Patent Description:
A ground radio station (GRS) for a command and control (C2) link system is disclosed. In embodiments, the GRS includes a communications interface comprising antenna elements and transceivers. The GRS includes a traffic manager for establishing and maintaining, in conjunction with the communications interface C2 links to air radio stations (ARS) aboard unmanned aircraft systems (UAS) operating within the coverage area and/or transmission range of the GRS. When the number n of UAS in service to the GRS meets or exceeds the total number N of C2 channels allocated to the GRS, the traffic manager establishes contingency C2 links whereby two or more UAS share (e.g., via time slotting/slicing) a single C2 channel. The GRS includes a fusion engine for tracking the wait time of each UAS waiting on a contingency C2 link (e.g., sharing a C2 channel) until a full C2 link on an unshared C2 channel is available. The fusion engine also generates dynamic variables S by tracking the number n of UAS in service over time, where the dynamic variable S represents the probability distribution over time of the number n of UAS in service to the GRS. The fusion engine generates normalized congestion metrics specific to the GRS by fusing the collected wait times and the dynamic variables.

In some embodiments, the congestion metrics include time metrics, e.g., an expected wait time for a UAS intending to establish a C2 link to the GRS.

In some embodiments, the time metrics include time submetrics, e.g., a standard deviation of the expected wait time and a maximum wait time.

In some embodiments, the congestion metrics include channel availability metrics, e.g., an expected number of available C2 channels.

In some embodiments, the channel availability metrics include channel availability submetrics, e.g., a standard deviation of the expected number of available C2 channels and an expected idle time, e.g., the duration or likelihood the GRS has no UAS in service and this all C2 channels are available.

In some embodiments, the congestion metrics identify and track the duration of various GRS operating states, e.g., a nominal state of the GRS, wherein the dynamic distribution S of UAS in service is less than the number N of available C2 channels; an off-nominal or saturated state where S greater than or equal to N but still less than W, or the maximum number of UAS servable by the GRS via full and contingency C2 links; and a critical or danger state wherein S is greater than or equal to W, e.g., the GRS has no spectrum resources available for either full or contingency C2 links.

In some embodiments, the fusion engine collects the wait times of UAS waiting for a contingency C2 link, e.g., to a critical-state GRS.

In some embodiments, the fusion engine directs the GRS to signal one or more UAS in service to request the UAS transfer its C2 link to a different GRS to free up spectrum resources.

In some embodiments, the fusion engine forwards the congestion metrics and submetrics to a centralized spectrum arbitrator.

A method for generating command and control (C2) congestion metrics at a ground radio station (GRS) of a C2 link system is also disclosed. In embodiments, the method includes establishing, via the GRS, C2 links to unmanned aircraft systems (UAS) within the coverage area or transmission range of the GRS, each C2 link on a C2 channel allocated to the GRS. The method includes, when the number n of UAS in service to the GRS meets or exceeds the number of N C2 channels allocated to the GRS, establishing contingency C2 links to two or more UAS on a shared C2 channel. The method includes collecting, via a fusion engine of the GRS, wait times for each UAS waiting on a contingency C2 link (e.g., on a shared C2 channel) for a standard C2 link on an unshared C2 channel. The method includes generating, via the fusion engine, dynamic variables S tracking the number n of UAS in service to the GRS over time, where the dynamic variable S represents the probability distribution over time of the number n of UAS in service to the GRS. The method includes generating congestion metrics for the GRS by fusing the wait times and dynamic variables.

In some embodiments, the method includes generating time metrics, e.g., an expected wait time, and/or time submetrics, e.g., a standard deviation of the expected wait time and a maximum wait time.

In some embodiments, the method includes generating C2 channel availability metrics, e.g., an expected number of available C2 channels, and/or C2 channel availability submetrics, e.g., a standard deviation of the expected number of available C2 channels and an expected idle time.

