Multiband Polarimetric SAR in Arctic Scenarios

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1 Multiband Polarimetric SAR in Arctic Scenarios Technology demonstration for potential future capabilities Ernst Krogager Joint Research Centre Danish Defence Acquisition and Logistics Organization (DALO) Ballerup, Denmark Abstract In relation to a working group on future capabilities for applications in the Arctic region, the Danish Defence Acquisition and Logistics Organization (DALO) has conducted test campaigns with the multi-band, fully polarimetric F-SAR system owned by the German Aerospace Center (DLR) in order to explore the possibilities that advanced synthetic aperture radar (SAR) systems provide for surveillance, change detection, moving target identification and high resolution imaging. Examples of results and some preliminary conclusions are presented in this paper. Keywords SAR; polarimetry; Arctic; surveillance; detection; recognition I. INTRODUCTION In relation to future capabilities in the Arctic region, the Danish Defence Acquisition and Logistics Organization (DALO) has carried out several test campaigns with the F-SAR system of the German Aerospace Center (DLR), which offered the possibility of exploring the performance of a highresolution, fully polarimetric SAR system with five frequency bands in the range of 400 MHz to 10 GHz [1][5]. After an initial test in Denmark in October 2014, the main test campaign was held in Greenland from late April to late May 2015 with several different test sites and test scenarios designed for investigating the use of advanced, multi-channel SAR systems for applications such as surveillance, change detection and target recognition. Fully polarimetric radar systems are still not commonly used for military applications, mainly due to added complexity and cost, but nevertheless, the potential benefits of fully polarimetric systems must be taken into due consideration for future capabilities [9]. Hence, a main objective of the test campaigns reported here has been to demonstrate and illustrate how the utilization of information carried by the polarization of the electromagnetic waves could improve the performance of imaging radar systems significantly. The test scenarios included experiments with objects hidden under snow as well as moving targets and boats near icebergs. Detailed ground truth was collected in the form of precision GPS measurements with associated photos, and aerial photos were taken during helicopter flights. Examples of results and findings are presented in this paper with a focus on techniques for visualization of multi-band polarimetric SAR imagery. Fig. 1. Test sites for F-SAR campaign in Greenland April/May TABLE I. F-SAR PRINCIPAL PARAMETERS X C S L P f [GHz] PolSAR Quad Quad Quad Quad Quad InSAR BW [MHz] power [W] rg res. [m] az res. [m] swath [km] 2 to 5, depending on altitude II. EXPERIMENTS AND TEST SCENARIOS A. F-SAR system description DLR employed the airborne F-SAR system in X-C-S-Lband and P-band configurations for the mission with technical parameters as given in Table 1. Data acquisitions were made with up to three simultaneous polarizations: X-C-L or X-S-L,

2 Fig. 2. L-band SAR image of Kangerlussuaq area around the airport. Parked aircraft can be seen in the taxiway area near the hangars. Colour coding is based on the sphere, diplane, helix decomposition as explained in section III.B. while P-band data acquisition was carried out on separate flights after reconfiguration. B. Description of Test Sites Flights with F-SAR were carried out over four test sites located at Kangerlussuaq, K-Transect, Kulusuk (Lost Squadron site nearby), Nuuk and Qeqertarsuaq. In this paper, selected examples from Kangerlussuaq and Qeqertarsuaq are shown. 1) Kangerlussuaq Calibration reflectors and man-made objects were emplaced, and detailed ground truth was collected in the form of photos, videos and precision GPS recordings. Detection of changes was demonstrated by repeated flights over a given test area, where objects were moved between flights. 2) Qeqertarsuaq, Disko Island This test area provided opportunities for collecting SAR image data of the village area, ships near ice, dogsleds, snow scooters, as well as test setups on the ice and snow cover of the Disko Island with tent, corner reflectors and buried test objects, including humans hidden in snow caves. whereby RGB (red, green, blue) images are generated using the respective components of the decompositions [9][9]. 1) Pauli decomposition [ S]= k1[ S] + k 2[ S] + k 3[ S] [ S] diplane( θ ) sphere diplane( 0 ) diplane( 45 ) = [ S] sphere cos 2θ sin 2θ sin 2θ cos 2θ 10 = 01 (1) (2) (3) k = [ k1 k k ] = 3 1 [ S + S S S 2S T ] (4) 2 2 HH VV HH VV HV III. METHODOLOGY A. Geocoding Regions of interest were selected and cropped from the original datasets. For each region of interest (ROI), polarimetric decompositions were applied, and the resulting images were geocoded based on a digital elevation model (DEM) created from interferometric X-band data collected during initial F-SAR flights at the various test sites. B. Polarimetric decompositions For the presentation of results, two coherent threecomponent decompositions are employed in this paper: conventional Pauli decomposition (HH-VV, HV, HH+VV) and Krogager sphere, diplane, helix decomposition (SDH), Fig. 3. Test area at the Lyngmark Glacier on the Disko Island with experimentation area around blue cottage indicated.

