GPS receiver. GPS antenna. HDDT recorder. Video monitor. GPS DPA synchronisation. Other. Operating terminal. Sensor. Record unit.

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1 High Precision Georeferencing using GPS/INS and Image Matching Michael Cramer, Dirk Stallmann and Norbert Haala Institute of Photogrammetry, University of Stuttgart Geschwister-Scholl-Str. 24, Stuttgart / Germany Michael.Cramer@ifp.uni-stuttgart.de BIOGRAPHIES Michael Cramer is a research associate in the Institute of Photogrammetry. He received his diploma in surveying from the University of Stuttgart in From 1993 till 1995 he was employed in the special research group "SFB 228 { High precision navigation", mainly related to the topic attitude determination using multiantenna GPS and low-cost INS. Now heis working in the eld of GPS/INS integration for georeferencing of digital airborne and satellite three line CCD scanner. Dirk Stallmann took his Dipl. Ing. in Geodesy and Surveying Engineering from the University of Hannover, Germany, in From 1989 till 1995 he was working at the Swiss Federal Institute of Technology, Zurich, on image matching for image/object tracking, precise measurement and automatic digital terrain model generation from airborne and satellite images (SPOT, MOMS- 02). Since 1995 he is working at the University of Stuttgart on photogrammetric processing of airborne and satellite based three line CCD scanner and sensor integration. Norbert Haala received his diploma in surveying from the University of Stuttgart in He started as a research associate at the Institute for Photogrammetry as a member of the special research group "SFB 228 { High precision navigation". He has been working extensively in the eld of image reconstruction and nished his Ph. D. thesis "Building reconstruction from aerial images and DSM data" in Since 1995 he is associate professor and head of the research group "Sensor-Integration". ABSTRACT The registration and geometric rectication of airborne scanner imagery is an essential prerequisite for the processing and analysis of this type of images. The Digital Photogrammetric Assembly (DPA) is an airborne camera consisting of three pan-chromatic line arrays for stereo imaging and four line arrays for multi-spectral imaging. For georeferencing the sensor system is completed by a module consisting of a dierential GPS receiver conguration and an Inertial Navigation System (INS). Additionally, due to the along-track stereo capability of the camera error terms for position and attitude can be estimated by photogrammetric constraints utilizing ground control points and corresponding image points. In order to get a high accuracy position and attitude are determined by integrating all available information (GPS, INS and stereo image data). Within the article the geometric processing of the high precision and high resolution scanner imagery will be described and results of the performed testight in October 1996 will be presented. 1 INTRODUCTION The DPA is an integrated airborne push-broom scanning system with real time data collection capability. The fundamental idea of this system is to obtain high quality 3D and multispectral information of a scene simultaneously. In order to acquire geometric information three high resolution CCD lines are used providing panchromatic images in forward, nadir and backward direction of the ight path. The ground pixel size for these images at the ying height of approximately 2000 m above ground is in the order of 0.25 m. For multispectral purposes four CCD lines are used to acquire images of the spectral bands red, green, blue and near infrared. For georeferencing of the digital image data, a six degree of freedom strap-down INS is utilized. Additionally, a dierential GPS receiver conguration is synchronized to overcome the well known systematic INS error eects. Hence, for every scan line the fully exterior orientation parameters of position and attitude are available. More details about the georeferencing process in general are given in e. g. [8], [9]. Within this paper the algorithm for georeferencing the image data is described. In contrary to the common approach of determining the exterior orientation for the complete trajectory by using a Kalman lter starting with an initial alignment procedure, a strip-wise approach is utilized. The in-ight alignment of the INS is realized using ground control points in the three channels. By using the collinearity condition of the the osets and drift (linear rates) for the attitude angles are

