WO2025088470A1

WO2025088470A1 - Aircraft systems

Info

Publication number: WO2025088470A1
Application number: PCT/IB2024/060337
Authority: WO
Inventors: Thomas GRAHAM-NICOLL
Original assignee: Graham Air Intl Ltd
Current assignee: Graham Air Intl Ltd
Priority date: 2023-10-24
Filing date: 2024-10-21
Publication date: 2025-05-01
Anticipated expiration: 2026-04-24

Abstract

A Flight Control System for an aerial vehicle, the system comprising an autopilot for autonomously controlling the flight of the aerial vehicle; a GNSS receiver for receiving GNSS signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle; and one or more radio receivers for receiving radio signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle. The Flight Control System has a primary mode of operation in which a location of the aerial vehicle is calculated using the received GNSS signals, and provided to the autopilot for controlling the flight of the aerial vehicle and a secondary mode of operation in which a location of the aerial vehicle is calculated using the received radio signals, and provided to the autopilot for controlling the flight of the aerial vehicle.

Description

AIRCRAFT SYSTEMS

TECHNICAL FIELD

The present invention relates generally to Aircraft Systems and methods, including Unmanned Aircraft Systems. The invention relates in particular, although not necessarily exclusively, to systems and methods for controlling the flight paths of Aerial Vehicles (e.g. Unmanned Aerial Vehicles) to avoid flight hazards.

BACKGROUND

In recent times, there has been an increase in the use of Unmanned Aerial Vehicles (“UAV” or “UAVs”), often referred to as “drones”, for various types of reconnaissance, surveillance, information gathering and inspection activities for commercial, law enforcement and military purposes. These UAVs are remotely piloted aircraft that carry cameras, sensors, communications equipment and payloads to support various mission goals without requiring a manned pilot onboard.

In commercial, law enforcement and military environments, one or more UAVs are typically deployed as part of an overall Unmanned Aircraft System (“UAS”), with one or more human operators (“pilots”) controlling the drones remotely through a (typically) ground-based controller to ensure safe operation. Navigation data input by a pilot/operator is transmitted to the remotely operated UAVs from the ground-based controller through a command-and-control system (sometimes referred to as a command, control and communication system) or a C2 link or datalink, which provides one or more wireless communication links between the controller and the UAVs. The wireless communication link (or links) may, for example, include radio links and/or satellite links operating with suitable communication protocols, and provide data transmission to and from the UAV. In many cases, a UAV will have at least a degree of autonomy in its flight operation, for example, using an onboard autopilot system to follow a defined flight path (typically using GNSS-based navigation, e.g., based on GPS waypoints).

Currently, no automated guidance systems exist to allow integration of all aircraft types to operate uniformly in shared mixed-use airspace. Vehicles are currently separated by manned controllers and supplemented by last minute transponder-based traffic collision avoidance systems (TCAS).

As the number of drones that are operational in shared, mixed-use airspace increases, so do the safety concerns and, in particular, the concerns around the risk of collisions with other aircraft. Although existing ‘Detect and Avoid’ (DAA) systems used in larger UAV and other aircraft (e.g., TCAS systems in commercial aircraft) can prompt pilot intervention at the ‘last minute’ to avoid mid-air collisions when a collision risk is detected, it is undesirable for such ‘last minute’ measures to be used frequently; they should not be the ‘norm’.

SUMMARY

In general, embodiments of the present invention are concerned with reducing the risk of mid-air collisions and other in-flight risks involving UAVs by providing a system and method that makes use of the known and/or predicted locations of flight hazards (e.g., other aircraft, fixed obstacles, restricted airspace, bad weather conditions, etc.) to control the flight of a UAV to navigate around the flight hazards before any collision risk (as would be identified by a TCAS system, for example) exists.

In a first aspect, the invention provides an unmanned aircraft system, the system comprising: at least one unmanned aerial vehicle (UAV); and a Flight Control System for updating flight path data defining a flight path for the UAV, the UAV comprising autonomous flight controls that use the flight path data to control the flight of the UAV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including analysis of flight data for one or more other aircraft in airspace around the flight path to determine one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the UAV will bring the UAV closer than a predefined minimum distance from one of the other aircraft, the Flight Control System is operative to update the UAV flight path data to adjust the flight path of the UAV to be more than the predefined minimum distance from the predicted future position of the other aircraft.

This approach enables the UAV’s flight path to be updated autonomously, during a mission (i.e., whilst the UAV is in flight), to avoid other aircraft, whilst still ultimately performing its intended mission, for example reaching and/or spending time at a destination initially set, for example, by a human operator.

The “predetermined distance” may change dependent on factors such as flight parameters (e.g., speed) of the aircraft and geographical location. For example, for airborne vehicles flying over non-populated areas, the “predetermined distance” could be less than the case where the vehicles are flying over a city or in other higher risk areas, such as near airports with manned aircraft landing and taking off.

