In-Orbit Geometric Calibration
Without Accurate Ground Control Data
Yonghua Jiang, Guo Zhang, Tong Wang, Deren Li, and Yanbin Zhao
Abstract
In-orbit geometric calibration is a key technology for improv-
ing the geometric positioning accuracy of satellites. Con-
ventional geometric calibration, which uses high-accuracy
ground control data to accurately calibrate the orientation
parameters of a satellite, heavily relies on the control data of
the calibration fields and may not be applicable in emergen-
cies where urgent and accurate positioning is needed. The
constant calibration of satellites is also difficult owing to the
lack of permanent calibration fields. This paper presents a
geometric cross-calibration method for the rapid and accu-
rate calibration of satellites. The conjugate points from the
multitemporal images of one satellite or multi-satellite images
are first automatically extracted; then, the interior orienta-
tion parameters of the satellite requiring calibration can be
precisely recovered according to the positioning consistency
constraint of the conjugate points. In contrast to the conven-
tional method, the proposed method can accurately calibrate
the orientation parameters without using high-accuracy
control data of the calibration fields. Therefore, the proposed
method aids in the constant calibration of satellites to ensure
the positioning accuracy, even without sufficient permanent
calibration fields. The multitemporal images of the Yaogan-4
satellite and the images of the ZY3-01 and ZY02C satellites
were considered for verifying this method. Finally, accuracies
of approximately 0.7 and 0.6 pixels were achieved by the pro-
posed and conventional methods, respectively. The difference
between the two methods was only approximately 0.1 pixels,
demonstrating that the proposed method can achieve a cali-
bration accuracy as high as that achieved by the conventional
method, even without the use of high-accuracy control data.
Introduction
Conventional geometric calibration uses high-accuracy ground
control data to calibrate the orientation parameters of a satel-
lite. It plays an important role in improving the geometric
accuracy of satellite images. Images of the calibration fields
are collected to complete the geometric calibration once the
satellite is launched. At present, the conventional geometric
calibration method is sophisticated and has been fully vali-
dated. For example, the biases between the instrument and at-
titude and orbit control subsystem (
AOCS
) reference frames of
the SPOT-5 satellite were determined through exterior calibra-
tion; the interior orientation was calibrated using a five-degree
polynomial (Valorge
et al
., 2003; Breton
et al
., 2002). After
on-orbit geometric calibration by using globally distributed
calibration fields, the planimetric and elevation accuracies of
up to 50 and 15 m (root mean square,
RMS
), respectively, were
achieved for stereo imagery without ground control points
(
GCPs
) (Bouillon
et al
., 2003). The interlock angles and field
angle maps for the Ikonos and GeoEye satellites were periodi-
cally calibrated using the calibration fields located in Denver
and Lunar Lake. Without
GCPs
, the planimetric and eleva-
tion accuracies of Ikonos are obtained as 12 and 10 m (
RMS
),
respectively (Dial
et al
., 2003; Grodecki and Lutes, 2005;
Grodecki and Dial, 2001; Grodecki and Dial, 2002), whereas
the planimetric accuracy of GeoEye is better than 3 m (
RMS
)
(Mulawa, 2011; Crespi
et al
., 2010; Aguilar
et
al., 2013). The
on-orbit geometric calibration of the Orbview-3 satellite is
based on a mathematical model and estimate of the calibration
parameters, and it is incorporated into rigorous and flexible
self-calibration triangulation. Orbview-3 achieved a planimet-
ric accuracy of 7.1 m and an elevation accuracy of 9.1 m (
RMS
)
(Mulawa, 2004). Systematic on-orbit calibration was conduct-
ed for the panchromatic remote-sensing instrument for stereo
mapping (
PRISM
) of the Advanced Land Observing Satellite
(
ALOS
) that included the exterior orientation, interior charge-
coupled device (
CCD
) alignment, and sensor-alignment trend
calibration. The planimetric and elevation accuracies without
GCPs
are better than 8 and 10 m (
RMS
), respectively (Tadono
et
al
., 2004; Takaku and Tadono, 2009; Tadono
et al
., 2012).
As conventional geometric calibration depends on high-ac-
curacy control data, it requires a satellite to scan the calibra-
tion fields before conducting calibration; thus, the timeliness
of the conventional method is restricted by the quantity and
distribution of the permanent calibration fields. For example,
there are only three permanent geometric calibration fields
located at Henan, Tianjin, and Taiyuan in China for calibrat-
ing Chinese satellites. A long time is required for a majority
of Chinese satellites to acquire cloudless images covering the
calibration fields for the first on-orbit geometric calibration
after launch. For example, two months were required for the
OVS-1A/1B satellites, which are two commercial microsatel-
lites launched on 15 June 2017 in China, to acquire cloudless
images covering the calibration fields for their first calibra-
tion. Further, the lack of immediate geometric calibration
resulted in a basic image product with poor geometric quality
during those two months. Moreover, conventional methods
cannot be applied when geometric calibration should be
accomplished as soon as a satellite is launched (e.g., for a
battlefield) owing to time delays in the acquisition of cloud-
less images covering calibration fields. In addition, satellites
should be constantly calibrated; it is very difficult to regularly
obtain cloudless images covering calibration fields, consider-
ing the quantity, distribution, and climate of the calibration
fields. As a result, changes in the orientation parameters can-
not be calibrated in time.
Yonghua Jiang is with the School of Remote Sensing and
Information Engineering of Wuhan University. Guo Zhang,
Tong Wang, and Deren Li are with the State Key Laboratory of
Information Engineering in Surveying, Mapping and Remote
Sensing of Wuhan University (
).
Yanbin Zhao is with the Shanghai Institute of Satellite
Engineering.
Photogrammetric Engineering & Remote Sensing
Vol. 84, No. 8, August 2018, pp. 485–493.
0099-1112/18/485–493
© 2018 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.84.8.485
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
August 2018
485