2 determined in a least squares adjustment. 2 THE DPA SENSOR SYSTEM The development of the DPA sensor system started in the late eighties and was done by the Daimler{ Benz Aerospace (DASA), formerly the Messerschmitt{ Bolkow-Blohm (MBB) company. The philosophy of the system is to get single path pan-chromatic stereo coverage and multispectral coverage of the terrain. This is similar to other imaging airborne sensors like the MEIS imager [7] or the MOMS-02 sensor [1] for space applications. Originally, the camera system consists of three panchromatic CCD line arrays for the in-ight stereo imaging connected with an INS providing linear accelerations and angular rates measurements. First tests to evaluate the potential of the stereo module were done in 1992 and are published in [5]. Later, the camera was completed by the multispectral module for acquisition of multispectral images in the red, green, blue and nearinfrared band. Additionally, a dierential GPS receiver conguration was synchronized with the system. The optical part together with the sensor electronics and the INS are mounted in a Zeiss Jena SM2000 platform for stabilization of the imaging system during the ight. The components for operating the system and storing the recorded data are xed in two racks. The complete camera system is shown in gure 1. channels are using one lens and a linear CCD array of 6000 pixel each. The convergence angle is 25 between nadir and backward and forward channel, respectively. The eld of view is 37, the resulting swath width is approximately 1300 m with a ying height of 2000 m above ground. Due to the reduced focal length of the multispectral channels the eld of view of the spectral and the stereo module is the same. Stereo module Focal length Line array Pixelsize Data resolution Convergence angle Spectral range Spectral module Focal length Line array Pixelsize Data resolution Spectral range 80 mm pix/line 10 m 8 bit { 780 nm 40 mm 6000 pix/line 10 m 8 bit 440 { 525 nm 520 { 600 nm 610 { 685 nm 770 { 890 nm Table 1: Basic camera parameters GPS antenna Other Sensor INS GPS receiver GPS DPA synchronisation (optional) Sensor electronics Platform Optics 2.1 Optic module Video monitor Operating terminal Electronics unit Figure 1: DPA recording system HDDT recorder Record unit Playback unit Power supply The basic parameters of the optical part of the DPA system are given in table 1. The stereo module consist of a double lens each with three CCD lines (forward, nadir and backward view) of 6000 pixel. The linear arrays are optically buttoned providing wide-angle geometry with a width of pixel. In contrary to this, the spectral 2.2 GPS/INS components For georeferencing the recorded DPA image data the optical system is completed with a strap-down inertial navigation system of navigation grade accuracy class. The INS is connected with the imaging sensor at the hardware level. Namely, theinsraw data are recorded only in combination with image data. Therefore, INS angular rates and linear accelerations are only available for the image strips and not for the whole ight trajectory. The measurement frequency of image data and INS data are identical. The utilized strap-down six degree of freedom INS is manufactured by Sagem and consists of two Sagem GSL82 two axes dry tuned gyroscopes and three Sundstrad QA2000 accelerometers. The technical specications are given in table 2. To conrm the INS accuracies given in the calibration sheet a static data set was analyzed. The recording time was about several minutes with a data rate of 470 Hz. With known initial position and attitude the measurements are reduced by earth rotation and gravity. The remaining sensor noise can be used to estimate the expected accuracy. Additionally, rst approximations for

