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EP-4154236-B1 - VERIFICATION OF UNMANNED AERIAL VEHICLE ADS-B RECEIVER OPERABILITY

EP4154236B1EP 4154236 B1EP4154236 B1EP 4154236B1EP-4154236-B1

Inventors

  • KOZLER, Shirley
  • JONES, Brandon L.

Dates

Publication Date
20260513
Application Date
20210720

Claims (15)

  1. A non-transitory computer-readable medium having logic stored thereon that, in response to execution by one or more processors of a computing system, cause the computing system to perform actions for verifying operability of an automatic dependent surveillance-broadcast, ADS-B, receiver, the actions comprising: receiving, by the computing system, ADS-B data obtained by the ADS-B receiver included in a first unmanned aerial vehicle,(UAV (101-A), the ADS-B data representative of ADS-B messages broadcast by traffic within a reception range of the ADS-B receiver during a first period of time (T1); estimating, by the computing system, a traffic environment for a service area spanning, at least in part, a first operating area of the first UAV during the first period of time, wherein the traffic environment is estimated based, at least in part, on the ADS-B data obtained by the first UAV and additional traffic data different from the ADS-B data; determining, by the computing system, an expected observed traffic of the first UAV during the first period of time based on the estimated traffic environment; and verifying, by the computing system, operability of the ADS-B receiver of the first UAV based on a comparison between the expected observed traffic of the first UAV and the traffic associated with the ADS-B data received by the ADS-B receiver of the first UAV.
  2. The non-transitory computer-readable medium of claim 1, wherein the ADS-B receiver is an ADS-B In only receiver, and wherein the first UAV does not include an ADS-B Out capable transponder; and/or wherein the ADS-B messages include at least one of a unique identifier, a latitude, a longitude, an altitude, or a speed of one or more aircraft included in the traffic at one or more instances of time within the first period of time.
  3. The non-transitory computer-readable medium of claim 1, wherein the additional traffic data corresponds to additional ADS-B data obtained by a plurality of ADS-B receivers, each associated with a respective UAV included in a plurality of UAVs (101-A, 101-B) operating within the service area during the first period of time.
  4. The non-transitory computer-readable medium of claim 3, wherein the additional ADS-B data of the plurality of UAVs is segmented into different tracks of observed traffic during the first period of time, each of the different tracks associated with a respective one of the plurality of UAVs.
  5. The non-transitory computer-readable medium of claim 4, wherein the different tracks further include a first track of the observed traffic associated with the ADS-B data of the first UAV.
  6. The non-transitory computer-readable medium of claim 4, wherein estimating the traffic environment further comprises: combining each of the different tracks of the observed traffic into a singular estimate of the traffic environment.
  7. The non-transitory computer-readable medium of claim 6, wherein the different tracks of the observed traffic are combined using at least one of a probabilistic Bayesian estimator or threshold matching to generate the singular estimate of the traffic environment; and optionally, wherein the probabilistic Bayesian estimator is a Kalman Filter, an Extended Kalman Filter, or an Unscented Kalman Filter.
  8. The non-transitory computer-readable medium of claim 1, wherein the comparison corresponds to determining one or more comparison metrics comparing the expected observed traffic and the traffic associated with the ADS-B data, and wherein the operability of the ADS-B receiver of the first UAV is verified as nominal when at least one of the one or more comparison metrics is within a threshold range.
  9. The non-transitory computer-readable medium of claim 8, wherein determining the expected observed traffic of the first UAV includes: identifying one or more aircraft, included in the estimated traffic environment, within the reception range of the ADS-B receiver of the first UAV at one or more instances of time within the first period of time based, at least in part, on a flight path of the first UAV during the first period of time.
  10. The non-transitory computer-readable medium of claim 9, wherein a difference between a total number of aircraft expected to be observed by the first UAV based on the one or more aircraft identified and an actual total number of aircraft observed based on the traffic associated with the ADS-B data is included in the one or more comparison metrics; or wherein a difference between an expected observation duration of each of the one or more aircraft identified from the estimated traffic environment and an actual observation duration of the one or more aircraft determined from the ADS-B data is included in the one or more comparison metrics.
  11. The non-transitory computer-readable medium of claim 1, wherein verifying operability of the ADS-B receiver of the first UAV is determined in substantially real time.
  12. The non-transitory computer-readable medium of claim 1, wherein the actions further comprise: receiving, by the computing system, the ADS-B data and the additional traffic data in real time; identifying, by the computing system, a first aircraft expected to be observed by the first UAV at a first time instance based on the estimated traffic environment; and flagging the ADS-B receiver of the first UAV as subnominal when the ADS-B data does not include an ADS-B message corresponding to the first aircraft at the first time instance; and determining an action to be taken to address the ADS-B receiver of the first UAV being subnominal.
  13. The non-transitory computer-readable medium of claim 1, wherein the actions further comprise: comparing the estimated traffic environment to third party aggregated ADS-B data to verify accuracy of the estimated traffic environment.
  14. A computer-implemented method for verifying operability of an automatic dependent surveillance-broadcast, ADS-B, receiver, the method comprising: receiving ADS-B data obtained by the ADS-B receiver included in a first unmanned aerial vehicle, UAV, (101-A), the ADS-B data representative of ADS-B messages broadcast by traffic within a reception range of the ADS-B receiver during a first period of time (T1); estimating a traffic environment for a service area spanning, at least in part, a first operating area of the first UAV during the first period of time, wherein the traffic environment is estimated based, at least in part, on the ADS-B data obtained by the first UAV and additional traffic data different from the ADS-B data; determining an expected observed traffic of the first UAV during the first period of time based on the estimated traffic environment; and verifying operability of the ADS-B receiver of the first UAV based on a comparison between the expected observed traffic of the first UAV and the traffic associated with the ADS-B data received by the ADS-B receiver of the first UAV.
  15. A system, comprising: a plurality of unmanned aerial vehicles, UAVs, (101-A) configured to operate within a service area during a first period of time (T1), wherein each of the plurality of UAVs include an automatic dependent surveillance-broadcast, ADS-B, receiver to receive ADS-B data representative of ADS-B messages broadcast by traffic within a reception range of the ADS-B receiver when the plurality of UAVs are in operation; a traffic estimator (220) configured to collectively receive the ADS-B data of the plurality of UAVs as collective ADS-B data and estimate a traffic environment for the first period of time spanning, at least in part, a first operating area of a first UAV included in the plurality of UAVs, wherein the estimated traffic environment is based, at least in part, on the collective ADS-B data; and an ADS-B health monitor (230) configured to verify operability of the ADS-B receiver of the first UAV included in the plurality of UAVs based on a comparison between expected observed traffic of the first UAV, determined from the estimated traffic environment, and the traffic associated with the ADS-B data received by the ADS-B receiver of the first UAV.