The term “flight path” used herein is intended to cover any in-flight operation of the UAV (or other aerial vehicle). This may include, for example, flight from a start point to an end point (optionally via one or more waypoints), a flight pattern around a point of interest or around a specific geographical area (e.g., for surveillance of that area), and hovering over a specific location.

The updating of the flight path data to adjust the flight path may include, for example, changes in heading, altitude, rate of climb (ascent) / sink (descent), and/or speed of the UAV (or other aerial vehicle).

As will become more apparent from the detailed discussion of embodiments further below, the Flight Control System may include functions that are carried out by ground-based systems as well as functions that are carried out by systems (including an autopilot) onboard the UAV. The term “Flight Control System" should be understood accordingly. In some embodiments, the flight data for the one or more other aircraft in airspace around the flight path comprises Automatic Dependent Surveillance data (e.g., ADS-B and/or ADS-C data) and/or FLARM data.

In some embodiments, the flight data is obtained from a transponder or transponders onboard the UAV itself and/or transponders onboard one or more other UAVs associated with the unmanned aircraft system. These transponders typically encompass ‘Mode S’ as well as ADS-B. Additionally, or alternatively, the flight data may be obtained from one or more ground- based ADS-B receivers, connected to the unmanned aircraft system, that receive the flight data directly from aircraft and/or internet sources, accessible to the unmanned aircraft system, that provide a feed of the flight data.

Whatever the source or sources of the flight data, the data is preferably updated at least once every 5 seconds or less.

In some embodiments, the Flight Control System makes use of TCAS logic inputs when updating the flight path data. This logic can be used to update the flight path data in a timely way that avoids the UAV triggering any Traffic Advisories (TAs) or Resolution Advisories (RAs) by TCAS systems of other aircraft. This can be achieved by predicting other aircraft movements sufficiently far ahead of the current position of the UAV to allow changes in the flight path well ahead of the UAV entering the TA region of the other aircraft.

In some embodiments, the flight path changes for the UAV (dictated by the updated flight path data) can include changes in altitude, changes in the rate of climb or sink, changes in the heading, changes in the speed of the UAV, or a combination of any two or more of these changes.

In some embodiments, the analysis of flight hazards by the Flight Control System comprises analysis of flight hazard types in addition to other aircraft. In this case, the Flight Control System can update the flight path data for the UAV based on the combined impact of all of the analysed flight hazard types.

In addition to other aircraft sharing the airspace with the UAV, flight hazard types that embodiments of the invention might use in the control of the UAV’s flight path include: adverse weather conditions, restricted airspace and/or other predefined geographical areas to be avoided by the UAV, and permanent or temporary structures or objects.

In some embodiments, the analysis of flight hazards comprises applying a risk grading to each of a plurality of airspace zones based on hazard data defining the presence or not of a flight hazard in a zone at a given time. The grading can dictate, for each airspace zone at a given time, whether or not it is safe for a UAV to pass through the zone. The flight path for the UAV can be updated to avoid unsafe zones.

Whilst the airspace zones may be any suitable size and shape, in some embodiments the zones are arranged in a regular 3-D array of cuboid zones, for example a 3-D array of 500m x 500m cubes, 1km x 1km x 1km cubes, 5km x 5km x 5km cubes or 10km x 10km x 10km cubes, or a mixture of different size cubes.

Adopting the approach described above, it becomes possible for multiple UAVs (e.g., three or four or more) to be deployed in an unmanned aircraft system under the control of a single pilot because each UAV is capable of autonomously avoiding other aircraft along its flight path without pilot input.

In a second aspect, the invention provides a Flight Control System for updating flight path data defining a flight path for an aerial vehicle, wherein the Flight Control System is operative to update the flight path data periodically, based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including analysis of received flight data for one or more other aircraft in airspace around the flight path to determine one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the aerial vehicle will bring the aerial vehicle closer than a predefined minimum distance from one of the other aircraft, the Flight Control System is operative to update the aerial vehicle flight path data to adjust the flight path of the aerial vehicle to be more than the predefined minimum distance from the predicted future position of the other aircraft. Whilst the Flight Control System of the second aspect is particularly useful for updating the flight path of one or more UAVs, embodiments of the system can be used in the control (including autonomous control) or other aerial vehicles, including, for example, eVTOL and other Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) systems, as well as conventional manned aircraft.

Embodiments of this second aspect may comprise one or more of the features set forth above in the context of embodiments of the first aspect.

In a third aspect, the invention provides a computer-implemented method for updating flight path data defining a flight path for an aerial vehicle, the method comprising: receiving flight data for one or more other aircraft in airspace around the flight path; based on the received flight data for the one or more other aircraft, determining one or more predicted future positions for each of the one or more other aircraft; in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the aerial vehicle will bring the aerial vehicle closer than a predefined minimum distance from one of the other aircraft, updating the aerial vehicle flight path data to adjust the flight path of the aerial vehicle to ensure the aerial vehicle remains more than the predefined minimum distance from the predicted future position of the other aircraft.

