop and characterize SAM3 model (Trade-off TN)
Deliver to the Sentinel-3 STM PAD a Detailed Processing Model (DPM) of a SAR ocean waveform re-tracker based on the best SAMOSA model to operationally retrack Sentinel-3 SAR-Mode L1b waveforms
Validate Retracker using Cryosat Data in high and low sea conditions

14. SAMOSA 3 DDM and Re-tracker:
Physically-based model developed by Starlab from first principles
Analytical ( by Bessel Functions) solutions to model the Delay Doppler Maps (DDM) for the full span of Doppler Frequencies
Model depends on epoch, significant wave height, Pu, surface rms slope, and mispointing angle(s),
The model independent variables are the Doppler Frequency and the Time Delay
The waveforms are retracked by Least- Square Fitting Algorithm (Levenberg-Marquard)

15. Model Behaviour: effect of Sea State (SWH)
SWH affects the width of lobe of the SAR waveforms
SAMOSA3 model:
Dependence of waveform shape on SWH

16. Model Behaviour: effect of mispointing
Roll mispointing affect shape of the SAR waveforms
Model insensible to pitch mispointing
Effect significant only for mispointing greater than 0.1 deg

17. Effect of along-track mispointing:
negligible

18. Effect of across-track (roll) mispointing:
changes waveform tail
0.5°
0.3°
0.1°
0.0°

19. Challenges of SAR altimetry

20. Challenge 1: LRMSAR transitions

21. LRMSAR transitions (cont.)
Methodology to reduce SAR mode data to pseudo LRM has been developed by Starlab (RDSAR method)
Tested and validated with simulated SAR waveforms:
Full Bit Rate (FBR) SAR can be successfully transformed into pseudo-LRM waveforms that can be re-tracked with Brown model
RDSAR anyway does not give the same range noise as LRM (less number of accumulated independent looks)
RDSAR ensures continuity

22. Challenge 2: Coastal Zones
Waveforms at 20 Hz, one waveform each 300 meters – Optimal Conditions
Coastal Zone

23. Effect of the Land -> LIMITS
Track Orientation and bright targets can have effect on the level of the Land Contamination.. Even in SAR mode !!!
The land contamination in SAR Mode is greatly reduced but still present in unfavourable cases; MisFit and Ground Track Orientation to the coastline can be parameters useful to quantify the contamination

24. Challenge 3: Inland Water

25. Validation Exercise over open sea

26. CryoSat-2 and Jason-2: Range error in SAR and LRM as a function of sea state
Lots of CryoSat-2 data in LRM and SAR mode since July 2010 but not collocated (SAR and LRM are exclusive modes)
Comparison of CryoSat2 SAR with Jason2 LRM
Focus on small area in Norwegian Sea
July 2010 – March 2011
Wide range of sea states

27. Variability in SSH (Norwegian Sea)
SAM3 SSH
Ksiyinput = 0.01 deg
CryoSat-2 SAR (Hs < 2m)
SSH std 20Hz: cm
1Hz: cm
Jason-2 LRM (Hs < 2m)
SSH std 20Hz: cm
1Hz: cm
Factor of 1.43 reduction in SSH error with CryoSat-2 L1B SAR
SAR perf will improve with reprocessed CryoSat-2 L1B data

28. Variability in Hs (Norwegian Sea)
SAM3 SSH
Ksiyinput = 0.01 deg
CryoSat-2 SAR (Hs < 2m)
Hs std 20Hz: m
1Hz: m
Jason-2 LRM (Hs < 2m)
Hs std 20Hz: m
1Hz: m
Slight bias in SAR Hs ?
Factor of 1.26 reduction in SWH error with C2 L1B SAR

29. Bias in SAR Hs ? Validation against buoys
Buoy wave height data from UK Met Office
CryoSat-2 SAR data and buoys collocated within 50km and 30 minutes
Data for July May 2011

30. CryoSat-2 SAR Hs against buoys
Linear relation between C2 SAR Hs and buoy Hs over full range of sea states
Small bias < 0.5 m; Std ~ 0.3 m
Hs bias is directly linked to roll mispointing used as input to the SAR retracker
use of platform mispointing data as input to the SAR retracker should reduce this bias
Need to account for known small systematic bias in roll mispointing for C2 (Scharroo, pers comm.)
SAM3 SWH
Ksiyinput = 0.01 deg

31. Conclusions
Performance of CryoSat-2 SAR should improve with optimised SAR retracking that uses platform roll mispointing as input
Both variability and SWH bias
Same analyses to be repeated in a less dynamic region
Analyses of CryoSat-2 SAR performance against pseudo-LRM products
In summary:
CryoSat-2 SAR mode produces very good data over ocean
we have a fully-analytical, robust and computationally efficient model that successfully retracks CryoSat-2 SAR waveforms
SAR shows improved performance compared to LRM for both SSH and SWH
SAR opens up a wide range of new scientific possibilities over ocean, coastal zone and inland water
Ready for Sentinel-3!