In some embodiments, the method includes identifying one or more GRS operating states, e.g., a nominal state of the GRS, wherein S < N; an off-nominal/saturated state of the GRS, wherein S ≥ N and S < W, and W is an integer corresponding to the maximum number of UAS concurrently servable by the GRS via the at least one set of contingency C2 links; and a critical/danger state of the GRS , wherein S ≥ W.

In some embodiments, the method includes signaling one or more UAS in service based on the congestion metrics, e.g., to request the UAS transfer its C2 link to another UAS to free up spectrum resources.

In some embodiments, the method includes transmitting the congestion metrics to a centralized spectrum arbitrator.

Broadly speaking, embodiments of the inventive concepts disclosed herein are directed to a software-based fusion engine to ground radio stations (GRS) managing and monitoring the command and control (C2) operations of unmanned aircraft systems (UAS), e.g., via control and non-payload communications (CNPC) waveforms. The fusion engine continually tracks critical data points related to C2 traffic management and the capacity of each GRS (e.g., in a network of GRS) to effectively serve its constituent UAS. By fusing the collected data points, the fusion engine can determine if its GRS is oversubscribed or undersubscribed-i.e., if the GRS has fewer or greater radio frequency (RF) spectrum resources than it actually needs. Further, central control facilities managing the CNPC network of GRS can control and allocate spectrum access on a dynamic and proactive basis. Corner cases can be effectively addressed to optimize the capacity of each individual GRS and the network as a whole, while individual UAS operators can use congestion metrics to more effectively plan flight paths and flight times to optimize network capacity. Normalized and unified congestion metrics and submetrics can accurately represent spectrum congestion and usage across multiple GRS across the C2 link system regardless of the individual hardware/software components or allocated spectrum resources of any individual GRS.

Referring to <FIG>, an operating environment <NUM> (e.g., C2 link system) for unmanned aircraft systems (UAS) <NUM> is disclosed. The operating environment <NUM> may include ground radio stations <NUM>, <NUM>, and <NUM> (GRS), respectively serving coverage areas <NUM>, <NUM>, and <NUM>, and centralized spectrum arbitrator <NUM>.

In embodiments, the operating environment <NUM> may comprise a collection of interconnected coverage areas <NUM>, <NUM>, <NUM> within which the UAS <NUM> may operate. For example, the UAS <NUM> may file a flight plan providing for operations along a flight path <NUM> between an origin point <NUM> and a destination <NUM>. The flight path <NUM> may direct the UAS <NUM> along, or proximate to, a predetermined route through the coverage area <NUM>, into the coverage area <NUM>, and finally into the coverage area <NUM> within which the destination <NUM> may be located.

In embodiments, while operating in the coverage area <NUM>, the GRS <NUM> serving that coverage area may establish and maintain a command and control (C2) link <NUM> to the UAS <NUM> as well as any other UAS operating within the coverage area <NUM> or otherwise in service to the GRS <NUM> (e.g., UAS within transmission range of the GRS). For example, the coverage areas <NUM>, <NUM>, <NUM> may be defined by a geographical area within a predetermined transmission range of their corresponding GRS <NUM>, <NUM>, <NUM>. The bounds of a coverage area may include a predetermined altitude or a temporal boundary. For example, the operating environment <NUM> may include peripheral areas <NUM>, <NUM> within the transmission range of more than one GRS or coverage area (e.g., the peripheral area <NUM> within the range of GRS <NUM>, <NUM>/coverage areas <NUM>, <NUM> and the peripheral area <NUM> within the range of GRS <NUM>, <NUM>/coverage areas <NUM>, <NUM>); accordingly, the peripheral area <NUM> may be served by the GRS <NUM> at some predetermined times and by the GRS <NUM> during other predetermined times.

