Pilots shut off GPS, other tools to train for future wars | Air Force Times | airforcetimes.com
Dealing With The Chinese Apocalypse
While the GPS signal at the earth's surface is very weak, it is difficult but possible to jam against more sophisticated SAASM and M-code receivers. and see GPS Jamming
This may degrade manned operations, but will shut down most current UAV operations if GPS is jammed over a significant area. Old standbys such as vision based, SAR aided TERCOM, celestial, and pure inertial will be expensive to add in and each by itself will have problems and limitations. All Source Data fusion navigation as proposed by Williams and Crump may be required,
Abstract. The drive towards utilizing small, cheap, autonomous
aerial vehicles for military operations means that navigation systems that are robust
to GPS denial must be employed. The simplest option available is to increase
the accuracy of the inertial measurement unit (IMU), but this can substantially
increase the price per operational unit. This paper presents an overview of the
All Source Navigation system developed by BAE Systems Australia based on
inexpensive MEMS IMUs and a supporting image processing unit. The navigation
system is capable of sustaining the operational flight capability of the
vehicle for prolonged periods of time compared to the pure inertial solution. At
its core, All - Source Navigation makes use of SLAM techniques . A variety of
additional aiding sources are fused into the inertial navigation solution to g ive
improved navigational accuracy during flight. The system is capable of
performing both conventional static, as well as in flight alignment. All Source
Navigation is demonstrated on the Kingfisher 2 UAV platform at the West Sale test
facility.
Another Kalman filter based approach is proposed by Srikanth
Saripalli of the School of Earth and Space Exploration, Arizona State
University, Tempe, AZ, USA in “State Estimation for UAVs in GPS-denied
Environments”. State Estimation for UAVs in GPS-denied ... - ResearchGate
Abstract: UAVs flying at high altitudes can normally rely on
GPS for accurate position and velocity estimates. However, navigation through
areas such as canyons and under forest canopy, where GPS coverage is transient
or unavailable, necessitates an alternative approach. In these situations, a
position estimate can be obtained using vision. This paper develops an
algorithm that uses cheap accelerometers and gyroscopes and combines them with
position estimates from vision in an extended kalman filter framework to
provide precise position and orientation information. We show preliminary
experimental results that prove that our technique can be used for accurate
positioning information for UAVs in GPS-denied environments.
or "Autonomous Flight in GPS-Denied Environments Using MonocularVision and Inertial Sensors" by Allen D. Wu, Eric N. Johnson, Michael Kaess, Frank Dellaert,
and Girish Chowdhary.
Abstract: A vision-aided inertial navigation system that enables
autonomous flight of an aerial vehicle in GPS-denied environments is presented.
Particularly, feature point information from a monocular vision sensor are used
to bound the drift resulting from integrating accelerations and angular rate
measurements from an Inertial Measurement Unit (IMU) forward in time. An
Extended Kalman filter framework is proposed for performing the tasks of
vision-based mapping and navigation separately. When GPS is available, multiple
observations of a single landmark point from the vision sensor are used to
estimate the point’s location in inertial space. When GPS is not available,
points that have been sufficiently mapped out can be used for estimating
vehicle position and attitude. Simulation and flight test results of a vehicle
operating autonomously in a simplified loss-of-GPS scenario verify the
presented method.
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