Terrafirma Persistent Scatterer Processing Validation

Transcription

1 Terrafirma Persistent Scatterer Processing Validation Nico Adam (1), Alessandro Parizzi (1), Michael Eineder (1), Michele Crosetto () (1) Remote Sensing Technology Institute () Institute of Geomatics

2 Signal and Noise Flow radar Focus CR signal clutter noise Focus : Focus SAR focussing (CEOS test)?performance + Estimator E{σ defo (γ)} bias InSAR : InSAR Coregistration Interferometric phase (extraction) priority PS h update v displacement Linear LOS displacement DEM update PS detection PS stability estimation (D A,SCR) PS density Misdetection by sidelobes Temporal limited PS APS Relative to absolute conversion Higher order PS Scene calibration Folie

3 DLR Amsterdam ASAR ±4 mm/year Folie 3 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

4 DLR Alkmaar ERS ±4 mm/year Folie 4 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

5 DLR Alkmaar ASAR ±4 mm/year Folie 5 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

6 Data Selection Test for suitability of the baseline-time distribution Pre-screening of the data Determine reference scene free of artefacts moderate Doppler frequency moderate APS contribution Defined processing areas Example data for cropping Folie 6

7 Check for Correct Input Data Phase Offset Test Coregistration Check Folie 7

8 DLR Sidelobe Risk Map Amsterdam ASAR Folie 8 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

9 OSP Misdetection Sidelobe Risk 0.4: 4.% 0.6: 0.5% 0.8: 0.08% Folie 9

10 One or Two Dominant Point Scatterers standard PS estimation fails PS density reduces 100 m 8 m 56 m LOS Folie 10

11 Principle of Two Scatterer Detection Two models for amplitude fading depending on baseline sin( B Δ + ϕ) i = a B Δ + ϕ ( B Δ + Δϕ) i = a + a + a a cos h Example: Folie 11

12 DLR Risk Map for Two Scatterers Inside of a single Resolution Cell Tested scatterers Nearly all to have full overlap with OSP Folie 1

13 DLR: Risk Map for Two Scatterers Inside of Resolution Cell 3956 out of % of used PS All OSPs ca. 1% Folie 13 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

14 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 14

15 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 15

16 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 16

17 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 17

18 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 18

19 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 19

20 DLR OSP Amsterdam ASAR deformation scatter plot: coherence Folie 0

21 DLR OSP Amsterdam ASAR deformation std. deviation depending on coherence σ=0.40 mm/year σ=0.35 mm/year coh: err: Folie 1

22 Typically best measured Deformation Error Best available PS with γ = 0.96 are expected to have a 0.35 mm/year standard deviation (two systems) σ best =0.35 mm/year Relative measurement: = 0.5 mm/year Folie

23 Theoretical Limit of Deformation Error PS with γ = 1.0 are expected to have a 0.3 mm/year standard deviation (two systems) σ lim =0.3 mm/year Relative measurement: = 0.1mm/year Folie 3

24 Absolute Deformation std. Deviation σ defo = N free σ ϕ S INSAR measured S = N = N free free k k Var ΔT 1 { T } i theory Folie 4

25 Corrected Absolute Deformation std. Deviation ( γ ) σ σ PSI = σ + defo floor σ floor = σ + σ + σ + σ K radar focus = 0.1 [ mm / year] coreg approx Folie 5

26 Interpretation of Accuracy Estimates PU 0.5 mm/y is the practically achievable deformation precision 0.5 mm/y is the standard deviation of the slope of the fitted line 0.5 mm 1 year std. dev. of slope uncertainty: 0.5 mm/y The deviation of single points can be arbitrarily, it depends on the actual SCR coregistration f DC APS compensation Folie 6

27 Expected Precision for Topography F. Rocca: σ h x = 8.77 N Amsterdam ASAR Alkmaar ASAR Alkmaar ERS DLR: N σ σ h = N N b j j APS, SCR ( ) N b x measured j j Folie 7

28 DLR s Work Quality of estimation varies in the test site (e.g. SCR of PS) Actual estimation performance Measured for typical scatterers Predicted for optimal scatterer Derived and compared with theory Introduction of two contrary concepts: 1. Detection:. Measurement: For spatial visualisations Requires high PS density Allows the use of low quality scatterers For time series visualisation Allows the use of best quality scatterers only Folie 8

29 DLR Amsterdam ASAR ±4 mm/year 1 Folie 9 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

30 DLR Alkmaar ERS ±4 mm/year 1 Folie 30 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

31 DLR Alkmaar ASAR ±4 mm/year 1 Folie 31 Institut für Methodik der Fernerkundung Deutsches Fernerkundungsdatenzentrum Remote bzw. Sensing Technology Institute

32 Geocoding by Christian Minet Folie 3

33 Geocoding by Christian Minet Folie 33