In embodiments, the GRS <NUM> may use the C2 link <NUM> to transmit operating commands to, and receive diagnostic information from, the UAS <NUM>. For example, the GRS <NUM> may use the C2 link <NUM> to monitor the progress of the UAS <NUM> along its flight path <NUM> via the C2 link <NUM>, issuing commands to guide the UAS away from areas where communications may be less reliable or where atmospheric or other conditions may impede the mission of the UAS. When the flight path <NUM> of the UAS <NUM> passes out of the coverage area <NUM> into the coverage area <NUM> (e.g., when the UAS (102a) is within the peripheral area <NUM>), the UAS may be "handed off" from the GRS <NUM>, establishing a new C2 link (124a) to the GRS <NUM> (e.g., when the C2 signal transmitted by the GRS <NUM> is sufficiently strong for C2 operations, or stronger than the signal transmitted by the GRS <NUM>) while terminating the C2 link <NUM> to the GRS <NUM>, seamlessly continuing operations within the coverage area <NUM>.

In embodiments, each GRS <NUM>, <NUM>, <NUM> may have a finite amount of spectrum resources for the maintenance of C2 links <NUM> to each UAS <NUM> operating within its coverage area <NUM>, <NUM>, <NUM>. For example, the centralized spectrum arbitrator <NUM> (e.g., central server) may manage and allocating spectrum resources to each individual GRS <NUM>, <NUM>, <NUM> and throughout the operating environment <NUM>.

In embodiments, the UAS <NUM> may be autonomous or semi-autonomous, e.g., controlled in full or in part by a remote operator <NUM>. For example, the remote operator <NUM> may issue C2 commands via the GRS <NUM>, or may serve as a backup controller if one or more autonomous systems fail aboard the UAS <NUM> or must be overwritten. Similarly, the centralized spectrum arbitrator <NUM> may in turn serve as a backup operator of the UAS <NUM> (e.g., via C2 commands over the C2 link <NUM> issued by a human in the loop (HITL)) should the remote operator <NUM> become incapacitated.

Referring now to <FIG>, the GRS <NUM> is disclosed. The GRS <NUM>, <NUM> of <FIG> may be implemented and may function similarly to the GRS <NUM>.

In embodiments, referring in particular to <FIG>, the GRS <NUM> may include a communications interface, e.g., directional, omnidirectional, and/or sectoral antenna elements <NUM> and one or more transceivers <NUM>, for managing communications with the UAS (<NUM>, <FIG>) operating within its coverage area (<NUM>, <FIG>) or, e.g., within its transmission range. For example, the transceivers <NUM> may be in communication with, or may be incorporated into, control processors <NUM> (e.g., the GRS <NUM> may be a partially or fully software-defined radio (SDR) system). The GRS <NUM> may establish C2 links (<NUM>, <FIG>) and communicate with its constituent UAS <NUM> via control and non-payload communication (CNPC) waveforms.

In embodiments, the GRS <NUM> may include a traffic manager <NUM> and fusion engine <NUM>. For example, the traffic manager <NUM> and fusion engine <NUM> may be implemented as software-based modules configured for execution on the control processors <NUM> of the GRS <NUM>. The traffic manager <NUM> may be responsible for establishing, maintaining, and/or terminating C2 links <NUM> with each UAS <NUM> in service to the GRS <NUM> (e.g., within the coverage area <NUM> or within transmission range of the GRS).

The fusion engine <NUM> may continually capture data points relevant to each constituent UAS <NUM> served by the GRS <NUM>, fusing the data points to generate congestion metrics and forwarding the congestion metrics to the centralized spectrum arbitrator <NUM>. The centralized spectrum arbitrator <NUM> may analyze congestion metrics from the GRS <NUM> and other GRS (<NUM>, <NUM>) operating within the operating environment <NUM> in order to anticipate likely congestion issues before they happen and proactively implement dynamic spectrum access across the network of GRS. For example, the centralized spectrum arbitrator <NUM> may redistribute spectrum resources such that high-demand GRS are allocated adequate spectrum resources and low-demand GRS are not allocated more spectrum resources than they actually need.

Referring also to <FIG>, the GRS <NUM> may be allocated a finite amount of spectrum resources (e.g., by the centralized spectrum arbitrator <NUM>). For example, the GRS <NUM> may be allocated an integer number N of C2 channels 212a,. 212n (e.g., equivalent segments in an allocated CNPC frequency band) and may therefore be configured to simultaneously serve N UAS (<NUM>, <FIG>; e.g., maintain a full C2 link (<NUM>, <FIG>) with N UAS, via the traffic manager <NUM>) at any given time.

