Vorstellung eines photogrammetrischen Kamerasystems für UAVs mit hochgenauer GNSS/INS Information für standardisierte Verarbeitungsverfahren

Transcription

1 Vorstellung eines photogrammetrischen Kamerasystems für UAVs mit hochgenauer GNSS/INS Information für standardisierte Verarbeitungsverfahren T. Kraft a, M. Geßner a, H. Meißner a, H. J. Przybilla b, M. Gerke c a Institute of Optical Sensor Systems, German Aerospace Center (DLR), Berlin, Germany b Department of Geodesy, University of Applied Sciences, Bochum, Germany c ITC, University of Twente, 7500 AE Enschede, Netherlands

2 Slide 2 Institute of Optical Sensor Systems, DLR Berlin

3 Slide 3 Institute of Optical Sensor Systems, DLR Berlin

4 Slide 4 MACS - Modular Airborne Camera System MACS HALE MACS Jet MACS RT MACS TumbleCam MACS Micro Precise modelling of mountainous regions Rapid mapping using Jet Aircrafts Real-Time Mapping High-resolution 3D-models of urban areas Lightweight mapping solution for RPAS HALE Aircraft Jet Aircraft Powered Glider Mini RPAS Micro RPAS

5 Slide 5 Concept of MACS-Micro PC104 Embedded PC GNSS/IMU Industrial Camera

6 Slide 6 Sensor selection for MACS-Micro Camera Module Sensor Resolution Pixel Pitch Mount Weight SVS EVO 8051 CCD 3296x2472 5,5µm MFT 180g SVS EVO CMOS 4000x3000 4,7µm MFT 180g SVS HR CCD 4864x3232 7,4µm M58 320g Ximea CMV20000 CMOS 5120x3840 6,4µm M58 175g SVS HR CCD 6576x4384 5,5µm M58 320g IGN uses CMOSIS CMV20000 chip for their CamLight Camera

7 Slide 7 Current Prototype Module SVS EVO (global shutter) with APO Xenoplan f2.0/24 (fixed to f4.0) Weight [g] 320 Novatel L1/L2 GNSS receiver 110 Novatel L1/L2 GNSS Antenna 130 Sensonor STIM300 IMU 80 PC104 Embedded PC 350 Stabilized Gimbal 250 Payload Bay 160 Power Management and Cabling 220 Total 1620

8 Slide 9 Geometric Calibration Pre- and Post-Flight Calibration - Calibration target of Beuth University of Applied Sciences, Berlin - 9 different locations with different distances, line of sights and height levels - 4 images with 4 different rotations (0, 90, 180, 270 ) per location - Pre-flight: Post-flight: Software: Technet Pictran

9 Slide 10 Geometric Calibration Pre-flight Post-flight Diff Diff Parameter value value (pre/post) in pixel c K [mm] 24, , x H [mm] y H [mm] R 0 [mm] 7,0781 7, Pre-flight Post-flight Diff Parameter value value (pre/post) K E E-04-4,700E-08 K E E-07 5,480E-10 P 1-6,251E-06-7,627E-06 1,376E-06 P 2 1,450E-05 1,576E-05-1,256E-06 0,001 0,0009 RMS Pre-flight [mm] RMS Post-flight [mm] 4,00E-07 3,50E-07 3,00E-07 0,0008 2,50E-07 2,00E-07 0,0007 1,50E-07 0,0006 0,0005 xh yh ck 1,00E-07 5,01E-08 1,00E-10 RMS Pre-flight RMS Post-flight K1 K2 P1 P2

10 Slide 11 Geometric Calibration Focal length 24,220 Long term stability (over weeks) [mm] 24,215 ck - Additional Calibration target of Bochum University of Applied Sciences 24, Parameter Target Berlin Berlin Bochum Bochum Principal point Software Pictran Pictran Aicon Aicon 0,100 c K [mm] x H [mm] y H [mm] R 0 [mm] K E E E E-04 [mm] 0,050 0,000-0,050-0, XH YH K E E E E-07 P E E E E-05 P E E E E-06-0,150-0,200

11 Slide 12 Geometric Calibration 50 Radial symmetric distortion [µm] Pre-Flight Post-Flight

12 Slide 13 Radiometric Calibration Dark Signal Non-Uniformity (DSNU) - Ambient temperature of approx. 20 C - 5 images per exposure time (200us, 400us, 800us and 1600us) - AD converter offset = 358DN (standard deviation of 224DN) Photo Response Non-Uniformity (PRNU) - Custom-built natural light LED flat field ( - Color rendering index level (CRI) of 98 - Color temperature of 5000 Kelvin - 5 images per exposure time (100us, 250us, 500us, 1000us and 1500us)

13 Slide 14 Image Acquisition Test Area - Berlin Campus of DLR (80x70m) Ground Control Points - 39 GCP s - StdDev of 3mm in XY and 2mm in Z Flight Configuration - Flight pattern cross - Overlap in flight direction 90% - Overlap across flight direction 75% - Ground sampling distance (GSD) 1.1cm - Height above ground 55m

14 Slide 15 Image Acquisition Date and Time Weather Exposure Time Images taken GSD :50 p.m. Cloudy 1500us 342 (155 used for AT) 1.6cm

15 Slide 16 Traditional Photogrammetric Workflow - Image Post-Processing (DSNU, PRNU, Debayering) - GNSS/INS Post-Processing (SAPOS, forward and backward calcuation) - Aerial Triangulation (AT) of 155 images (with 7 control points) MIPPS Inertial Explorer Match-AT

16 Slide 17 Result of AT (7 control points / 32 check points) Observation Standard deviation a-priori GNSS X = Y = Z = 0.02m IMU omega = phi = kappa = Standard deviation a-posteriori (RMS) X = 0.016m Y = 0.018m Z = 0.009m o = p = k = Automatic points (image) x = y = 1µm x = y = 0.6 µm Control points (image) x = y = 1µm Control points (7) Check points (32) XY = 0.007m Z = 0.005m XY = 0.007m Z = 0.005m x y = 0.7µm = 0.6µm XY = 0.013m (0.8 GSD) Z = 0.007m (0.4 GSD) XY = 0.011m (0.7 GSD) Z = 0.005m (0.3 GSD) Sigma naught 0.6µm (0.1 GSD)

17 Slide 18 Conclusion - Introduced an modular airborne camera for RPAS - Verified geometric stability with a pre- and post-flight-calibration - Did a test flight with an RPAS less 5kg MTOW - Aerial images can be processed with proven standard software for aerial photogrammetry MACS-Micro is applicable to RPAS photogrammetry - Result s of AT reaches a precision of conventional terrestrial GNSS surveys - CMOS sensor shows an increased sensor noise in low illuminated areas - Investigate suitability for object reconstruction - Further validation flights

18 Slide 19 Any questions? German Aerospace Center (DLR) Institute of Optical Sensor Systems (OS) Department for Sensor Concepts and Applications Thomas Kraft

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