The performances of the complementary
filter earlier described have
been tested by means of both
simulated and real world flights.
With references to off-line testing,
the simulator values of the relevant
variables have been assumed as real
and compared with the values obtained
from complementary filter and GPS.
The values obtained from GPS are
filtered through a first order low-pass
filter, whose cut-off frequency has been
chosen in order to reduce as much as
possible the noise, but without attenuating
the aircraft dynamic. Based on these
requirements, the cut-off frequency
used for GPS has been set to 1 Hz.
In order to emphasize the performances
and the usefulness of the complementary
filter, in the next some figures are shown
which present a comparison among
measures obtained by complimentary
filter (red line), measures obtained by
GPS (black line) and real value (blue line)
of some inertial parameters of interest.
The figures refer to an autonomous
landing off-line simulation and are
representative of the several off-line
simulations performed in the validation
stage of the autonomous guidance
algorithms and, as a consequence,
of the complementary filter too.

Figure 2 - Comparison among measures obtained by complimentary filter and GPS and real value
of altitude during off-line simulated autonomous landing
In particular, Figure 2 shows the
comparison among the above mentioned
values with reference to the altitude
measure during an autonomous
landing, while Figure 3 shows this
comparison regarding the vertical
speed during the same manoeuvre.
Both figures show that by using the complementary filter here proposed
two advantages can be obtained:
● complementary filter is able to
attenuate the noise more than
the first order low-pass filter;
● measures obtained from
complementary filter have more
accuracy than the ones obtained
by filtering the GPS measures.
For what concerns real world in-flight
testing, in all flights performed in order
to validate advanced guidance algorithms
developed in the framework of TECVOL
project, as previously described, the
behaviour of complementary filter
fully confirmed results obtained in offline
simulations. For instance, this is
shown in the figures reported in the
next, referred to different in flight
tests and selected to emphasize the
performances of the complementary
filter with regard to altitude (see Figure
4, referred to a real world autonomous
landing manoeuvre) and to vertical speed
estimations (see Figure 5, which refers
to a real world mid-air flight phase).

Figure 3 - Comparison among measures obtained by complimentary filter and GPS and real value
of vertical speed during off-line simulated autonomous landing

Figure 4 - Comparison among altitude measures obtained by complimentary filter and GPS during
real world autonomous landing manoeuvre
The complementary filter has a further
feature: it is able to delete the frequency
content due to a sudden GPS precision
loss. This is shown in the figures
reported in the next, which refer to
GPS precision loss cases experienced
during real flights. In particular, these
figures show altitude (see Figure 6) and
XNEU position (see Figure 7) measures
when the GPS precision decreases
(as confirmed by increasing value of
GPS measure standard deviation).
Conclusions
In this paper a new algorithm has been
described for the integration of measures
provided by satellite navigation system
with the ones provided by other sensors,
such as ADS, AHRS and laser altimeter,
in order to allow a more accurate
determination of vehicle position and
speed, in both no-failure and GPS
failure conditions. The effectiveness
of the proposed algorithm has been
demonstrated by means of both off-line
and real world in-flight tests, referred
to an aeronautical application. It must
be emphasized yet that the proposed
algorithm is not limited to aeronautical
use only but it can be implemented in all
satellite-based navigation applications.
References
[1] Office of the Secretary of
Defense, “UAV Roadmap 2002-
2007 of Defense, Washington
DC, 2002, pp. 153-164.
[2] Kayton, M. and Fried, W.R., “Avionics Navigation Systems,”
2nd ed., Wiley-Interscience, New
York NY, 1997, pp. 600-607.
[3] Pachter M., “Challenges of
Autonomous Control”, IEEE
Control Systems, August 1998
[4] Malaek S. M. B., Izadi H. A.,
M. Pakmehr, “Flight Envelope
Expansion in Landing Phase Using
Classic, Intelligent and Adaptive
Controllers”, Journal of Aircraft, vol.
43, No. 1, January-February 2006
[5] Kaminer, I., Yakimenko,
O., Dobrokhodov, V., and
Jones, K., “Rapid Flight Test
Prototyping System and the
Fleet of UAV’s and MAVs at
the Naval Postgraduate School,”
AIAA-2004-6491, AIAA, 3rd “Unmanned Unlimited”Conference,
Chicago IL, 2004.
[6] Kingston, D., and Beard, D., “Real-
Time Attitude and Position Estimation
for Small UAVs Using Low-
Cost Sensors,” AIAA-2004-6488,
AIAA, 3rd “Unmanned Unlimited”
Conference, Chicago IL, 2004.
[7] Johnson, E., Schrage, D., Prasad,
J., and Vachtsevanos, G., “UAV
Flight Test Programs at Georgia
Tech,” AIAA-2004-6492, 3rd “Unmanned Unlimited”Conference,
Chicago IL, 2004.
[8] Ambrosino G., Ariola M.,
Ciniglio U., Corraro F., Pironti
A., Virgilio M., “Algorithms for
3D UAV Path Generation and
Tracking”, Proceedings of the 45th
IEEE Conference on Decision
and Control, San Diego, CA,
USA, December 13-15, 2006
[9] Luongo S., Carbone C. Corraro
F. Ciniglio U., “An Optimal 3D
Analytical Solution for Collision
Avoidance between Aircraft”,
Proceedings of the IEEE
Aerospace Conference 2009
[10] V. Di Vito, E. De Lellis, C. Marrone,
U. Ciniglio, F. Corraro, “UAV Free
Path Safe DGPS/AHRS Approach
and Landing System with Dynamic
and Performance Constraints”,
UAV Systems 2007 International
Conference & Exhibition [CD-ROM],
Paris, France, 12-14 June 2007
[11] V. Di Vito, E. De Lellis, C.
Marrone, Genito N., U. Ciniglio,
F. Corraro, “UAV Free Path
Safe DGPS/AHRS Autolanding:
algorithms and flight tests”,
submitted at UAS 2008 International
Conference & Exhibition, Paris,
France, 10-12 June 2008
[12] Accardo D., Cimmino G., Ciniglio U.,
Corraro F., Esposito F., Moccia A., “Integration of Advanced Altimetric
Systems for UAV Vertical Navigation
During Landing Manouevres”, AIAA,
Unmanned Unlimited Conference
Workshop and Exhibit, (paper no.
AIAA 2004-6318), 20 - 23 September
2004, Chicago, Illinois,USA.