In embodiments, the GRS <NUM> may actually serve (e.g., maintain C2 links <NUM> with) an integer number n of different UAS <NUM> operating within its coverage area (<NUM>, <FIG>) at any given time. For example, while N may remain consistent (e.g., between network restructurings or reallocations of spectrum resources throughout the operating environment (<NUM>, <FIG>)), n will vary over time according to traffic patterns and/or flight plans (e.g., throughout the day or even within an hour or two). The relationship between n and N, and the dynamic variable S, representing the probability distribution of n over time, may be crucial to understanding whether the GRS <NUM> is oversubscribed or undersubscribed.

In embodiments, the relationship between the GRS <NUM> and its constituent UAS <NUM> may be modelled as a queue by which the changing relationship between n and N, the dynamic variable S, and their effect on the GRS <NUM> may be monitored. For example, the GRS <NUM> may be associated with an arrival rate λ, or the rate at which new UAS <NUM> enter the coverage area <NUM> of the GRS <NUM> and must switch over to the GRS, e.g., establish a C2 link <NUM> to the GRS. Similarly, the GRS <NUM> may be associated with a service rate µ, or the rate at which UAS <NUM> currently linked/in service to the GRS <NUM> enter a new coverage area or transmission range, and thus switch over to a new GRS, terminating the C2 link <NUM> to the GRS <NUM>. It follows broadly, with respect to the ratio λ:µ between the arrival rate λ and the service rate µ, that a higher ratio λ:µ may be conducive to bottlenecking or oversubscription, and a lower ratio λ:µ may be conducive to undersubscription.

In embodiments, the GRS <NUM> may be associated with a nominal (e.g., noncritical) state corresponding to S < N, e.g., when the probability distribution S of the number n of UAS <NUM> currently served by the GRS <NUM> is less than the number N of C2 channels 212a-n allocated to the GRS, or the maximum number N of UAS the GRS can simultaneously serve while maintaining the nominal state. When in the nominal state, any new UAS <NUM> entering the coverage area <NUM> of the GRS <NUM> may establish a C2 link <NUM> to the GRS on an otherwise unoccupied/unused C2 channel 212a-n.

In embodiments, increasing C2 traffic may cause the GRS <NUM> to transition from the nominal state to an off-nominal (e.g., saturated) state corresponding to N ≤ S < W, where W is the maximum integer number of UAS <NUM> supportable by the GRS <NUM> in the off-nominal state. For example, a benefit of the CNPC waveform is that it allows C2 channels 212a-n to be split such that the GRS <NUM> can establish C2 contingency links 214a-b to two different UAS 102b-c on a single C2 channel 212a. A contingency link 214a-b may require alterations to the CNPC frame scheduling structure and may require the two UAS 102b-c to share the C2 channel 212a in interleaving time periods, providing each UAS 102b-c with half the communication time the UAS would otherwise have via a standard C2 link <NUM>. Contingency links 214a-b may be intended as a solely temporary measure, until another UAS <NUM> served by the GRS <NUM> switches over to a different GRS and S ≤ N, restoring the nominal state and allowing each UAS 102b-c to establish a standard/full C2 link <NUM> on a distinct C2 channel 212a-n. If, for example, the GRS <NUM> is required to share many C2 channels 212a-n, this may indicate oversubscription of the GRS (e.g., the GRS may have insufficient spectrum resources to handle its contingent of UAS traffic at one or more times). Similarly, if one or more C2 channels 212a-n remain shared for long periods of time before another C2 channel is released, this may also indicate oversubscription. In embodiments, W may be equal to 2N, e.g., assuming each C2 channel 212a-n is capable of being shared by two contingency links 214a-b. However, in the event some C2 channels 212a-n are not shareable, W may be less than 2N; similarly, in the event some C2 channels are shareable by more than two UAS <NUM>, 102b-c, W may be more than 2N.