3 Performance Rate output Accel output Dynamic range permanent 25 =s 4 g transient 50 =s 8 g Output voltage 10 V 10 V Temperature 1 10 ;4 = C 180 ppm= C sensitivity Linearity < 0:3% < 0:3% Bandwidth > 80 Hz min > 100 Hz min Misalignment 1 10 ;3 rad 1 10 ;3 rad Noise (rms max) 5 10 ;2 =s 1 10 ;4 g deg Table 2: Technical specications of DPA INS from calibration time / s Figure 2: Attitude in X-direction (static data) Sensor Mean Noise (rms) Rates X =s =s Y =s =s Z =s =s Accel X m=s m=s 2 Y m=s m=s 2 Z m=s m=s 2 deg Table 3: INS sensor osets and noise from static data time / s Figure 3: Attitude in Y-direction (static data) 0.02 the sensor osets can be determined. The results are given in table The remaining sensor noise is in the range of 0.05 =s for the angular rates and m=s 2 for linear accelerations in horizontal directions. For 1 g accelerations (in Z-component) the noise increases signicantly. The values are slightly worse compared to the calibration sheet. This can be expected because of none ideal lab environments during data recording. deg time / s In a second step the measurements are integrated to evaluate the positioning and attitude accuracy. Before integration the original measurements are reduced by the estimated osets. In gures 2, 3 and 4 the obtained attitudes in X, Y and Z-direction are plotted. The root mean square errors (rms) of the three angles are 0:012 0:004 and 0:006 for! ' and respectively. Figure 4: Attitude in Z-direction (static data) The high frequency changes of the attitude angles shown in the gures 2{4 are caused by the remaining sensor noise. The low frequency attitude variationsare of other inuence and cannot be modeled. These low frequency

4 variations are the limiting factor for the achievable attitude accuracy. The accuracy is in the range of =s. Nevertheless, the navigation grade accuracy class of the INS is conrmed. To overcome the systematic INS error eects, a dierential GPS receiver conguration is synchronized with the INS and optics module. The spatial osets between GPS antenna, INS and imaging CCD sensors of the camera are determined with conventional terrestrial methods. The time synchronization is realized by the exchange of synchronization pulses between the dierent sensors using a PC laptop with multisensor digital I/O board. The time pulses from the DPA (and additional sensors like an standard aerial camera) are received from the digital input and recorded in internal computer time. On the other hand, time signals within distinct time intervals are sent to the GPS receiver and recorded in the external GPS time frame. Using this conguration the internal time frame can be related to the external GPS time. If no additional sensors are used in a test the DPA time pulses can be sent to the GPS receiver directly. 3 GEOREFERENCING OF IMAGE DATA Earlier test have shown that traditional GPS/INS integration methods via Kalman ltering are sucient for almost all mapping applications (mapping scales 1:5000 and smaller). Using a navigation grade INS and differential GPS (carrier phase measurement) the exterior orientation parameters can be achieved with an accuracy of 0:15 ; 0:2 m for position and 4 ; ;3 for attitude. For these tests the use of position and attitude obtained by Kalman ltering of GPS/INS data for the georeferencing of aerial images resulted in an accuracy (rms, compared to given ground control points) of 0.3 m in horizontal components and 0.5 m in height, the maximum errors did not exceed the 1 m level at a ying height of 1000 m [10]. For our application the accuracy of the georeferencing should be in the order of the used ground pixel size of 0:25 m which resulted from the ying height ofap- proximately 2000 m above ground. Additionally, dueto hardware restrictions the initial alignment of the INS body frame to the earth xed frame is only approximately available. In order to obtain this accuracy and to correct the initial alignment of the INS for each strip, GPS and INS are combined with photogrammetric techniques. For this reason, the georeferencing is divided into two steps. First, position and orientation are determined for each scan line by a GPS/INS integration. In the second step remaining oset and drift parameters are estimated for the attitude parameters to model the errors of the integrated GPS/INS processing. Therefore, photogrammetric techniques involving the collinearity and coplanarity conditions are utilized. 