MODELLING ORIENTATION PARAMETERS OF SENSOR PLATFORMS 
Joachim Lindenberger 
Institute of Photogrammetry 
Stuttgart University 
Keplerstr.11 7000 Stuttgart 1 
Fed. Rep. of Germany 
Commission I / 3 
1. Introduction 
Recent advances in photogrammetry may be characterized by the 
introduction of computer technology into all photogrammetric 
procedures. The first link in such procedures, the primary data 
acquisition, plays an important role in this development, 
because the transformation of a classical photography into a 
computer readable format is a time-consuming and costly pro- 
cess. For this reason the substitution of the photo-chemical 
layer by photo-electrical sensors is the subject of current 
research. The three-line scanner and the airborne laser pro- 
filing system are two typical examples of the new sensor 
technologies which are mentioned here as the background to the 
studies presented in this paper. 
Comparing modern scanners with conventional photogrammetry the 
main principles become obvious : the scanners provide less 
information per exposure, which must be compensated by a higher 
exposure rate. In consequence the exterior orientation para- 
meters of the scanner platform must be determined with a higher 
rate. Closely connected to this point is the problem of a weak 
geometry of the scanner data. Single spot laser scanning repre- 
sents an extreme. When only a single measurement is executed at 
every point of time, no geometric redundancy is obtained. Then 
the determination of the exterior orientation parameters is not 
possible in the conventional, indirect manner with the help of 
terrestrial control points. In this case the exterior orienta- 
tion parameters must be directly measured by additional devices 
with a sufficient accuracy. These brief arguments explain why 
the direct measurement of the exterior orientation parameters 
of a modern sensor platform and their consideration in the 
whole evaluation process is indispensable. 
This paper presents a mathematical model describing the dynamic 
and stochastical properties of any time-dependent parameter. 
The evaluation of measured data takes full advantage of this 
model for the solution of a series of problems such as : sto- 
chastical description of the measurement process, filtering and 
smoothing of observations, detection of gross measurement 
errors, stochastical description of the filtered data. To sum- 
marize, the dynamic modelling of measured exterior orientation 
parameters provides filtered data with their stochastic proper- 
ties for input into further evaluations of sensor data. 
The measured orientation parameters represent a trajectory of 
the sensor platform, which is disturbed by the observation 
errors. As the observation errors are unknown, we are unable to 
reconstruct the true track of the sensor platform. An approach 
to the true movement will be found by the introduction of a 
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