3 2) Sphere, diplane, helix decomposition [ S ] = e jϕ{e jϕ s k s [ S ] sphere + k d [ S ] diplane( θ ) + k h [ S ] helix( θ )} (5) 1 0 [ S ] sphere = 0 1 cos 2θ [ S ] diplane( θ ) = sin 2θ [ S ] helix( θ ) = 1 j 2θ e 2 (6) sin 2θ cos 2θ (7) 1 ± j ± j 1 (8) k s = S RL (9) kd = min ( S RR, S LL ) (10) kh = S RR S LL (11) ϕ = 12 (ϕ RR + ϕ LL π ) (12) θ = 14 (ϕ RR ϕ LL + π ) (13) ϕ s = ϕ RL = 12 (ϕ RR + ϕ LL ) (14) As can be seen from (9)-(14), the SDH decomposition is closely related to the components measured directly by circular polarization (or obtained by transforming from the horizontalvertical linear polarization basis to the right-left circular polarization basis). The use of these decompositions rather than a straightforward use of the measured HH, HV, VV scattering matrix elements allows for interpretations in terms of physical scattering properties. The two considered decompositions have some similarity in terms of physical scattering mechanisms. Thus, the SDH sphere component is identical to the HH+VV term of the Pauli decomposition, and the HH-VV term is representing an even-bounce scatterer, e.g., a dihedral. For a dihedral aligned horizontally or vertically, HH-VV is identical to the diplane component of the SDH decomposition, while a dihedral with an orientation angle different from 0 or 90 degrees will generate contributions to the HH-VV component as well as to the HV component. A more complex target with two or more even-bounce contributions will contribute to both the diplane and the helix component of the SDH decomposition and to HH-VV and HV of the Pauli decomposition [11]. IV. Fig. 4. SDH and Pauli decomposition images of parked aircraft at Kangerlussuaq airport. From top: X (590 MHz BW), S (300 MHz BW), L (150 MHz BW). Left column RGB: sphere, diplane, helix. Right column RGB: HH-VV, HV, HH+VV. phase information of the decompositions, which is not used for the RGB image generation. However, the separation of three components with significant physical merit facilitates the visualization and interpretation of the radar scattering properties. RESULTS A. Kangerlussuaq Images of an aircraft parked at Kangerlussuaq airport are shown in Fig. 4 for three different frequency bands and two different polarimetric decompositions. A notable difference between the two representations can be seen in some areas, which are all green in the SDH representation, but partly green and partly red in the Pauli decomposition. This indicates that the associated scattering contributions are due to even-bounce reflections from structures with some slope relative to the radar geometry. In fact, such information is also included in the B. Qeqertarsuaq The test sites at Qeqertarsuaq included an area around the harbor village of Qeqertarsuaq as well as an area on the Disko Island covered by ice and snow. A cottage in this area was used as a base for experiments with stationary and moving test objects, see Fig. 5. At this test site, we carried out change detection experiments by digging caves into the snow to the northeast of the cottage, where test objects (including persons and metallic reflectors) were present during some flights and absent during others. Likewise, two snow scooters and two dogsleds were used as both stationary and moving test objects.