3.1 GPS/INS integration The mechanization of the INS angular rates and linear accelerations is done in a geocentric earth xed coordinate frame. The use of this coordinate system is straightforward, because the GPS measurements are obtained in the same frame and therefore no additional transformations are necessary. More details about the algorithm can be found in [11]. Before starting the mechanization, the INS measurements are reduced by the sensor osets which are estimated by assuming a straight ight line resulting in zero values for the mean accelerations. Additionally, at the beginning of the measurement the initial relation between the INS body frame and the local level frame is necessary. The initial position for each ight line is obtained by GPS. A rst estimation of the initial yaw angle is calculated from the GPS positions rotated to the local level frame. The initial roll angle! and pitch angle ' are assumed to be zero. Using the estimated initial alignment and sensor osets the mechanization is done, whereas the INS derived positions are updated via GPS at every GPS measurement epoch. After integration for every DPA scan line i the parameters of exterior orientation (position X i Y i Z i, attitude! i ' i i )areavailable. The positioning accuracy is mainly dependent on the accuracy of the GPS positioning. The attitudes are corrupted by a constant oset ^! 0 ^' 0 ^ 0 due to the incorrect initial alignment and the unknown misalignment between the INS body frame and the DPA image frame. Additionally, there are some remaining drift eects ^! 1 ^' 1 ^ 1 caused by remaining sensor osets. 3.2 Photogrammetric calibration In order to correct these remaining errors a photogrammetric evaluation utilizing the stereo capability of the camera has to be performed. Therefore, standard photogrammetric techniques for relative (coplanarity condition) and absolute orientation (collinearity condition) [6] can be used to determine the unknown oset parameters and time dependent drift parameters. The coplanarity condition describes the fact that pairs of homologous pointing vectors ~x i ~x j are located in one plane, or mathematically spoken, the vector triple product of the two pointing vectors and the base vector ~ b between the perspective centers X ~ 0i X ~ 0j has the value of zero. For each pair of homologous image points one coplanarity condition equation can be found: ~x i ~x j ~ b =0 (1)

5 For the collinearity condition the standard formulas can be used: x 0 = x 0 ; c r 11X + r 12 Y + r 13 Z r 31 X + r 32 Y + r 33 Z (2) 49.0 y 0 = y 0 ; c r 21X + r 22 Y + r 23 Z r 31 X + r 32 Y + r 33 Z Latitude [deg] 48.9 Testsite 4.5 km x 7 km with 48.8 X = X ; X 0 Y = Y ; Y 0 Z = Z ; Z 0 where X 0 Y 0 Z 0 coordinates of perspective center X Y Z coordinates of object point r 11 r 12 r 33 rotation matrix R(! ' ) x 0 y 0 coordinates of image point x 0 y 0 coordinates of principle point of image The equations 1 and 2 are functions of the unknown parameters ^! 0 ^' 0 ^ 0 ^! 1 ^' 1 ^ 1. For each ightlinethese parameters are estimated in a least squares adjustment approach. Additionally, for each tie point three unknown object point coordinates have to be estimated in the adjustment. The corrected attitudes ^! i ^' i ^ i can be calculated using equation 3. ^! i =! i +^! 0 +^! 1 t ^' i = ' i +^' 0 +^' 1 t (3) ^ i = i +^ 0 +^ 1 t As observations for the adjustment a number of coordinates of corresponding image points in the for-, nadir- and aft-channel have to be measured either manually or by automatic image matching techniques. The matching can be done using an intensity based approach [3]. Additionally, image coordinates of ground control points are required. A similar approach can be found in [2]. 4 THE TESTFLIGHT DESIGN For the geometric accuracy evaluation of the integrated sensor system a testight over the well surveyed test site Vaihingen/Enz (size 4:5 7 km 2 ) near Stuttgart, Germany, was carried out in October For ground control 200 points using white PVC plates or paintings with the size of 1 1 m 2 were signalized. A subset of 38 points was determined using a network of static dierential GPS baselines. To transform the obtained WGS84 coordinates into the local geodetic reference Longitude [deg] Figure 5: Testight scenario ( ) system a (7 parameter) spatial Helmert transformation was used. The transformation parameters are derived from 6 points given in both coordinate systems. The remaining ground control points are determined using traditional photogrammetric aerial triangulation. The obtained accuracy is 2 cm for the horizontal and 3 cm for the vertical components. Atwin-engined Cessna 404 Titan aircraft provided by Kirchner & Wolf Consult Company, Hildesheim was equipped with the DPA sensor system. Additionally, for photogrammetric data evaluation a Zeiss RMK-TOP wide-angle aerial camera was