Determining Impact of Navigation Errors on Mission Capabilities
Kathleen Ann Kramer, Stephen Craig Stubberud · 2021
The mission of an unmanned aerial system (UAS) is highly dependent on the accuracy of the utilized navigation system. UAS navigation systems typically rely on GPS or image navigation. However, GPS-based systems are vulnerable to being jammed or, in some areas, blocked. Image navigation systems require communications and/or landmarks to navigate. Again, these are not always available. Some UAS systems have multiple navigation systems that include inertial system or homing systems. These systems may not be the most accurate, but can provide enough capability to allow the UAS to navigate from a last known position to a point where the primary navigation system can be re-established.The ability for the UAS to understand its navigation accuracy is important for its mission planning capability. Success can depend on whether the navigation solution is within a given accuracy or not. Very accurate navigation solutions are important for the safety of not just the UAS but also whatever is around and below the UAS. If the primary navigation system is not operational or degraded, the secondary navigation systems may take over. Some of these systems, such as an INS, degrade over time. The UAS should use its inherent knowledge of its navigation capabilities to infer if and how it can complete its mission.Navigation failures and degradations impact the mission capabilities of an UAS. An impact assessment technique is developed to identify the UAS navigation capabilities. The concept is to implement a neural network system that estimates the accuracy of the navigation solution with regards to the mission parameters based on the estimated accuracy of the available navigation capabilities. The neural network uses the monitored status of the navigation systems and estimates navigation accuracy. The accuracy of the overall navigation solution is derived from the inertial system, the image capabilities, the GPS effectiveness, and the availability of homing beacons. Each system reports a measure of quality generated by the neural network. The neural network will be trained navigation system accuracy parameters that map to a quality score.The neural network solution will feed a fuzzy evidence accrual system. The evidence accrual system will create estimated measures that let the mission planning determine the safety and effectiveness for the unmanned aerial system to continue its mission. The evidence accrual result will use the navigation accuracy and the mission safety parameters to make a determination if the planned UAS mission can continue.