The updated flight path data can be used, for example, by an autopilot of an aerial vehicle (e.g., a UAV) to autonomously control the flight of the aerial vehicle.

Embodiments of this third aspect may comprise one or more of the features set forth above in the context of embodiments of the first and second aspects.

In a fourth aspect, the invention provides an unmanned aircraft system, the system comprising: an unmanned aerial vehicle (UAV); a Flight Control System for updating flight path data defining a flight path for the UAV, the UAV comprising autonomous flight controls that use the flight path data to control the flight of the UAV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including predicting a weather-related risk based on a combination of: forecast weather data for airspace around a current flight path between the start point and the end point; and live weather data for airspace around the current flight path between the start point and the end point; in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the UAV will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the UAV to avoid the identified region.

In some embodiments, the forecast weather data is obtained periodically from one or more internet sources that are accessible to the unmanned aircraft system.

In some embodiments, the live weather data is obtained periodically from one or more weather satellites and/or weather radar systems, accessible to the unmanned aircraft system. Additionally, or alternatively, the live weather data may be obtained using a radar onboard the UAV itself.

Whatever the source or sources of the weather data, the data is preferably updated at least once every 5 seconds.

Embodiments of this fourth aspect may comprise one or more of the features set forth in the context of embodiments of the other aspects above.

For example, similarly to the aspects above, the analysis of flight hazards may comprise analysis of other flight hazard types in addition to adverse weather, the Flight Control System updating the flight path data for the UAV based on the combined impact of all of the analysed flight hazard types.

In a fifth aspect, the invention provides a Flight Control System for updating flight path data defining a flight path for an aerial vehicle, wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including predicting a weather-related risk based on a combination of: forecast weather data for airspace around a current flight path between the start point and the end point; and live weather data for airspace around the current flight path between the start point and the end point; in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the aerial vehicle will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the aerial vehicle to avoid the identified region.

As in the other aspects above, in some embodiments the analysis of flight hazards comprises analysis of other flight hazard types in addition to adverse weather, the Flight Control System updating the flight path data for the aerial vehicle based on the combined impact of all of the analysed flight hazard types.

Embodiments of this fifth aspect may comprise one or more of the features set forth in the context of embodiments of the other aspects above.

In a sixth aspect, the invention provides a computer-implemented method for updating flight path data defining a flight path for an aerial vehicle, the method comprising: receiving forecast weather data for airspace around a current flight path between the start point and the end point; receiving live weather data for airspace around the current flight path between the start point and the end point; predicting a weather-related risk based on a combination of the forecast weather data and live weather data; and in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the aerial vehicle will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the aerial vehicle to avoid the identified region. The updated flight path data can be used, for example, by an autopilot of an aerial vehicle (e.g., a UAV) to autonomously control the flight of the aerial vehicle.

Embodiments of this sixth aspect may comprise one or more of the features set forth in the context of embodiments of the other aspects above.

In a seventh aspect, the invention provides a Flight Control System for an aerial vehicle, the system comprising: an autopilot for autonomously controlling the flight of the aerial vehicle; a GNSS receiver for receiving GNSS signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle; and one or more radio receivers for receiving radio signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle; the Flight Control System having a primary mode of operation in which a location of the aerial vehicle is calculated using the received GNSS signals, and provided to the autopilot for controlling the flight of the aerial vehicle; and the Flight Control System having a secondary mode of operation in which a location of the aerial vehicle is calculated using the received radio signals, and provided to the autopilot for controlling the flight of the aerial vehicle.

In some embodiments, the secondary mode of operation of the Flight Control System is (only) used when the GNSS receiver is unable to receive GNSS signals, so called GNSS-denied (e.g., GPS-denied) navigation.

In some embodiments, in the secondary mode of operation the location is calculated using triangulation of the received radio signals, trilateration of the received radio signals or a combination of both.

In some embodiments, the Flight Control System further comprises an inertial navigation system, and data from the inertial navigation system is used in conjunction with the radio signals in the secondary mode of operation to calculate the location of the aerial vehicle. The updated location / position of the vehicle may be defined over a ground-based map (e.g., one that is known, surveyed, and approved). In some embodiments, the location of the aerial vehicle is calculated in the secondary mode of operation using radio signals from known radio beacons, for example cell towers of one or more cellular networks. In these embodiments, the radio receiver (or each radio receiver when there is more than one) is configured to receive radio signals from the cell towers. For example, the radio receiver(s) can include one or more SIM cards.

In the same or other embodiments, the radio signals may be signals from VHF radio transmitters such as VOR or TACAN transmitters for example.

In some embodiments, the radio receiver(s) is/are configured to receive radio signals from cell towers of multiple cellular networks operated by different cellular network providers (e.g., by using multiple SIM cards, at least one for each network provider).