installed in the aircraft and synchronized with the other on-board sensors. The results from photogrammetric aerial triangulation are used to estimate the geometrical accuracy potential of the DPA. In order to allow a stable and constant alignment between the sensors both imaging sensors were rigidly mounted to the aircraft during the testight. The geodetic GPS receivers chosen for this testight are three Trimble SSE4000 receivers. Two of them are used as master stations in the test area to get redundant reference data. The remaining third receiver is installed in the aircraft. The time pulses for the synchronization of the system are recorded by this receiver. During the testight six photogrammetric strips were own in cross-pattern with an average ying height of 2000 m above ground (gure 5). The digital DPA images (40000 lines length for long strips, lines for cross strips, image scale 1:25000 (pan-chromatic)) were captured with a data rate of 235 Hz. Due to the hardware connection the number of INS measurements and the INS recording data rate are the same. The GPS observations were recorded with 1 Hz data rate. The satellite conguration during the test was quite good. Even during ight turns, the number of satellites tracked from

6 [m] east north height Image No Figure 6: Estimated positioning accuracy from inverse photogrammetry [milli deg] roll pitch yaw Image No vertical component height = 3.5 cm. For the orientation angles these values are! = 2:2 10 ;3 for the roll, ' =2:4 10 ;3 the pitch and =1:0 10 ;3 the yaw angle, respectively. It has to be pointed out that the exterior orientation parameters from aerial triangulation mentioned above are estimated values only and might be dierent from the actual true physical position and orientation. Due to the fact that these values are estimated as free unknown parameters in the bundle adjustment process they are aected by remaining systematic errors of the exterior and the inner orientation. To derive the inuence of these errors the exterior orientation is calculated using dierent parameter sets for the bundle adjustment. The inner orientation (IO) was derived from a 4 and a 8 parameter transformation. The self calibration (SC) is done with a12and a 44 additional parameter set. The dierent solutions are compared and the obtained mean dierences (rms values) in the estimated position X 0 Y 0 Z 0 and orientation! ' of the perspective centers of the camera are given in table 4. AT 1 AT 2 Dierences (rms) Pos [cm] Att [10 ;3 ] IO/SC IO/SC X 0 Y 0 Z 0! ' 4/12 4/ /44 8/ /12 8/ Table 4: Dierences in estimated exterior orientation parameters using additional parameter sets in the bundle adjustment Figure 7: Estimated attitude accuracy from inverse photogrammetry the roving receiver in the aircraft did not fall below 5. The maximum PDOP did not exceed 6. To provide reference information overall 36 photogrammetric images (west-east strips 7 images each, southnorth strips 5 images each, image scale 1:13000) with 60% forward and 30% side-overlap were captured during the test and form the photogrammetric block. These images are processed in a bundle adjustment to determine the remaining ground control point coordinates on the one hand and to obtain reference values for the parameters of exterior orientation on the other hand. In gure 6 (position) and 7 (attitude) the obtained standard deviations of the estimated orientation parameters are shown. The mean values of standard deviation for the horizontal components of the camera perspective centers are east = 7.8 cm and north = 8.0 cm, for the Depending on the chosen parameter set for the adjustment process especially the horizontal coordinates X 0 and Y 0 and the roll (!) and pitch (') angle are in- uenced. The obtained mean dierences are approximately up to 3 times larger than their theoretical standard deviations for position and 2 times larger for! and '. Hence, the positions and attitudes from inverse photogrammetry can be used as reference data with 0.2 m positioning and 5 10 ;3 attitude accuracy only. 5 TEST RESULTS 5.1 Exterior orientation The GPS data have been processed using two independent commercial software packages from Trimble (GPSurvey 2.0) and Geotronics (Geotracer 2.0). To achieve highest possible positioning accuracy double differenced phase solutions are calculated, utilizing the implemented on-the-y integer ambiguity algorithms [4].

