The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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Figure 2: IG’s PRS navigation-orientation Control Unit based 
on the PC 104 architecture (~ 13 x 20 x 18 cm3, ~ 2 kg). 
4. ON SENSOR NAVIGATION, CONTROL, 
ORIENTATION AND CALIBRATION IN UAS-BASED 
PRS 
Sensor navigation is the real-time determination of a sensor’s 
orientation elements, usually the position of the origin of the 
sensor [instrumental] reference frame and the attitude of this 
frame. Sensor control can be regarded as a specialized mission 
control task; it refers to the operation of the sensor (switch on, 
stabilization, heading correction, triggering, etc.) according to a 
given sensor mission plan and with the help of the sensor 
navigation data. Thus, for instance, navigation of a frame 
camera is a prerequisite for its further stabilization through 
some form of camera control. Sensor orientation and 
calibration are well known topics in PRS and, in the context of 
this paper, require no further discussion. The mentioned tasks, 
from sensor navigation to calibration, mainly depend on two 
technologies: trajectory determination —in the sense of time- 
Position-Velocity-Attitude (tPVA) determination— and sensor 
calibration and orientation (SCO) in PRS —i.e., direct sensor 
orientation (DSO), indirect or integrated sensor orientation 
(ISO) and other methods. 
Small unmanned autonomous vehicles and their cost target 
define a somewhat new scenario: the PRS navigation- 
orientation and sensor payloads may be exposed to unfriendly 
electromagnetic and mechanical environments that may require 
HW and SW protection techniques; rotary wing UAs 
(helicopters) are as common as fixed wing UAs (airplanes); the 
low cost of small UAs open the market to players who may not 
use the sophisticated PRS HW and SW gear and the 
experienced PRS operators. The next two sections are devoted, 
therefore, to tPVA determination and to sensor orientation and 
calibration for the particular case of UAS-based PRS with 
small UAs. 
4.1 tPVA trajectory determination 
In UAS-based PRS, tPVA trajectory determination either in 
real-time (for sensor navigation, sensor control and real-time 
applications) or in post-processing (for precise sensor 
calibration and orientation) is, in principle, a similar problem to 
the traditional airborne PRS one. It is accomplished through the 
PRS navigation-orientation payload which may or may not be 
used as the real-time navigation input for the auto-pilot or UA 
FCS. As a result, the PRS navigation-orientation payload may 
have to fulfill safe navigation requirements which, depending 
on the need of mechanical isolation between the PRS sensor 
payload and the UA main body, may require filtering 
techniques and vibration analysis. 
Figure 3: EPFL’s Hasselblad Biogon SWCE 903 (~ 17 x 21 x 
17 cm3, ~ 5 kg). 
There are two main challenges in tPVA trajectory 
determination for UAS-based PRS: high integrity (controlled 
accuracy and high reliability) of the real-time solution and high 
accuracy and precision of the post-processed solution for 
sensor calibration and orientation. 
Integrity is a hot topic in satellite navigation and it is addressed 
in various ways: GPS augmentations with signal integrity 
monitoring like the US Wide Area Augmentation System 
(WAAS) or the European Geostationary Navigation Overlay 
System (EGNOS); GPS Receiver Autonomous Integrity 
Monitoring (RAIM); GPS receiver hybridization with 
additional and complementary sensors; Autonomous Integrity 
Monitoring (AIM) of hybrid navigation systems; Global 
Navigation Satellite System (GNSS) configurations with GPS 
and the Russian GLONASS and in the future with GPS and the 
EU Galileo system. Further to this, in recent years, the use of 
hybrid nvigation systems with redundant IMU configurations 
of various kinds have been proposed (Colomina et al., 2004), 
integrated, 
Figure 4: Siemens star target from a distance of 20 m 
[preliminary results]. 
tested and analysed (Waegli et al., 2008) with encouraging 
results. As of today, dual frequency GPS receivers with 
WAAS/EGNOS an capabilities, possibly GLONASS capable, 
with algorithm redundant IMU configurations, barometric 
altimeters and magnetometers plus an AIM capability can 
provide 1- m level accuracy and sufficient integrity for 
unmanned operations. 
For the mentioned configuration, optimal accuracy and 
precision in tPVA trajectory determination is pursued with 
sophisticated sensor models; from GPS signal modeling, 
including integer ambiguity resolution, to the calibration of the 
IMUs. The estimation of the tPVA parameters and the rest of 
the model parameters with, typically, forward and backward 
Kalman filtering should render, in principle, accurate and