Abstract: The present disclosure generally pertains to systems and methods for detecting surface conditions using multiple images of different polarizations. A system in accordance with the present disclosure captures images having different polarizations and compares the images to evaluate surface conditions of an area, such as a runway, landing pad, roadway, or taxiway on which a vehicle is expected to land or otherwise travel. In some cases, a surface hazard, such as water, ice, or snow covering a surface of the area, may be detected and identified. Information indicative of the surface conditions may be used to make control decisions for operation of the vehicle.

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 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 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 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 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 configured to sense objects around the aircraft and provide data indicative of the sensed objects. A sense and avoid system is designed in a plurality of software layers, each layer functioning in an independent manner. An evasion software layer is made up of fixed, non-modifiable code that meets an applicable regulatory standard. The remainder of the software layers may be made up of modifiable or non-modifiable code configured so as not to adversely impact the functioning of an evasion software layer, even when modified. Each of the software layers of the sense and avoid system may use information from the sensors and information about the aircraft to generate a recommendation which is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with the sensed object. The aircraft may then be controlled, in accordance with the recommendation, to avoid collision with the object.

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.