7 Due to the dierent software packages and the reference data obtained from two master stations four dierent ight trajectories are calculated and compared. Overall, six dierent combinations between the four trajectories are possible to check for remaining positioning osets due to wrong estimated integer ambiguities. Hence, ambiguous solutions are excluded from further processing. After this, the obtained and tested GPS data are integrated with the INS data following the algorithm described in chapter 3.1. To estimate the absolute GPS/INS positioning and attitude accuracy the obtained results from GPS/INS integration are compared to the reference values from photogrammetry. Figure 8 gives the position dierences. The rms values are 0.13 cm for east, 0.15 cm for north, and 0.07 cm for height component, respectively. It has to be mentioned that these errors are mainly aected by the insucient reference values for position from bundle adjustment. Especially, the relatively low accuracy of the horizontal components deteriorates the GPS/INS results. The real GPS/INS positions are expected to be better. Strip Oset [ ] Drift [10 ;3 =s] roll pitch yaw roll pitch yaw Table 5: Remaining osets and drifts of GPS/INS attitudes before photogrammetric calibration The evaluated GPS/INS attitude accuracy is given in table 5 for all image strips. As an example in gure 9 these results are illustrated for image strip 2. The GPS/INS angles compared to the attitudes from bundle adjustment are shifted by a certain amount andthere are still remaining drift eects. During an image ight the attitudes! ' of a nominal straight ight line can vary between values of at least 4. Since the initial alignment is based on the assumption of zero attitude values this results in an oset error in that order of magnitude. Small systematic errors occur from the unknown misalignment between the INS body frame and the DPA (and photogrammetry) image frame and drift eects due to remaining gyro osets also caused by deviations from a straight ight line.nevertheless, the errors are systematic following a rst order polynomial. In order to x them the stereo capabilityof the camera is utilized (section 3.2). After linear tting the remaining dierences from GPS/INS attitudes and aerial triangulation are in the range of 5 10 ;3. [m] east north height GPS Time [sec] Figure 8: Accuracy of GPS/INS camera position [deg] roll pitch yaw GPS Time [sec] Figure 9: Accuracy of GPS/INS camera attitude before photogrammetric calibration (strip 2) 5.2 Evaluation of the point positioning accuracy To evaluate the point positioning accuracy several runs of the orientation program using dierent control point distributions, strip length and number of correction parameters are performed. The image coordinates are measured manually in the original three images. All ground control points are signalized and could be easily measured. The check points are determined by spatial intersection using the improved exterior orientation from GPS/INS and photogrammetric calibration. The accuracy derived from the check point dierences in image space is 50 to 60 m rms equivalent to 5 to 6 pixel. The corresponding accuracy in the object space is 0.5 to 1.0 m in planimetry and 2.6 m in height. These results are quite worse. The aspired accuracy of approximately 1 pixel

8 distortions the images are transformed into \approximate vertical" images in a rectication process. For the rectication the \direct method" for image rectication is used (gure 11). The images are rectied on a horizontal plane in the mean ying height above ground (Z-plane). Each pixel in the image space is projected on the Z-plane by using the exterior orientation. The resulting points are irregularly distributed in this plane and carry the grey value of the corresponding image points. The transfer to the regular grid is solved by interpolation using weighted averaging of grey values of all neighbouring points within a certain radius. The weight is chosen reciprocal to the distance between the grid point and its neighbours. If no neighbours are found around a grid point, as this is the case outside the borders of the image, a background value is assigned to this pixel. An example of the rectication is shown in gure 12. The rectication does not take into account the variations of the terrain height. Nevertheless, after