In embodiments of this seventh aspect, the aerial vehicle may, for example, be an unmanned aerial vehicle.

In some embodiments of the seventh aspect, the radio receiver(s) is/are configured to receive radio signals from an array of radio beacons at a predetermined location, for example at a landing location such as an airfield or airport. The array of radio beacons may be dedicated to be used for guiding an aerial vehicle (e.g., a UAV) to land at the landing location. This may be particularly useful, for example, to aid the landing of complex and/or large aerial vehicle(s) without the use of a GNSS signal (e.g., in a GNSS-denied situation or where there is a problem with the vehicle(s) GNSS receiver). In such dedicated arrays of beacons, there will generally be at least three beacons around the landing location and preferably between 3 and 24 (although there may be more).

In an alternative approach, which can be used alone or in combination with the approach described above for the seventh aspect, the location of the aerial vehicle can be determined by using an array of ground antennas for detecting radio signals to/from the aerial vehicle. Specifically, the detected radio signals can be being employed to calculate the location of the aerial vehicle using triangulation of the detected radio signals, trilateration of the detected radio signals or a combination of both. As with the approach using radio beacons discussed above, the array of ground antennas may be deployed around a landing location to be used to guide the aerial vehicle (e.g., UAV) in to land. In an eighth aspect, the invention provides a method for use in the autonomous control of the flight of an aerial vehicle, wherein, in normal operation of the aerial vehicle, a current location of the vehicle is calculated from GNSS signals, the method comprising, in the absence of GNSS signals, calculating a location of the aerial vehicle using opportunistic radio signals and/or radio signals from known radio beacons.

Embodiments of this eighth aspect may comprise one or more of the features set forth above in the context of embodiments of the seventh aspect.

Moreover, embodiments of the various aspects set forth above may be combined with one another in any combination, as will be appreciated by the skilled person.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 illustrates schematically an unmanned aircraft system in accordance with embodiments of the various aspects of the invention;

Figure 2 conceptually illustrates the main components of a Flight Control System in accordance with embodiments of the various aspects of the invention; and

Figure 3 shows an outline of various functional elements, and the relationships between them, of a Flight Control System in accordance with embodiments of the various aspects of the invention.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments are described below by way of example. Each of the functions described may, for example, be implemented in hardware, software executing on one or more digital processors, or a combination of software and hardware.

The embodiments are illustrated in the context of Unmanned Aircraft Systems including multiple UAVs. The skilled person will appreciate, however, that concepts and features described herein may be applied to a number of other contexts, for example to autonomous or semi-autonomous operation of manned flight systems / aircraft. Embodiments of the present invention are generally aimed at optimising the navigation of an aerial vehicle in 3 -dimensional space and time to allow the aerial vehicle to freely navigate (largely or wholly autonomously) around other air traffic, ground-based structures, restricted airspace and weather without creating a situation where a (‘last minute’) conflict resolution is required. More generally, adoption of the approaches described herein can lead to a more optimised, synergistic operation between various different aircraft types operating in shared airspace.

In particular it is an aim of embodiments of the invention to optimise navigation for an aerial vehicle (e.g., a UAV) to ensure continued safe conduct of a flight by avoiding flight hazards, including:

• collisions with other aircraft;

• incursion into restricted airspace and undesirable, unapproved geographical locations;

• collision with persons, vehicles, vessels and structures, both moving and stationary; and

• adverse weather conditions, to ensure continued safe conduct of a flight.

The approach proposed for the embodiment of the present invention exemplified here is to automatically plan and update the flight paths of UAVs to avoid all of the above flight hazards, with adjustments to the flight path being made long before a collision (or other) risk truly exists. These flight path changes are conducted autonomously, although it will generally be desirable to notify an operator (e.g., remote pilot) of route changes en-route to the desired final geographical destination. Additionally, or alternatively, in some operating scenarios it may be more appropriate to at least give an operator the opportunity to approve or override a proposed change in flight path before it is executed

By using this approach, as already suggested above, conventional manned aircraft operating in accordance with existing methods and regulations will be able to operate unaffected by the new integration of unmanned aircraft and provide a safe way to support harmonized aircraft operation with all types of aircraft. Figure 1 schematically shows the key system components of an unmanned aircraft system in accordance with an embodiment of the invention.

A Ground Control Station communicates with a fleet of UAVs (‘Air Vehicles’ in fig. 1) to transmit live command and telemetry data to the UAVs. The Ground Control Station also receives telemetry data from the UAVs. A pilot based at, or remotely connected to, the Ground Control Station can command / fly multiple (typically 4 or more) UAVs at the same time safely in a global airspace environment using the system described here.

