A method for aiding the landing of an aircraft on a landing runway comprises the following steps implemented in an automatic manner by a processing unit: a) acquiring information relating to the landing runway; b) acquiring information relating to a current situation of the aircraft; c) determining, as a function of said information, at least one deviation between at least one parameter relating to a landing position of the aircraft on the landing runway and a reference relating to a central longitudinal axis of the landing runway; d) comparing this deviation with a predetermined threshold; and e) as a function of the result of the comparison carried out in step d), commanding, if appropriate, the signaling of an alert by means of a signaling system of the aircraft.

A method for aiding the landing of an aircraft on a landing runway comprising the following steps implemented in an automatic manner by a processing unit: a) acquiring information relating to the landing runway; b) acquiring information relating to a current situation of the aircraft; f) determining a maximum roll angle, in absolute value, necessary to allow a flight of the aircraft along a trajectory between a current position and a target landing position on the landing runway; g) comparing this maximum roll angle with a predetermined limit; and h) as a function of the result of the comparison carried out in step g), commanding, if appropriate, the signaling of an alert by means of a signaling system of the aircraft.

Method and device for estimating lateral speed and lateral position of an aircraft during a phase where the aircraft is traveling on the ground. The device includes a unit for determining an initial lateral position value, corresponding to lateral position with respect to axis of a runway when touching down on landing, a unit for repetitively determining, at least from runway touch down, current ground speed and a current lateral angular deviation, representing angular deviation between the current route and the heading of the runway, a unit for repetitively computing current lateral speed, from the current ground speed and current lateral angular deviation, a unit for computing a current lateral position, from current lateral speed and initial lateral position, and a link for transmitting the current lateral speed and/or the current lateral position to at least one user system.

A method for providing landing assistance for an aircraft is provided. The method analyzes terrain data; identifies one or more landing zones, based on analyzing the terrain data, each of the one or more landing zones comprising a flat area lacking obstacles to aircraft landing; and presents the one or more landing zones via a display element onboard the aircraft.

An aerial vehicle and system for automatically detecting an object (e.g., human, pet, or other animal) approaching the aerial vehicle is described. When an approaching object is detected by an object detection component, a safety profile may be executed to reduce or avoid any potential harm to the object and/or the aerial vehicle. For example, if the object is detected entering a safety perimeter of the aerial vehicle, the rotation of a propeller closest to the object may be stopped to avoid harming the object and rotations of remaining propellers may be modified to maintain control and flight of the aerial vehicle.

In one example, a method to guide and navigate the aircraft during a complete engine failure is disclosed. Nearby airport data is obtained based on aircraft current location upon detecting the complete aircraft engine failure. Minimum and maximum glide distances of the aircraft are computed based on the current aircraft state parameters and environmental parameters. Candidate reachable airports are determined using the obtained nearby airport data for safe landing based on the computed minimum and maximum glide distances. A glide path for each candidate reachable airport is determined. The aircraft is navigated and guided to a selected one of the candidate reachable airports using an associated glide path.

An aircraft defining an upright orientation and an inverted orientation, a ground station; and a control system for remotely controlling the flight of the aircraft. The ground station has an auto-land function that causes the aircraft to invert, stall, and controllably land in the inverted orientation to protect a payload and a rudder extending down from the aircraft. In the upright orientation, the ground station depicts the view from a first aircraft camera. When switching to the inverted orientation: (1) the ground station depicts the view from a second aircraft camera, (2) the aircraft switches the colors of red and green wing lights, extends the ailerons to act as inverted flaps, and (3) the control system adapts a ground station controller for the inverted orientation. The aircraft landing gear is an expanded polypropylene pad located above the wing when the aircraft is in the upright orientation.

A system and method is provided for updating an aircraft flight management system with approach and landing information received from a NOTAM transmission. The system and method receives an updated ILS category, updates the ILS category and updates the associated decision height/altitude. In addition, the system and method generates a notification of the NOTAM update and disregards user attempts to select an ILS category and/or decision height that is inconsistent with the NOTAM update.

Improved mechanisms for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, atmospheric liquid water content, or precipitable water and other atmospheric-based phenomena, for example presence and intensity of fog, based upon these sensor readings, predicting future precipitation and atmospheric-based phenomena, and estimating effects of the atmospheric-based phenomena on visibility, for example by calculating runway visible range (RVR) estimates and forecasts based on the atmospheric-based phenomena.

A method is provided for supporting an aircraft approaching a runway on an airfield. The method includes receiving a sequence of images of the airfield, captured by a camera onboard the aircraft approaching the runway. For at least one image of the sequence of images, the method includes applying the image(s) to a machine learning model trained to predict a pose of the aircraft relative to the runway. The machine learning model is configured to map the image(s) to the pose based on a training set of labeled images with respective ground truth poses of the aircraft relative to the runway. The pose is output as a current pose estimate of the aircraft relative to the runway for use in at least one of monitoring the current pose estimate, generating an alert based on the current pose estimate, or guidance or control of the aircraft on a final approach.