this step an ortho image can be generated utilizing the same procedure by introducing the individual terrain heights of the DTM previously derived from the rectied stereo image pair. Figure 10: Planimetric (top) and height (bottom) check point dierences in image and object space is not achieved. The use of more control points and higher correction terms for the orientation parameters does not lead to a signicant better accuracy. Further analysis of the residuals in the control and check points (gure 10) shows signicant systematic errors due to insuciencies in the functional model for the orientation procedure. Original image y Rectified image y" i 1 Scanlines i 1 i i+1 i i+1 Projection centres Ground point Image point Z plane Flight path x" x x" 5.3 Image rectication Grid point The recorded images show distortions mainly caused by attitude variations. These distortions aect e. g. the stereo viewing for 3-D measurement, the image matching for automatic Digital Surface/Terrain Model (DSM/DTM) generation and the band-to-band registration of the multispectral channels. To eliminate these y" Ground point Figure 11: Image rectication

9 Further work will be done in expanding the strip-wise approach for georeferencing to a fully aerial triangulation of digital 3-CCD-line-imagery. Therefore, the neighbouring strips will be tied together by automatic point transfer. The realization of a full aerial triangulation will reduce the number of ground control points and permit an automatic self calibration of the camera. This will improve the geometric accuracy again. ACKNOWLEDGMENTS This project is funded by the German Federal Oce for Military Technology and Procurement (BWB) in Koblenz. Dr. Franz Muller (DASA) was responsible for operating the system during the ight and he provided the DPAraw data. His work is gratefully acknowledged. The authors wish to thank Mrs. Esther Hinz, Mrs. Antje Quednau, Mr. Christian Statter, Mr. Werner Schneider and Mr. Thomas Schaible for all their work in this project. REFERENCES [1] F. Ackermann. Das MOMS-02-Stereosegment- Ein hochgenaues System der digitalen Photogrammetrie. GIS - Geo-Informations-Systeme, 6:16{22, [2] J. R. Gibson. Photogrammetric Calibration of a digital Electro-Optical Stereo Imaging System. Geomatica, 48(2):95{109, [3] R.M. Haralick and L.G. Shapiro. Computer and Robot Vision, volume 2. Addison-Wesley Publishing Company, [4] R. Hatch. Instantaneous Ambiguity Resolution. In Kinematic Systems in Geodesy, Surveying and Remote Sensing, pages 299{308. Springer Verlag, September Figure 12: Image rectication, original (top) and recti- ed (bottom) image 6 CONCLUSIONS The numerical results described in this paper are only preliminary. More intensive investigations are still under way to obtain the aspired one-pixel accuracy of the georeferencing process. Nevertheless, the great potential of the DPA for airborne digital data collection has been proven. Compared to the analogue photographic image acquisition the direct recording of digital imagery has a lot of benets like the direct availability and the higher dynamic range and spectral resolution of the digital data. [5] O. Hofmann, A. Kaltenecker, and F. Muller. Das ugzeugestutzte, digitale Dreizeilenaufnahme- und Auswertesystem DPA { erste Erprobungsergebnisse. In D. Fritsch and D. Hobbie, editors, Photogrammetric Week '93, pages 97{107, Heidelberg, Herbert Wichmann Verlag. [6] K. Kraus. Photogrammetrie I. Dummler Verlag, Bonn, [7] W.D. McColl, R.A. Neville, and S.M. Till. Multidetector Electro-Optical Imaging Scanner MEIS. In Proceedings of the Eighth Canadian Symposium on Remote Sensing, pages 71{79, [8] K.P. Schwarz, M. Chapman, E. Cannon, and P. Gong. An Integrated INS/GPS Approach to the Georeferencing of Remotely Sensed Data. In Photogrammetric Engineering & Remote Sensing, volume 59, pages 1667{1674, 1993.

10 [9] K.P. Schwarz, M. Chapman, E. Cannon, P. Gong, and D. Cosandier. A precise Positioning/Attitude system in Support of Airborne Remote Sensing. In Proc. ISPRS Meeting Comm. II, pages 191{201, Ottawa, [10] J. Skaloud, M. Cramer, and K.P. Schwarz. Exterior Orientation without Ground Control. In Proc. ISPRS Congress Comm. III, pages 125{130, Wien, July [11] M. Wei and K.P. Schwarz. A Strap-down Inertial Algorithm Using an Earth-xed Cartesian Frame. In Navigation, volume 37, pages 153{167, 1990.