Ship Detection with COSMO-SkyMed PingPong Data

Transcription

1 Ship Detection with COSMO-SkyMed PingPong Data Armando Marino (1) and Pasquale Iervolino (2) (1) The Open University, Engineering and Innovation, Milton Keynes, UK (2) Surrey University, Surrey Space Centre, Guilford, UK CORSAIR Catapult, 28 Feb 2018

2 Outline Depolarisation Anomaly Detector(DePolAD) Algorithm Physical Interpretation Results Conclusions -2-

3 Algorithm -3-

4 Scattering from ships

5 Scattering from icebergs Multiple reflections Surface scattering

6 Depolarisation Anomaly Detector (DePolAD) This new algorithm was successfully used to detection icebergs. It is based on the idea that an iceberg will produce an anomaly in the volume scattering and multiple reflections. It only needs dual pol detected images. Perfect for PING-PONG! Λ = HV 2 2 test HH HV 2 train train The detectorλis large if: HV increases between the small and large window If the ratio HV/HH increases between the small and large window. Both components are indicators of volume scattering. Armando Marino, Wolfgang Dierking and Christine Wesche -6- (2016), A Depolarization Ratio Anomaly Detector to Identify Icebergs in Sea Ice Using Dual-Polarization SAR Images, IEEE TGRS, 54(9), Sep. 2016

7 Implementation It can deal with targets embedded in sea ice. Differentiate between the targets based on anomalies in volume scattering and multiple reflections Training window Test window -7-

8 Physical interpretation Λ = ρ ring R 1+ c + crhv 1 1 ρ ρ tot : cross-over-co polarization ratio, or depolarisation ratio R: ratio between in the test window over the ring window RHV: ratio between HV intensity in the test window over the ring window c: ratio between number of samples in the total area over the test area If the target does not change between ring and test, than Λ is zero 1+ c Λ homogeneous = ρ ρ = 0 1+ c1 If the volume increases between ring and test, than Λ is positive and large Rρ and RHV will be very large Rρ, RHV If the volume decreases between ring and test, than Λ is negative 1+ c lim lim Λ = ρring ρtot = ρtot Rρ, RHV c 1+ c Λ = ρring ρtot = 0 + c0

9 Intensity DePolAD (idepolad) The detector DePolAD is normalised. In some situations it may be better to work with not normalised distances. We can use DePolAD to obtain an intensity image with enhanced contrast icebergs vs sea-ice and use this as the distance I Λ HV 2 2 HV test train = 2 HH train HV 2 test If there is an increase of volume the pixels will be multiplied by a large number. If it is homogeneous or there is a decrease, the pixel is multiplied by a small number. -9-

10 Contrast enhancement and targets: Sentinel-1 HV intensity: iceberg Contrast enhanced HV intensity -10-

11 Clutter histogram: Sentinel-1 HV intensity: no iceberg Contrast enhanced HV intensity -11-

12 Clutter histogram of idepolad Real data Real data Fitted exponential It passes the Chi Square and 2 samples Kolmogorov-Smirnov tests, but the tails of the histogram seems heavier. -12-

13 Clutter Statistics From the data it can be observed that the data fits the exponential distribution Even though there may be problems with heavier tails A Cell Averaging Constant False Alarm Rate (CA-CFAR) can be applied This is if we consider only the positive values P ( T ) f T σ σ σ x x 1 = e dx = e = e T σ ( ) T = log P σ = f σ We calculate the mean only of the positive values. It is like we apply a pre-classification of the idepolad f T -13-

14 Results -14-

15 Dataset used HH/HV PINGPONG Cosmo SkyMed images 10 images were acquired under the CORSAIR call of opportunity Geographical area: North Sea, near the harbour of Rotterdam. This is one of the busiest harbours During the months of October and November

16 8 November 2016 COSMO-SkyMed Product - ASI 2016 processed under license from ASI AgenziaSpazialeItaliana. All rights reserved. Distributed by e-geos -16-

17 16 November 2016 COSMO-SkyMed Product - ASI 2016 processed under license from ASI AgenziaSpazialeItaliana. All rights reserved. Distributed by e-geos -17-

18 Conclusions A new detector (idepolad) designed for iceberg detection embedded in sea ice was tested for ship detection. idepolad is a distance focused on enhancing anomalies in the volume scattering and multiple reflection. The algorithm was tested with HH/HV PINGPONG Cosmo SkyMed images. The algorithm seems to reject the heterogeneous clutter properly. 18

19 Thank you very much for this opportunity. -19-