Figure 5 - Comparison among vertical speed measures obtained by complimentary filter and GPS
during real world autonomous landing manoeuvre

Figure 6 - Comparison among altitude measures obtained by complimentary filter and GPS during
real flight in case of GPS precision loss
[13] Savage, P., “Strapdown Analytics,” Strapdown Associates Inc.,
Minneapolis MN, 2002, Chap. 15.
[14] Farrell, J.A., and Barth, M., “The
Global Positioning System & Inertial Navigation,” McGraw
Hill Professional, New York NY,
1998, pp 135-139, pp 241-257.
[15] Grewal, M.S., Weill, L.R.,
and Andrews, A.P., “Global
Positioning System, Inertial
Navigation and Integration,” John
Wiley & Sons, New York NY,
2002, pp 14-37, pp 103-130.

Figure 7 - Comparison among XNEU position measures obtained by complimentary filter and GPS
during real flight in case of GPS precision loss
[16] Rogers, R.M., “Applied Mathematics
in Integrated Navigation
Instruments,”AIAA Education
Series, AIAA, Washington DC,
2000, pp 18-94, pp 163-177.
[17] Chatfield, A.B., “Fundamentals
of High Accuracy Inertial
Navigation,”AIAA Press, Washington
DC, 1997, pp. 267-271.
[18] Johnson, E.N., Proctor, A.A.,
Ha, J., and Tannenbaum, A.R.,
“Development and Test of Highly
Autonomous Unmanned Aerial
Vehicles,” AIAA, Journal of
Aerospace Computing, Information
and Communication, Vol. 1,
Issue 12, 2004,pp. 485-501.
[19] Walter, B.E., Knutzon, J.S., Sannier,
A.V., and Oliver, J.H., “Virtual
UAV Ground Control Station,”
AIAA-2004-6230, AIAA, 3rd “Unmanned Unlimited”Conference,
Chicago IL, 2004.
[20] Evans, J., Inalhan, G., Jang,
J.S., Teo, R., and Tomlin, C.J., “Dragonfly: a Versatile UAV
Platform for the Advancement of
Aircraft Navigation and Control,” IEEE,Proceedings of Digital Avionics
Systems, Vol. 1, Daytona Beach,
FL, 2001, pp. 1C3/1 - 1C3/12.
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