Description

TECHNICAL FIELD This disclosure relates generally to Automatic Dependent Surveillance-Broadcast (ADS-B) receivers, and in particular but not exclusively, relates to operability verification of ADS-B In receivers of unmanned aerial vehicles (UAVs). BACKGROUND INFORMATION Automatic Dependent Surveillance-Broadcast (ADS-B) is a satellite-derived aircraft location system that combines an aircraft's positioning source, aircraft avionics, and ground infrastructure to create an accurate surveillance interface between aircrafts and air traffic control. ADS-B equipment is broadly categorized as ADS-B Out and ADS-B In, which respectively correspond to the capability to output and receive ADS-B data. Aircraft equipped with ADS-B Out transponders, for example, are capable of broadcasting ADS-B data indicative of aircraft position, altitude, and velocity vector at rates greater than traditional radar-based surveillance systems to enable accurate, real-time, and dynamic tracking of the broadcasting aircraft. ADS-B data may be of particular importance to unmanned aerial vehicles (UAVs), which are becoming increasingly popular in general and provide opportunities for transportation of goods between physical locations (e.g., from retailer to consumer). A UAV is a vehicle capable of travel without a physically-present human operator that may be capable of operating, at least partially, autonomously. When a UAV operates in a remote-control mode, a pilot or driver that is at a remote location can control the UAV via commands that are sent to the UAV via a wireless link. When the UAV operates in an autonomous mode, the unmanned vehicle typically moves based on pre-programmed navigation waypoints, dynamic automation systems, or a combination thereof. Further, some unmanned vehicles can operate in both a remote-control mode and an autonomous mode, and in some instances may do so simultaneously. For instance, a remote pilot or driver may wish to leave navigation to an autonomous system while manually performing another task. EP 2894623 A1 discloses a method of matching flight data from multiple sources, including receiving a parametric flight data set for a given flight where the parametric flight data set includes a number of data features, receiving operational flight data sets related to a number of flights where the operational flight data sets include a number of data features, and determining a matching operational flight data set for the parametric flight data set. BRIEF DESCRIPTION OF THE DRAWINGS The claims define the matter for protection. Non-limiting and non-exhaustive embodiments of the invention are described with reference to the following figures, wherein like reference numerals refer to like parts throughout the various views unless otherwise specified. Not all instances of an element are necessarily labeled so as not to clutter the drawings where appropriate. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles being described. FIG. 1 illustrates an aerial map of a geographic area at an instance of time, in accordance with an embodiment of the disclosure.FIG. 2 illustrates a flow chart for continuously monitoring ADS-B receivers of a plurality of UAVs via a traffic estimator and an ADS-B health monitor, in accordance with an embodiment of the disclosure.FIG. 3 illustrates a flow chart for verifying ADS-B operability with an ADS-B monitor, in accordance with an embodiment of the disclosure.FIG. 4 illustrates a functional block diagram of a computing system including a plurality of UAVs, an external computing device, and a third party data provider, in accordance with an embodiment of the disclosure. DETAILED DESCRIPTION Embodiments of a system, apparatus, and method for verification of unmanned aerial vehicle ADS-B receiver operability are described herein. In the following description numerous specific details are set forth to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the techniques described herein can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring certain aspects. Some portions of the detailed description that follow are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magn