1. Applying Target Decomposition Algorithms on the Detection of Man Made Targets Using Polarimetric SAR University of British Columbia September, 2007 Flavio Wasniewski*, Ian Cumming

2. Objectives 1. Review the Detection of Crashed Airplanes (DCA) methodology applied by Lukowski et. al. 2. Test this methodology with a more diverse set of target clutters and types; 3. Compare its performance with available target detection algorithms; 4. Develop improvements to the methodology in order to give good detection performance to a range of target and clutter types. 2

3. Detection of Man Made Targets with Radar Polarimetry 3  High target-to-clutter ratio (not necessarily higher than in natural targets)  Dihedral scattering expected (phase information can be explored)  Polarimetric decompositions are among the most promising algorithms  Most civilian operational applications focus in ship detection

4. Detection of Crashed Airplanes (DCA) Source: Lukowski et. al., CJRS, 2004 4  Promising in-land application  Tested on airplanes and low vegetation clutter  Tail and wings usually remain intact and provide dihedrals  Can it be applied to all discrete man made targets? (will dihedrals always be present?)

5. 5 Methodology 1 (DCA)  The cross symbol is a logical “and” combining the 3 results.

6. 6 Methodology 2

7. 7 Methodology 3

8. 8 Methodology 4

9. Algorithms (1/5) – Polarimetric Whitening Filter 9  Bright pixels represent strong radar returns, but targets are obscured;  PWF reduces speckle (σ/µ) without affecting the resolution;  Target-to-clutter ratio is improved

10. 10 Algorithms (2/5) – Even Bounce Analysis  Explores the 180° phase shift between HH and VV

11. 11 Algorithms (3/5) – Cameron Decomposition  Classifies the target according to the maximum symmetric component in one of six elemental scatterers. TargetSMZ Trihedral1 Dihedral Dipole0 Cylinder0.5 Narrow Diplane -0.5 Quarter Wave i Source: Cameron, 1996

12. 12 Algorithms (4/5) – Freeman-Durden Decomposition Decomposition of backscatter into three basic scattering mechanisms:  Volume scattering: canopy scatter from a cloud of randomly oriented dipoles  Double-bounce: scattering from a dihedral  Surface scattering: Single bounce from a moderately rough surface Source: Freeman et. al.

13. 13 Algorithms (5/5) – Coherence Test  Detects coherent targets based on the degree of coherence and target-to-clutter ratio. Degree of coherence   and  are the Pauli components

14. Closing (dilation + erosion) Clustering Erasing 1 and 2-pixel detections Morphological processing 14

15. Experiments: data sets used (1) Gagetown dataset 15

16. Experiments: data sets used (2) Westham Island dataset 16

17. 17 Results – Target 21 (House Among Trees) CV-580 dataTarget and clutter (Ikonos image)

18. 18 Results – Target 21 – Methodology 1 PWF and Even Bounce

19. 19 Results – Target 21 – Methodology 1 Cameron combined to PWF and Even Bounce

20. 20 Results – Target 21 – Methodology 2

21. 21 Results – Target 21 – Methodology 3 Detection map after morphology

22. 22 Results – Target 21 – Methodology 4 Cameron + PWF + Even Bounce + Coherence TestDetection map

23. 23 Results – Target 2 (Plow)

24. 24 Results – Target 2 – Methodology 1 - Same detection results were achieved by Methodologies 2 and 4

25. 25 Results – Target 5 (Horizontal cylinders)  Man made target with no dihedral behaviour  No detections

26. 26 Results – Target 7 (House)

27. 27 Results – Target 20 (Crashed Plane in Grass) Corner reflectors Target

28. Results – Target 20 - Methodology 1 - Same detection results were achieved by Methodologies 2 and 4 28

29. Results Methodology 1Methodology 2Methodology 4 Total False Alarm count 5141 Total False Alarm Rate 210108772 Methodology 1Methodology 2Methodology 4 False Alarm count (Low Vegetation) 030 False Alarm count (High & medium Vegetation) 5111 Total Per Vegetation type 29

30. Summary Methodology 1 (DCA) detected the targets with no false alarms when clutter is low vegetation. It did present false alarms in high vegetation; Methodology 2 (Coherence Test) typically detects the target with few false alarms in both situations; Methodology 3 (Freeman-Durden decomposition) generally presented high false alarm rates in this study; Methodology 4 (DCA + Coherence Test) performs better than DCA methodology on high vegetation clutter. 30

31. Thank you