Abstract: A system for efficiently sensing collision threats has an image sensor configured to capture an image of a scene external to a vehicle. The system is configured to then identify an area of the image that is associated with homogeneous sensor values and is thus likely devoid of collision threats. In order to reduce the computational processing required for detecting collision threats, the system culls the identified area from the image, thereby conserving the processing resources of the system.

Abstract: A monitoring system for an aircraft can include an image sensor and a radar sensor. The system can provide noise compensation to a radar sample corresponding to a return radar signal received by the radar sensor based on information detected by the image sensor. The system can identify one or more object types in the image captured by the image sensor and then translate the identified object types to corresponding positions on a map. The system can correlate the radar sample to a position on the map and any object type located at that position can be identified. The system can then select a noise pattern that corresponds to the identified object type from the map and use the selected noise pattern to compensate the radar sample.

Abstract: A monitoring system for an aircraft uses sensors configured to sense objects around the aircraft to generate a recommendation that is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with a sensed object. A first algorithm generates guidance to avoid encounters with sensed airborne aircrafts. A second algorithm generates guidance to avoid encounters with sensed non-aircraft airborne obstacles and ground obstacles. The second algorithm sends inhibiting information to the first algorithm in a feedback loop based on the position of sensed non-aircraft objects. The first algorithm considers this inhibiting information when generating avoidance guidance regarding airborne aircrafts.

Abstract: A simulation testing architecture can be applied to an aircraft monitoring system for an aircraft that includes complex algorithms (such as machine learning algorithms) for sensing objects around the aircraft and controlling the aircraft to avoid such objects. A reference scenario is selected from a plurality of stored scenarios based on a desired set of aircraft safety standards. A stochastic process is applied to generate a large number of conditional variations within a simulated environment, varying weather, objects in the airspace, points of failure, and the like to provide a representative sample of possible aircraft missions and encounters within the selected reference scenario. Synthetic environmental inputs are fed into the aircraft monitoring system software, and the resultant actions of the software are logged. These logs can be used to generate metrics on an encounter-level basis, a scenario-level basis, or across a population of scenarios.

Abstract: A monitoring system for an aircraft has sensors configured to sense objects around the aircraft and provide data indicative of the sensed objects. The system contains a first type of computing module that processes data obtained from all the sensors and a second type of computing module dedicated to processing data from a particular sensor. The second module may characterize and locate a detected object within the processed image data. Both the first and second modules generate a likelihood of detection of an object within their processed image data. A scheduler module calculates a percentage of computing resources that should be assigned to processing data from a respective image sensor in view of this likelihood and assigns a dedicated compute module to an image sensor requiring a higher percentage of attention. Processing resources may therefore be focused on geospatial areas with a high likelihood of object detection.

Abstract: A monitoring system for an aircraft has sensors that are used to sense the presence of objects around the aircraft for collision avoidance, navigation, or other purposes. At least one of the sensors may be configured to sense objects around the aircraft and provide data indicative of the sensed objects. The monitoring system may use information from the sensor and information about the aircraft to determine an escape envelope including possible routes that the aircraft can follow to avoid colliding with the object. The monitoring system may select an escape path based on the escape envelope and control the aircraft to follow the escape path to avoid collision with one or more objects.

Abstract: A monitoring system for an aircraft has sensors that are used to sense the presence of objects around the aircraft for collision avoidance, navigation, or other purposes. At least one of the sensors may be configured to sense objects around the aircraft and provide data indicative of the sensed objects. The monitoring system may use information from the sensor and information about the aircraft to determine an escape envelope including possible routes that the aircraft can follow to avoid colliding with the object. The monitoring system may select an escape path based on the escape envelope and control the aircraft to follow the escape path to avoid collision with one or more objects.