4 Fig. 5. Overview of experimentation area around blue cottage. Two snow scooters and two dogsleds were used as stationary and moving test objects during flights. Snow caves were dug into for experiments with hidden objects. Two persons, a ladder made of aluminum, and two aluboxes forming a dihedral corner structure with mostly double-bounce scattering. The lower right image in Fig. 6 shows a difference map generated from two consecutive passes of the P-band system. The clear blue and red areas correspond very well with positions, where changes were made at the test site shown in Fig. 5. Notably, the difference between an empty cave and the same cave with a person present is clearly visible at P-band in spite of the rather low range resolution. Likewise, smeared and displaced signatures of the moving test objects are clearly visible. It should be noted here, that the images in Fig. 6 are not all recorded simultaneously, since the system only allowed for up to three frequencies at a time, and P-band only in singleband mode. Hence, the X-, C- and L-band images were recorded simultaneously, while the S- and P-band images were recorded during different passes. A closer look at a smaller area around the blue cottage is shown in Fig. 7, where SDH images from two consecutive passes are shown. Between the passes, several changes were made as marked in the images. As can be seen, even a rather small change like a medium-size person in or out of a snow cave is clearly visible at P-band despite the rather low range resolution, even without special processing techniques. Fig. 6. SDH images of area around the blue cottage (bright area in the lower left part of the images) at five frequency bands. Also shown is a P-band difference map based on two consecutive passes. Changes due to snow scooters, dogsledges, persons and metal objects in and out of snow caves are clearly seen. For visualization of changes, difference maps were generated based on comparing pairs of images from different flights. Further examples for the upper part of the scene in Fig. 6 are shown in Fig. 8 - Fig. 13, which include difference maps generated from different polarimetric quantities: ks, kd, kh, HH, VV, HV. Fig. 7. SDH images of a smaller area in the vicinity of the blue cottage for two consecutive passes. Location of test objects are marked by yellow frames.

5 Fig. 8. Sphere component difference map Fig. 9. Diplane component difference map Fig. 10. Helix component difference map Fig. 11. HH component difference map Fig. 12. VV component difference map Fig. 13. HV component difference map As can be seen, the different polarimetric quantities highlight different scattering characteristics, and as expected, the changes caused by removing trihedral reflectors are more pronounced in the sphere component image than in the diplane component image. However, since the trihedrals were small in terms of wavelength at P-band, significant contributions are also seen in the diplane and helix component images. Notably, the change caused by a person in the upper cave is most clearly visible in the HH image, while barely visible in the others. Fig. 14 shows a series of SAR images of an area near Qeqertarsuaq harbour, where the water was mostly covered by ice at the time of data acquisition. Based on an aerial photo (also shown in Fig. 14) taken from a helicopter on the way to the base on the Disko Island, details of the scene in Fig. 14 could be identified. Thus, as can be seen in the left side of the geocoded aerial photo, a number of boats were lined up along the edge of the ice, where melting had begun. The photo was taken the day before the acquisition of data at X-C-S-L-bands, while the P-band data acquisition took place four days later, when the melting had extended further into the ice-covered region. For comparing with the polarimetric images, Fig. 14 also includes a single-polarization image (VV) at X-band. Evidently, a scene like this contains many scattering contributions with features that cannot be exploited from images based on a single-polarization system. Furthermore, the images at different frequency bands illustrate how different characteristics can be extracted depending on the frequency band. At X-band, for example, the tracks due to snow scooters and dogsleds are clearly visible, while the tracks disappear at the lower frequencies. The images clearly show how the different frequency bands provide complementary information. At the higher frequencies, tracks in the surface from snow scooters and dogsleds are seen, while the lower frequencies pick up reflections from objects and structures below the iceand snow-covered surface. Fig. 14. SAR images at five frequency bands (based on SDH decomposition) of scene from Qeqertarsuaq ice-covered harbour area. Also shown is a singlepolarization X-band image. Lower left: geocoded aerial photo. Lower right: cropped aerial photo before geocoding.

