TU3.L09 - Critical Assessment of diverse Polarimetric SAR Systems – pros and cons
1. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 1 Hawaiian Village, Honolulu, Hawaii, 2010 July 25 – 30 IGARSS10-TU3.L09-4414, Sea Pearl 1/2/3 Tuesday, 2010 July 27, 13:35 – 15:15 "Critical Assessment of diverse Polarimetric SAR Systems – pros and cons” Wolfgang-Martin Boerner1 Invited Presentation 1. UIC-ECE/CSN, 900 W Taylor St, SEL-4210, CHICAGO, IL/USA-60607-7018, + I-312-996-5480, wmb1uic@yahoo.com IEEE International Geosciences& Remote Sensing Symposium
2. Wolfgang-Martin Boerner1, Thomas L. Ainsworth2, Eric Pottier3, Ya-Qiu Jin 4, Shane Robert Cloude5, Yoshio Yamaguchi6, Jakob J. vanZyl7, Konstantinos (Kostas) P. Papathanassiou8, Carlos Lopez-Martinez9 1. UIC-ECE/CSN, 900 W Taylor St, SEL-4210, CHICAGO, IL/USA-60607-7018, + I-312-996-5480, wmb1uic@yahoo.com 2. NRL-RSD/ISS, Code 7263, 4555 Overlook Ave SW, Bldg-2, WASHINGTON, DC/USA-20375-5351, ainsworth@nrl.navy.mil 3. Univ-Rennes-1, IETR-SAPHIR, Beaulieu Bat 11D, 263 ave Gen. Leclerc, F-35700 RENNES, FR, +33-2-23235763, eric.pottier@univrennes1.fr 4. Fudan Daxue, East Guan Hua, Floor 11, Room 1103, 220 Handan Road, Yangpu, Shanghai, PRC-200-433, yqjin@fudan.ac.cn 5. AECL, 26 Westfield Avenue, Cupar, Fife KY15-5AA, Scotland UK, aelc@mac.com 6. NU-IE, Ikarashi 2 Nocho 8050, NIIGATA-Shi, 950-2128, +81-25-262-6752, yamaguchi@ie.niigata-u.ac.jp 7. NASA-JPL, CALTECH MS 180-804, 4800 Oak Grove Dr, PASADENA, CA/USA-91109-8099, +1-818-354-1365, Jakob.J.vanZyl@jpl.nasa.gov 8. DLR-HR, Muenchener-Str. 20, Geb-102, D-82230 OPH-WESSLING, Obb, GER, +49-8153-28-2306, kostas.papathanassiou@dlr.de 9. UPC-TSC/ARS-Group, North Campus, Bldg. D3, Room 203, Jordi Girona 1 – 3, Barcelona, Spain, ES-08034, clm@ieee.org WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 2
3. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 3 ABSTRACT-1 Considerable advances have been made during the past decades in polarimetric SAR systems leading to increased ability for recovering inherent polarization information conveyed by vector-electromagnetic wave backscatter. This paper compares the benefits offered by the major types of systems in relation to their application, as a function of their polarimetric architecture. POL-SAR system characterization includes the radar sensor, processing to transform the received data to polarimetric products, and calibration. More complex scattering scenarios require more capable polarimetric data collection and analysis. The system types considered are: Mono-Pol (single polarization, amplitude-only); Dual-Pol (traditional amplitude-only configuration, including HH+VH, VV+HV); Compact-Pol (transmit one polarization in base AB, and coherently receive two orthogonal polarizations in orthogonal base CD, which retain the relative phase between the received polarizations); and Full-Pol (coherent HH, HV, VH and VV).
4. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 4 ABSTRACT-2 Under the simplifying assumption of scattering symmetry in monostatic configurations implying HV=VH, the Full-Pol data reduce to the familiar Quad-Pol products (coherent HH, HV and VV). Compact-Pol architectures include: Coherent Linear LH-Pol (HH+HV, or VV+VH, or HH+VV, coherently in each case); Coherent Diagonal/Linear DL-Pol (transmit linear polarization at a diagonal angle of 45* with respect to horizontal, and receive coherently the conventional linear H and V, thus DH+DV); Coherent Circular LR-Pol (coherent RR+RL or LL+LR); Coherent Hybrid Circular/Linear CL-Pol (RH+RV or LH+LV). The amount of acquired data (and of all data-dependent subsystems such as storage and transfer), processing and calibration increases, for greater polarimetric sophistication; and so do mass and volume with greater polarimetric capability. The various architectures have different implications on data rate, swath-width and resolution issues that apply to any multi-channel radar whether polarimetric, interferometric or for multiple frequencies. Given this multi-dimensional possibility space, the paper attempts to identify the benefits of each type of system as a function of implementation, also addressing the forthcoming demands of space-borne POLin SAR and RP (Diff) POLinSAR deployments.
5. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 5 ABSTRACT-3 Since SEASAT (Mono-Pol HH, L-band), space-based SAR systems are gradually becoming polarimetrically more capable, including ENVISAT (Dual-Pol, C-band), ALOS-PALSAR (Full-Pol or Quad-Pol, depending on processing algorithm, L-band), TerraSAR-X (Full-Pol or Quad-Pol, X-band), and RADARSAT-2 (Full-Pol or Quad-Pol, C-band). Planetary examples include Magellan (Venus: HH, S-band), Cassini (Saturn: Mono-Pol – amplitude-only, Ku-band), two Mini-SARs (Moon: CL-Pol, S-band or S- and X-band), for which mass and data rate (or data volume) are critical parameters. Polarimetric diversity implies additional costs and impacts the mission operation scenario defined by user requirements and/or technological constraints. However, the paper hazards recommendations for the polarimetric architecture of future space-based SAR Systems; and it is concluded that any so-called cost-saving measures are ill-conceived and that we need to focus fully on the advancement of fully polarimetric SAR systems technology and stop all of the regressive approaches which will only take us back to the child stage of SAR concept initiation.
6. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 6 ABSTRACT-4 Contributing remarks by Dr. Lopez-Martinez Respect to your comments about compact-pol it is true that it is a step back concerning PolSAR. For instance, in terms of data classification, the lack of complete polarimetric information may lead to misclassification. From my experience, people are demanding operational classification. So, if we do not have fully polarimetric information, we will not be able to demonstrate this capability. Nevertheless, there is a more "dramatic" reading of the history of compact-pol vs full-pol. Final users are not polarimetric experts, so they are not able to distinguish compact-pol from full-pol. So, if they see poor results from compact-pol data, they will assume the same type of results with full-pol. I guess, it should be necessary to show what is lost from full-pol to compact-pol.
7. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 7
8. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 8 Orthogonal Tx pols Coherent Dual Rx Pseudo 3x3 scattering matrix One Tx Pol, Coherent Dual Rx Symmetry assumptions 2x2 covariance matrix No symmetry assumptions 2 magnitudes & co-pol phase Two Tx pols Two Rx pols 2 magnitudes 2 magnitudes One polarization Magnitude Polarimetric Imaging Radar Hierarchy R.K.Raney Nomenclature Result Processing Radar 4x4 scattering matrix No assumptions Full polarization Reciprocity & symmetry Quadrature polarization 3x3 scattering matrix Compact polarization No HV 2 orthogonal Like-pol images & CPD 2 orthogonal Like-pol images Dual polarization Like- and Cross-pol images Mono-polarization Real image
9. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 9 Ship Detection Using the Convair-580 (30to 60 incidence angle) Touzi et al, “Ship detection and characterization using polarimetric SAR”. CJRS, Special issue on RADARSAT-2, June 2004 HH HV VV Compact-RV Touzi Anisotropy Full-Pol Compact-RH
10. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 10 N Red: Sendai7602_HH polarization Green: Sendai7603_HH polarization Blue: Sendai7604_HH polarization
11. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 11 Flight direction Square path data
16. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 16 4-compornent scattering power decomposition algorithm using rotated coherency matrix Rader line of sight Deorientation Rotation of imsge
17. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 17 4-compornent scattering power decomposition algorithm using rotated coherency matrix
18. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 18 4-compornent scattering power decomposition algorithm using rotated coherency matrix
19. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 19 Four-component decomposition New rotated decomposition Scattering power decomposition by rotation of coherency matrix forNiigata City area in Niigata Prefecture of Japan
20. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 20 Sapporo City, Hokkaido Prefecture, Japan (a) Original decomposition (b) Decomposition after T33 rotation (e) Patch C: forest (d) Patch B: oriented urban (c) Patch A: orthogonal urban Deorientation
21. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 21 Interest area 3800m 0m Monitoring of ongoing surface deformation along Cheleng-Pu fault Data fusion of DEM and RADARSAT SAR images By CSRSR. Taiwan
22. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 22 “Natural hazards are inevitable. Natural disasters are not.”
29. WIDEBAND INTERFEROMETRIC SENSING AND IMAGING POLARIMETRY 29 FOUNDATIONS AND RELEVANCE OF MODERN EARTH REMOTE SENSING & ITS ACTIVITIES Conclusions: The Electromagnetic Spectrum: A Natural Global Treasure Terrestrial Remote Sensing with PolSAR: The Diagnostics of the Health of the Earth at all weather and volcanic conditions and at day and night