The Ground Control Station is also in communication with (i.e., connected over a network, for example the Internet) one or more servers (typically ground-based) that host(s) databases of information that can be used to assist in the optimisation of the UAV navigation. For example, the information can include:

• airspace maps (e.g., identifying restricted airspace and avoidance areas);

• NOTAMS (e.g., identifying temporary flight hazards);

• map data identifying densely populated areas and other geographical features relevant to navigation, such as roads, railways, airports and ports;

• real-time (or regularly refreshed) ADS-B data, or other aircraft location and flight data;

• real-time (or regularly refreshed) FLARM data, for position information of gliders and light aircraft;

• real-time (or regularly refreshed) weather satellite / radar data; and

• terrain avoidance data.

In addition to the above hazard / navigation information being obtained for processing by the Ground Control Station, some or all of this data can be transmitted to the UAVs, to be used directly by an autopilot onboard the UAV.

In addition to the above information obtained from ground-based servers, data from the UAV’s onboard systems can also be used as inputs to navigation decisions. For example, as shown in fig. 1, each UAV carries an ADS-B in/out Mode C/S transponder, and flight data about other aircraft captured by this onboard transponder can be used to inform navigation decisions, both directly by the UAV and also by the Ground Control Station (the UAV transponder data being transmitted to the Ground Control Station over a communication downlink).

Each UAV also includes at least a collision avoidance radar, which can be used to supplement other navigational data, in order to avoid collisions with aircraft or other obstacles (whether airborne or on the ground, and whether moving or static) that have not already been identified and navigated around. The UAV will typically also include a radar used for landing manoeuvres.

A UAV-based radar can also be used in some cases to provide or supplement radar-based weather data.

The Ground Control Station uses a combination of all of the navigation- / hazard-related information from the ground-based servers and the fleet of UAVs to generate and regularly update flight hazard data, which can be used to autonomously control the flight paths of the UAVs to avoid identified flight hazards (for example, to be used by autopilots onboard the UAVs to provide this autonomous control).

In the currently envisaged implementation for the exemplified embodiment, a 3D flight hazard map is created, at least for the airspace around the intended flight path for the UAV. Specifically, the airspace is mapped as a 3-D array of zones, in this example each being a 1km x 1km x 1km cube. The map is updated regularly based on the navigation/hazard data/information discussed above in order to provide a risk grading for each zone over time. The risk grading may, for example, use a ‘traffic light’ approach, with each zone, for each time interval, being graded as UAV traffic being allowed or denied.

The flight hazard map is maintained and updated by the Ground Control Station. A copy of the map is also stored by the UAVs autopilot and used by the autopilot to navigate around zones graded as ‘UAV traffic denied’. The UAV autopilot’s copy of the flight hazard map is regularly updated by the Ground Control Station but can also be supplemented with data collected locally by the UAV’s onboard systems.

In use, an operator / pilot selects a destination for the UAV and an initial flight path for the UAV is determined by the UAV autopilot, taking into account the current state of the flight hazard map. Once the UAV is in flight, the flight hazard map is regularly updated, based on the data from the ground-based servers and data from the UAV’s onboard systems (along with data fed to the Ground Control Station from other UAVs). If the map updates result in a change to the risk grading of a zone through which the current flight path takes the UAV at a time when the risk grading will now be ‘UAV traffic denied’, the UAV’s autopilot updates the flightpath to avoid the now-denied zone, well ahead of the UAV reaching that zone.

The autopilot decision making logic, and specifically decisions about flight path updates to avoid ‘UAV traffic denied’ zones, includes manned aircraft TCAS logic inputs that are used to ensure that a UAV controlled in accordance with the approach discussed above will never cause the triggering of a TA or RA by another aircraft’s TCAS system; i.e., the UAV autopilot will navigate the UAV past the other aircraft at a sufficient distance to avoid triggering the other aircraft’s TCAS.

In a similar way, GPWS/TCAS relationship logic inputs can be used to avoid causing dangerous situations for other users of the airspace.

In the unlikely event that the UAV comes into close proximity of a flight hazard (e.g., another aircraft or a fixed obstacle) that has not already been identified as a flight hazard, the hazard will be detected by the UAV’s onboard radar and the autopilot can take appropriate collision avoidance action. As another safeguard, the system can also be configured to alert an operator to such hazards, allowing the operator to manually navigate the UAV around the hazard.

Fig. 2 shows the main components of a Flight Control System in accordance with embodiments of the various aspects of the invention, which can be used to implement the concepts discussed above.

The term ‘FPOS’ (or “Flight Path Optimization System”) is used to describe the overall system, which can be used to control multiple UAVs within an unmanned aircraft system (or other systems of aerial vehicles).

As seen in fig. 2, the FPOS makes use of inputs from ADS-B (and/or Mode C/S transponders) and FLARM transponders (e.g., onboard the UAV), the UAV’s onboard collision avoidance radar and data feeds from ground-based databases, including an airspace map, forecast and live weather data, and internet-based ADS-B and FLARM data feeds (as already discussed above). The FPOS data is used by the UAV autopilot to safely navigate the UAV in a 4D environment (3D airspace and time).

