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example, SPOT 1, 2, and
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MOMS-02, IKONOS-2,
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nd inertial | (GPS/INS)
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into practical applications
\ (Digital Photogrammetry
ted by the Institute of
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
Photogrammetry, University of Stuttgart to produce 1:25,000
and 1:50,000 scales maps and automated DTM generation to
accuracies of better than 3m in 1995. The LH Systems ADS40
airborne digital sensor was developed by LH Systems Co. Ltd in
2000 and has been put on the world market. STARLABO
Cooperation designed the helicopter-mounted high resolution
TLS imaging system STARIMAGER jointly with University of
Tokyo in 2000 and have finished several test flights and
practical applications. These imaging systems use three linear
arrays mounted in the sensor focal plane to collect forward-,
nadir-, and backward-looking imagery for stereo mapping. The
concept of three linear scanners to collect stereo imagery has
been described in many literatures (Chen, 2001; ) and is
illustrated in Figure 1.
Unlike frame photography, where all pixels in the image are
exposed simultaneously, each line of TLS image is collected in a
pushbroom fashion at a different instant of time. Therefore, there
is in principle a different set of values for the six exterior
orientation elements for each line of the pushbroom scan.
Although the traditional indirect approach using ground control
points for the determination of the exterior orientation elements
of frame photographs through standard aerial triangulation
works for frame aerial photographs and spaceborne imagery,
this process if highly inefficient. This is because satellite
platforms remain relatively stable in relation to their orbital
altitude; any deviation of attitude from normal is usually minor
and systematically spread over the entire satellite scene
(Christensen et al., 1988), so mathematical sensor models are
developed to recover the time-dependent position and
orientation of the scanner. Airborne scanners on the other hand
are subject to atmospheric turbulence during their flight that can
lead to severe image distortions in the raw TLS imagery. For
airborne TLS a direct processing strategy utilizing direct
measurements of the exterior orientation provided by GPS and
INS is necessary for operational and efficient data evaluation.
Even though direct georeferencing is no must for digital frame
cameras a GPS/INS component is also included in some systems
(Toth, 1998).
The purpose of this paper is to deal with the integration of GPS,
INS, and STARIMAGER imagery for the georeferencing of a
digital airborne linear camera system with minimum ground
control. In this paper we tested STARIMAGER imagery with a
block of six strips and different number and geometric
configuration of ground control points and reported our obtained
results which could be taken as theorical reference for practical
TLS imagery triangulation and other linear imaging system
imagery geo-referencing process.
2 Combined Bundle Adjustment with GPS/IMU for
STARIMAGER
The STARIMAGER is equipped with a GPS/IMU system to
record the position and attitude of each image line during the
flight. However, like other frame sensor equipped with
GPS/IMU, the use of GPS and IMU for line sensor also requires
that certain measures be taken before and after the flight because
the positions and orientations from GPS/IMU do not refer to the
perspective center of the imaging sensor directly. Caused by
translational and rotational offsets, the GPS antenna and the
center of the inertial system are displaced from the camera.
Additionally, the attitudes from GPS/IMU are calculated from
the rotation of the IMU body frame defined by the IMU sensor
axes to the local level frame. The IMU axes do not coincide with
the image coordinate frame. The translational offsets between
GPS antenna and perspective center of camera can be
determined using conventional terrestrial surveying methods
after installation of the system in the aircraft used for the
imaging flight. The rotational offsets between the IMU sensor
axes and the camera coordinate system cannot be observed via
conventional survey methods. Therefore, these rotational offset
or misalignment angles between the IMU and camera system
have to be determined with triangulation using a small number
of tie and control points similar to conventional aerial frame
camera. In addition to these offsets and misalignments, some
systematic errors from GPS/IMU such as drifts of IMU should
be considered in triangulation. The primary focus of this section
is to present mathematical models used in triangulation of
STARIMAGER to deal with the systematic errors from
GPS/IMU observing data. Therefore, we will first describe the
error sources in GPS/IMU and then give two algorithms to
remove the systematic offsets for obtaining accurate exterior
orientation parameters for STARIMAGER imagery.
2.1 GPS/IMU data process
The GPS/IMU data process is an important step towards high
quality imagery and accurate measurements derived from it. The
timing of IMU recording, GPS recording and CCD line
recording must be done using a synchronized clock. This allows
the precise registration of each data-recording event. Due to
different sampling frequencies of GPS/IMU, a special software
was developed to post-process their original data including GSP
data re-sampling according to image line record and coordinate
system conversion.
As most tests and applications by integrating GPS/IMU systems
for geo-reference of image data, the positions and attitudes from
GPS/IMU do not refer to the perspective center of the imaging
sensor directly (Chen ef al., 2001; Lee et al., 2000). Caused by
translation and rotation offsets, the GPS antenna and the center
of the IMU are displaced from the camera. Additionally, the
attitudes from GPS/IMU are calculated from the rotation of the
IMU body frame defined by the IMU sensor axes to the local
level frame. The IMU axes do not coincide with the image
coordinate frame. These offsets have to be taken into account
before applying the orientations for the georeferencing of the
imagery. The translation offsets are determined using
conversional terrestrial surveying methods after installation of
the system in the satellite and aircraft used for the photo flights.
The rotation alignments between IMU and camera coordinate
system cannot be observed via conventional surveying methods.
Additionally, there are some drift errors caused by remaining
sensor offsets. Therefore, these alignments and drift errors have
to be determined with in-flight calibration using a small number
ground tie and control points. In next subsection two methods
are introduced to determine the offset of GPS, alignments and
drift errors of IMU for high accuracy positions and attitudes of
images.
2.2 Generalized Bundle Adjustment
To relate the image coordinates (x, y) of one point to its mapping
coordinates (X,Y, Z), the following collinear equations are used:
X XN X AX
Y= Yn + R(ON» PN>ÆN YAR cam y + AY ) (1)
Zl iz. =f] [AZ
where, (Xn, Yu, Zw, On, Qu, Kw) are the exterior orientation
parameters of the N" image line on which the image point in the
mapping coordinate, and obtained from GSP and IMU
observation values by removing the influence of GPS offsets,
IMU alignments and drift errors; R(Ow, On, Kn) is rotation
matrix of IMU to mapping coordinate system; A is scaling factor
from image to ground; R.,, is rotation matrix of camera to
satellite fixed coordinate system and the angles can be obtained
from table 1 for PRISM; (AX, AY, AZ) are offsets between GPS
antenna and perspective center of camera in satellite coordinate
system and can be obtained from the NASDA, Japan; fis focal