Proceedings International Workshop on Mobile Mapping Technology

li, rongxing

Bibliographic data

Monograph

Persistent identifier:: 856671290

Author:: Li, Rongxing

Title:: Proceedings International Workshop on Mobile Mapping Technology

Sub title:: April 21 - 23, 1999, Bangkok, Thailand

Scope:: 1 Online-Ressource (Getr. Zählung [ca. 400 Seiten])

Year of publication:: 1999

Place of publication:: London

Publisher of the original:: RICS Books

Identifier (digital):: 856671290

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: [Session 4: Sensor Integration and Calibration]

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: The Calibration of Imaging Sensors Integrated into a Rapid Route Mapping System. C. S. Fraser, A. M. Judd.

Document type:: Monograph

Structure type:: Chapter

4-1-5 3.4 Self-Calibration Model The additional parameter model for each of the two CCD cameras was as follows: Ax = - x p - (x/c) 5c + K] x r 2 + aix (1) Ay = - y P - (y/c) 5c + K! y r 2 where 5c is the correction to the estimate of principal distance, c, Ki is a coefficient of radial distortion, ai is the affinity term relating to differential scaling between the x and y image coordinates, x p and y p are the principal point coordinates, and r is the radial distance. Previous calibrations of the two Pulnix cameras had established that the radial distortion followed a near- cubic profile (hence the inclusion of K t only) and the level of decentering distortion was insignificant considering the degree of metric accuracy required. The presence of the affinity term aj was to prove problematic, as anticipated, especially in regard to the high projective coupling that existed between this parameter and the coordinates (x p , y p ) of the principal point. Even in instances when this term was suppressed, the recovery of interior orientation elements was quite weak. As a consequence, two basic self-calibration models were examined, one as represented by Eq. 1 and the other comprising principal distance (5c) and radial distortion (KO terms only. In the latter case, a^ x p and y p were suppressed to zero, with the image coordinate reference system being assumed to have its origin at the centre of the CCD array. Although this was unlikely to be the case in reality, the mildly convergent geometry of the two cameras offered the possibility of a significant level of projective absorption in the EO of errors arising from an erroneous interior orientation. Self-calibrating bundle adjustments for the 2-camera, 24-image, 225-point network were performed for each additional parameter model, using both free-network datum constraints (no explicit control points) and a control configuration of 22 object target points. In terms of object space triangulation accuracy, all four adjustments yielded essentially the same results. Over 200 ground checkpoints were available and in all cases the RMS coordinate discrepancies were within a centimetre or so of S x = 0.15m, S Y = 0.17m and S z (vertical) = 0.16m. While this accuracy is somewhat less than the design precision of ct X yz < 0.1m, the degradation was anticipated given both physical circumstances of the imaging configuration and concerns about the metric integrity of the analog-to-digital conversion of the SVHS video data. An RMS error of image coordinate residuals of approximately 5 pm was obtained in all four adjustments. In terms of the EO, the approaches of free-network and absolute ground control yielded basically the same solutions for camera position (X C ,Y C ,Z C ) and orientation (to, tp, k). This was understandable given that the preliminary object point coordinates employed in the inner-constraint adjustment were in fact the ‘true’ ground coordinates. 4 STEREO OBJECT POINT DETERMINATION As a result of the photogrammetric calibration process, the EO of each of the two CCD cameras was established with respect to the desired geodetic reference system. Aircraft position and attitude are also available at each exposure via the on-board kinematic GPS system coupled with the inertial positioning sensors. The nominally constant offset of position and orientation between the aircraft and the stereo camera set up was thus obtained and could be applied to determine the absolute object space coordinates of triangulated image features. This followed a two-stage process. In the first step the object space coordinates are determined with respect to the ‘relatively oriented’ stereo cameras. The final ground coordinate values are then obtained in a second step via a similarity transformation which takes into account the position and orientation measured by the onboard GPS/inertial system. It must be recalled that within the camera self-calibration network there was typically a dozen or more imaging rays to each target point. Routine application of RCAMS, on the other hand, involves only 2-ray intersection, often to features where it is difficult to precisely measure the corresponding coordinates of homologous image points. Coupled with this accuracy issue is the metric quality of the SVHS video imagery and the fact that the final EO cannot be assumed to be ‘fixed’ due to aircraft wing flexure and subsequent camera instability. A practical, analytical pre-analysis of object point intersection precision is therefore precluded to a large extent, for it could give only a vague indication of accuracy in the presence of such systematic error influences on the photogrammetric triangulation process. For the powerline mapping project, field accuracy checks were essentially the only feasible means to gain a reasonable estimate of the net impact of all error sources on the stereo triangulation process. Some 50 or more accuracy checks were performed on both powerline features (mainly pole locations) and adjacent trigonometrical survey markers. Positional errors were found to range up to 3.5m, with the achieved RMS positional accuracy (absolute position) of RCAMS being close to lm. This was consistent with the level of accuracy sought by the power company sponsoring the work. 5 PRACTICAL RCAMS APPLICATION In the period following the field calibration process described, the airborne RCAMS was employed for ‘vegetation mapping’ of some 2300 km of 66 kv powerlines in the State of Victoria. The survey involved the positioning of 15,000 poles and the recording of countless instances of vegetation encroachment into the inspection and clearance space around the powerlines. This information is critical for fire risk assessment. The task

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