Fig. 2 also illustrates another significant feature of embodiments of the present invention, referred to as ISM (“Inertial Supplemental Modelling”), an approach to tracking the location of the UAV making use of INS data from the UAV’s navigation system in combination with opportunistic radio signals or known radio beacons (e.g., cell towers) to triangulate a position of the UAV. This is particularly useful in the case where there is a loss of GNSS signal, which is normally relied upon by UAV autopilots to know the location of the UAV in order for the autopilot to control the UAV to follow a flight path. That is, in GNSS-denied navigation, the ISM modelling function can continue to provide the UAV autopilot with the UAV’s position, enabling safe navigation to continue.

Fig. 3 outlines the various functional elements of a Flight Control System for implementing the functionality discussed above.

Specifically, fig. 3 shows that the FPOS can receive ADS-B information from a (constantly updated) internet feed, as well as ADS-B data directly from transponders (e.g., a transponder onboard the UAV or a ground-based transponder, for example at a launch site for the UAV). Weather management data is obtained from weather models and forecasts, as well as from live satellite and radar sources. This weather data is then provided to the UAV autopilot to allow the UAV to automatically avoid areas of dangerous weather. Other inputs include digital terrain elevation ‘maps’, radar information from the UAV, TCAS and GPWS logic (as discussed above) and input from the ISM (discussed immediately above). All of this information can then be used by the FPOS to deliver flight hazard avoidance information to the UAV’s autopilot (for example in the form of a flight hazard map as discussed above).

Also as shown in fig. 3, the UAV’s autopilot, in addition to using an onboard copy of the FPOS data (updated regularly by the FPOS), can take inputs directly from an onboard radar (for near-term collision avoidance), and an onboard transponder (providing ADS-B and FLARM inputs, which can also be provided to the FPOS). Finally, fig. 3 illustrates again the ISM concept, making use of for example, cell tower triangulation to enable continued operation in a GNSS (e.g., GPS) denied environment.

By operating in the manner discussed above, embodiments of the invention can make appropriate, automated decisions to optimize the flight path of a UAV (or other aerial vehicle) to account for various types of flight hazard, maintaining a safe separation at all times from other aircraft, terrain, weather and obstacles, helping to ensure safe operation of the UAV and mission success, whilst minimizing workload for the UAV pilot (and other users of the airspace) in the process of collision avoidance and airspace management.

The skilled person will understand that various modifications and additions can be made to the examples described above without departing from the spirit and scope of the present invention.

The following numbered paragraphs set out various aspects of the systems and methods disclosed herein:

1. An unmanned aircraft system, the system comprising: an unmanned aerial vehicle (UAV); and a Flight Control System for updating flight path data defining a flight path for the UAV, the UAV comprising autonomous flight controls that use the flight path data to control the flight of the UAV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including analysis of flight data for one or more other aircraft in airspace around the flight path to determine one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the UAV will bring the UAV closer than a predefined minimum distance from one of the other aircraft, the Flight Control System being operative to update the UAV flight path data to adjust the flight path of the UAV to be more than the predefined minimum distance from the predicted future position of the other aircraft. A system according to paragraph 1, wherein the flight data for the one or more other aircraft in airspace around the flight path comprises Automatic Dependent Surveillance (ADS) data. A system according to paragraph 1 or paragraph 2, wherein the flight data for the one or more other aircraft in airspace around the flight path comprises FLARM data. A system according to any one of the preceding paragraphs, wherein the flight data for the one or more other aircraft is obtained from any one or more of a transponder or transponders onboard the UAV; a transponder or transponders onboard one or more other UAVs within the unmanned aircraft system; one or more ground-based transponders, within the unmanned aircraft system, receiving the flight data directly from aircraft; and one or more internet sources, accessible to the unmanned aircraft system, providing a feed of the flight data. A system according to any one of the preceding paragraphs, wherein the flight data for the one or more other aircraft is updated every 5 seconds or less. A system according to any one of the preceding paragraphs, wherein the Flight Control System makes use of TCAS logic inputs when updating the flight path data, the flight path data being updated to avoid the UAV triggering any Traffic Advisories (TAs) or Resolution Advisories (RAs) by TCAS systems of other aircraft. A system according to any one of the preceding paragraphs, wherein the updated flight path data causes changes to the flight of the UAV including one or more of changes in altitude, the rate of climb, the rate of sink, the heading, and the speed of the UAV. 8. A system according to any one of the preceding paragraphs, wherein the analysis of flight hazards comprises analysis of other flight hazard types in addition to other aircraft, the Flight Control System updating the flight path data for the UAV, based on the combined impact of all of the analysed flight hazard types.

9. A system according to paragraph 8, wherein the other flight hazard types include one or more of: adverse weather conditions; restricted airspace and/or other predefined geographical areas to be avoided by the UAV; and permanent or temporary structures or objects.