6 V. CONCLUSIONS An advanced SAR technology demonstration campaign (DALOEX 2015) was carried out in Greenland in April/May 2015 by the F-SAR system of DLR, Germany. The test scenarios were defined to consider applications like: surveillance, detection of objects, change detection, and target recognition. In this paper, some examples of obtained results have been presented with emerging conclusions concerning the utility of fully polarimetric SAR systems in different bands. The experiments carried out during the campaign have clearly demonstrated the superiority of fully polarimetric imaging over traditional single-polarization imaging. The possibilities of detecting various objects (above and below ice and snow surface), tracks after snow scooters and dogsleds, to mention a few examples, have been demonstrated, with surprisingly good results at P-band. Examples of joint use of polarimetric decompositions for visualization and interpretation of polarimetric SAR imagery have been presented. Each of the three-component decompositions, which are widely used for polarimetric SAR imagery, consist of five parameters, while only the three magnitudes are normally used for generation of RGB images. Important target information, e.g., the orientation angle about the radar line of sight, is therefore somehow hidden in the three-component images, and methods for highlighting such features are needed in order to explore the full amount of information contained in polarimetric radar data. The different frequency bands provide complementary information. At the higher frequencies, tracks in the surface from snow scooters and dogsleds are seen, while the lower frequencies pick up reflections from objects and structures below the ice- and snow-covered surface. The dataset collected during the DALOEX campaign forms a basis for extensive analyses and sensor/technology evaluation to support recommendations for future Arctic surveillance capabilities and advice for future sensor and platform acquisitions. REFERENCES [1] E. Krogager, Results from the DALOEX 2015 campaign with F-SAR in Greenland, Proceedings of EUSAR 2018, Aachen, Germany, [2] A. Reigber, E. Krogager, M. Keller, M. Jäger, I. Hajnsek, R. Horn, The DALO-ARCTIC campaign: Multi-spectral SAR imaging of ice features in Greenland, Proc. EUSAR 2016, Hamburg, Germany, [3] M. Jäger, E. Krogager, A. Reigber, Polarimetric SAR Change Detection in Multiple Frequency Bands for Environmental Monitoring and Surveillance in Arctic Regions, Proc. EUSAR 2016, Hamburg, Germany, [4] E. Krogager, S. von Platen Rosenmunthe and J. H. Hartvigsen, Demonstration of advanced SAR for applications in the Arctic, Proceedings of EUSAR 2016, Hamburg, Germany, [5] A. Reigber, R. Scheiber, M. Jäger, P. Prats-Iraola, I. Hajnsek, T. Jagdhuber, K.P. Papathanassiou, M. Nannini, E. Aguilera, S. Baumgartner, R. Horn, A. Nottensteiner, and A. Moreira, Very-highresolution airborne synthetic aperture, Radar Imaging: Signal Processing and Applications, Proceedings of the IEEE, Vol. 101, No. 3, pp , [6] J.-S. Lee and E. Pottier, Polarimetric Radar Imaging: From Basics to Applications, CRC, [7] D. Massonnet and J.-C. Souyris, Imaging With Synthetic Aperture Radar, CRC, [8] E. Krogager, W-M. Boerner, T. Ainsworth, J-S. Lee and J. S. Verdi, Interpretation of high-resolution polarimetric SAR data using detailed ground truth information, Proc. European Conference of Synthetic Aperture Radar (EUSAR), pp , [9] E. Krogager, Polarimetry for the full story, RTO SCI Symposium on Non-Cooperative Air Target Identification Using Radar, Mannheim (April 1998), RTO MP-6, p [10] E. Krogager and Z. H. Czyż, Properties of the sphere, diplane, helix decomposition, Proc. Journées Internationales de la Polarimétrie Radar, JIPR 95, pp , Nantes, France, [11] E. Krogager, Aspects of Polarimetric Radar Imaging, Doctoral Thesis, Technical University of Denmark / Danish Defence Research Establishment, May [12] R. Keith Raney, Synthetic Aperture Imaging Radar and Moving Targets, IEEE TAES, Vol. 7, May VI. ACKNOWLEDGMENT The author would like to thank the F-SAR team of DLR for the highly professional and efficient conduct of the test campaigns under the difficult conditions in the Arctic areas. Likewise, the support and guidance from the SAR Technology Department of DLR is highly appreciated, as is the support from the Danish MoD AGFOA experimentation program, from the Joint Arctic Command in Nuuk, and from Air Group West in Kangerlussuaq. Crucial was also the support from SikuAput, Qeqertarsuaq, and the dedicated assistance from the dog leaders and snow scooter drivers, who made the 10 km rides up to the test site on the Disko Island in the snowy and foggy Saturday morning of 9th May 2015 to act as test objects for experiments with this "all-weather, day-and-night sensor system". Finally, sincere thanks are due to Mr. Stig von Platen Rosenmunthe and our student assistant, Ms. Katrine Feld, for invaluable assistance with the handling and processing of the huge amount of data from the DALOEX trials.