10. A system according to any one of the preceding paragraphs, wherein the analysis of flight hazards comprises applying a risk grading to each of a plurality of airspace zones based on hazard data defining the presence or not of a flight hazard in a zone at a given time, the flight path data for the UAV being updated if the flight path of the UAV takes the UAV through an airspace zone at a time when the risk grading dictates that the UAV should avoid that airspace region at that time.

11. A system according to any one of the preceding paragraphs, comprising a plurality of UAVs.

12. A Flight Control System for updating flight path data defining a flight path for an aerial vehicle, wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including analysis of received flight data for one or more other aircraft in airspace around the flight path to determine one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the aerial vehicle will bring the aerial vehicle closer than a predefined minimum distance from one of the other aircraft, the Flight Control System is operative to update the aerial vehicle flight path data to adjust the flight path of the aerial vehicle to be more than the predefined minimum distance from the predicted future position of the other aircraft.

13. A Flight Control System according to paragraph 12, wherein the analysis of flight hazards comprises analysis of other flight hazard types in addition to other aircraft, the Flight Control System updating the flight path data for the aerial vehicle based on the combined impact of all of the analysed flight hazard types.

14. A computer-implemented method for updating flight path data defining a flight path for an aerial vehicle, the method comprising: receiving flight data for one or more other aircraft in airspace around the flight path; based on the received flight data for the one or more other aircraft, determining one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the aerial vehicle will bring the aerial vehicle closer than a predefined minimum distance from one of the other aircraft, updating the aerial vehicle flight path data to adjust the flight path of the aerial vehicle to ensure the aerial vehicle remains more than the predefined minimum distance from the predicted future position of the other aircraft.

15. A method according to paragraph 14, wherein the updated flight path data is used by an autopilot of an aerial vehicle to autonomously control the flight of the aerial vehicle.

16. An aircraft system, the system comprising: an aerial vehicle (AV), wherein the aerial vehicle is an Unmanned Aerial Vehicle, an eVTOL, or other Advanced Air Mobility (AAM) or Urban Air Mobility (UAM) system; and a Flight Control System for updating flight path data defining a flight path for the AV, the AV comprising autonomous flight controls that use the flight path data to control the flight of the AV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including analysis of flight data for one or more other aircraft in airspace around the flight path to determine one or more predicted future positions for each of the one or more other aircraft; and in the case where, based on the one or more predicted future positions for the other aircraft, the currently defined flight path for the AV will bring the AV closer than a predefined minimum distance from one of the other aircraft, the Flight Control System being operative to update the AV flight path data to adjust the flight path of the AV to be more than the predefined minimum distance from the predicted future position of the other aircraft. An unmanned aircraft system, the system comprising: an unmanned aerial vehicle (UAV); a Flight Control System for updating flight path data defining a flight path for the UAV, the UAV comprising autonomous flight controls that use the flight path data to control the flight of the UAV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including predicting a weather-related risk based on a combination of forecast weather data for airspace around a current flight path between the start point and the end point; and live weather data for airspace around the current flight path between the start point and the end point; in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the UAV will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the UAV to avoid the identified region. 18. A system according to paragraph 17, wherein forecast weather data is obtained periodically from one or more internet sources, accessible to the unmanned aircraft system.

19. A system according to paragraph 17 or paragraph 18, wherein live weather data is obtained periodically from one or more weather satellite and/or weather radar systems, accessible to the unmanned aircraft system. 0. A system according to any one of paragraphs 17 to 19, wherein live weather data is obtained using a radar onboard the UAV. 1. A system according to any one of paragraphs 17 to 20, wherein the forecast and/or live weather data is updated at least every 5 seconds or less. 2. A system according to any one of paragraphs 17 to 21, wherein the updated flight path data causes changes to the flight of the UAV including one or more of changes in altitude, the rate of climb, the rate of sink, the heading, and the speed of the UAV. 3. A system according to any one of paragraphs 17 to 22, wherein the analysis of flight hazards comprises analysis of other flight hazard types in addition to adverse weather, the Flight Control System updating the flight path data for the UAV based on the combined impact of all of the analysed flight hazard types. 4. A system according to paragraph 23, wherein the other flight hazard types include one or more of: other aircraft; restricted airspace and/or other predefined geographical areas to be avoided by the UAV; and permanent or temporary structures or objects. 5. A system according to any one of paragraphs 17 to 24, wherein the analysis of flight hazards comprises applying a risk grading to each of a plurality of airspace zones based on hazard data defining the presence or not of a flight hazard in a zone at a given time, the flight path data for the UAV being updated if the flight path of the UAV takes the UAV through an airspace zone at a time when the risk grading dictates that the UAV should avoid that airspace region at that time. A system according to any one of paragraphs 17 to 25, comprising a plurality of UAVs. A Flight Control System for updating flight path data defining a flight path for an aerial vehicle, wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including predicting a weather-related risk based on a combination of forecast weather data for airspace around a current flight path between the start point and the end point; and live weather data for airspace around the current flight path between the start point and the end point; in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the aerial vehicle will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the aerial vehicle to avoid the identified region. A Flight Control System according to paragraph 27, wherein the analysis of flight hazards comprises analysis of other flight hazard types in addition to adverse weather, the Flight Control System updating the flight path data for the aerial vehicle based on the combined impact of all of the analysed flight hazard types. A computer-implemented method for updating flight path data defining a flight path for an aerial vehicle between a start point and an endpoint, the method comprising: receiving forecast weather data for airspace around a current flight path; receiving live weather data for airspace around the current flight path between the start point and the end point; predicting a weather-related risk based on a combination of the forecast weather data and live weather data; and in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the aerial vehicle will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the aerial vehicle to avoid the identified region. A method according to paragraph 29, wherein the updated flight path data is used by an autopilot of an aerial vehicle to autonomously control the flight of the aerial vehicle. An aircraft system, the system comprising: an aerial vehicle (AV), wherein the aerial vehicle is an Unmanned Aerial Vehicle, an eVTOL, or other Advanced Air Mobility (AAM) or Urban Air Mobility (UAM) system; a Flight Control System for updating flight path data defining a flight path for the AV, the AV comprising autonomous flight controls that use the flight path data to control the flight of the AV to follow the flight path; wherein the Flight Control System is operative to update the flight path data periodically based on analysis of flight hazards in the airspace around the flight path; the analysis of flight hazards including predicting a weather-related risk based on a combination of: forecast weather data for airspace around a current flight path between the start point and the end point; and live weather data for airspace around the current flight path between the start point and the end point; in the case where the predicted weather-related risk for a region along the current flight path is above a predetermined threshold at a time when the AV will be in that region, the Flight Control System being operative to update the flight path data to adjust the flight path of the AV to avoid the identified region.

Claims

CLAIMS:

1. A Flight Control System for an aerial vehicle, the system comprising: an autopilot for autonomously controlling the flight of the aerial vehicle; a GNSS receiver for receiving GNSS signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle; and one or more radio receivers for receiving radio signals that can be used by the Flight Control System to calculate the current location of the aerial vehicle; the Flight Control System having a primary mode of operation in which a location of the aerial vehicle is calculated using the received GNSS signals, and provided to the autopilot for controlling the flight of the aerial vehicle; and the Flight Control System having a secondary mode of operation in which a location of the aerial vehicle is calculated using the received radio signals, and provided to the autopilot for controlling the flight of the aerial vehicle.

2. A system according to claim 1, wherein the secondary mode of operation of the Flight Control System is used when the GNSS receiver is unable to receive GNSS signals.

3. A system according to claim 1 or claim 2, wherein, in the secondary mode of operation, the location is calculated using triangulation of the received radio signals, trilateration of the received radio signals or a combination of both.

4. A system according to any one of claims 1 to 3, wherein the Flight Control System further comprises an inertial navigation system and where data from the inertial navigation system is used in conjunction with the radio signals in the secondary mode of operation to calculate the location of the aerial vehicle.

5. A system according to any one of claims 1 to 4, wherein the radio receiver(s) is/are configured to receive radio signals from cell towers of a cellular network.

6. A system according to claim 5, wherein the radio receiver(s) is/are configured to receive radio signals from cell towers of multiple cellular networks operated by different cellular network providers.

7. A system according to any one of claims 1 to 6, wherein the radio receiver(s) is/are configured to receive radio signals from VOR/TACAN transmitters at known locations.

8. A system according to any one of claims 1 to 7, wherein the radio receiver(s) is/are configured to receive radio signals from an array of radio beacons at a predetermined location.

9. A system according to claim 8, wherein the array of radio beacons is at a predetermined landing location to assist landing of the aerial vehicle at the landing location.

10. A system according to claim 8 or claim 9, comprising 3 to 24 radio beacons.

11. A system according to any one of claims 1 to 10, wherein the aerial vehicle is an unmanned aerial vehicle.

12. A system for determining the location of an aerial vehicle, the system comprising an array of ground antennas for detecting radio signals to/from the aerial vehicle, the detected radio signals being employed to calculate the location of the aerial vehicle using triangulation of the detected radio signals, trilateration of the detected radio signals or a combination of both.

13. A method for use in the autonomous control of the flight of an aerial vehicle, wherein in normal operation of the aerial vehicle a current location of the vehicle is calculated from GNSS signals, the method comprising, in the absence of GNSS signals, calculating a location of the aerial vehicle using opportunistic radio signals and/or radio signals from known radio beacons.

14. A method for determining the location of an aerial vehicle, the method using an array of ground antennas and comprising detecting, with the array of ground antennas, one or more radio signals to/from the aerial vehicle, and using the detected radio signal(s) to calculate the location of the aerial vehicle through triangulation of the detected radio signals, trilateration of the detected radio signals or a combination of both.