In embodiments, the GRS <NUM> may further be associated with a critical or danger state, whereby S > W. For example, n and S may include not only the UAS <NUM>, 102b-c currently served by the GRS <NUM> (e.g., via standard C2 links <NUM> and/or contingency C2 links 214a-b) but other UAS 102d entering the coverage area <NUM> of the GRS <NUM> that must establish a C2 link to the GRS <NUM>. If, for example, every C2 channel 212a-n is committed to a C2 link <NUM> or a pair of contingency C2 links 214a-b, there may be no spectrum resources available to the UAS 102d. Accordingly, the UAS 102d may have to wait until a C2 channel 212a-n is available, but the resulting loss of C2 signaling for the UAS 102d is an unacceptable state and may create a threat level. While a very brief waiting period may not be inherently dangerous, the longer the UAS 102d waits for an open channel, the higher the probability of lost connectivity.

Accordingly, the fusion engine <NUM> may enable dynamic spectrum access across the operating environment <NUM>, such that the GRS <NUM>, and every other GRS within the operating environment, rarely enters the critical state (or, e.g., is rarely expected to be based on its anticipated UAS traffic). Similarly, even the off-nominal state described above, where every UAS 102b-c can communicate with the GRS <NUM> but some must do so via degraded contingency links 214a-b (which may not provide full C2 services and may further degrade), should be avoided or reduced to a low probability via proper deployment of the fusion engine <NUM>.

In embodiments, the fusion engine <NUM> may track congestion at the GRS <NUM> by capturing one or more data points relevant to the capacity of the GRS to serve its constituent UAS <NUM>, 102b-c over time, or at any given time (e.g., all UAS maintaining a C2 link <NUM> to the GRS, and/or any entering UAS 102d intending to establish a new C2 link <NUM> for operations within the coverage area <NUM> of the GRS). For example, the fusion engine <NUM> may track the wait time T of each UAS 102b-c waiting for a standard C2 link <NUM>. For example, when the GRS <NUM> is in the off-nominal state, insufficient C2 channels 212a-n may be allocated to the GRS for every UAS 102b-c to establish a standard C2 link <NUM> on its own C2 channel. Accordingly, the one or more UAS 102b-c must wait on a C2 contingency link 214a-b before sufficient resources exist to establish standard C2 links <NUM> to both UAS. As both UAS 102b-c are waiting on a shared C2 channel 212n, the wait times of both UAS may be tracked independently (e.g., two wait times). Similarly, if the GRS <NUM> is in the critical state, the duration the entering UAS 102d must wait before establishing a link of any kind (e.g., either a standard C2 link <NUM> or a contingency link 214a-b) to the GRS <NUM> may also be tracked.

In embodiments, the fusion engine <NUM> may further track the exact number of C2 channels 212a-n shared at any given time (e.g., when the GRS <NUM> is either off-nominal or critical). Similarly, the fusion engine <NUM> may track S, or the number of UAS <NUM>, 102b-c served by the GRS <NUM> at any given time. For example, from these two sets of data points may be derived the relationship between the number of shared C2 channels 212an and the number N of total C2 channels allocated to the GRS, as well as channel availability (e.g., E [ (N-n) ] ) metrics and submetrics tracking relationship between the number n of UAS <NUM>, 102b-c in service and the number N of total C2 channels (e.g., and therefore the number (N-n) of available C2 channels). In some embodiments, channel availability metrics and/or submetrics may track the number of C2 channels 212a-n shared by two or more UAS 102b-c, and the total duration that each C2 channel is shared.

In embodiments, the fusion engine <NUM> may periodically (e.g., hourly, daily, according to some other predetermined time interval) fuse collected wait times and dynamic variables into congestion metrics, forwarding the congestion metrics to the centralized spectrum arbitrator <NUM>. For example, a first set of congestion metrics may include time metrics and submetrics based on collected wait times, which may include (but are not limited to, an expected wait time, or E [T]. For example, E [T] may be a statistical mean wait time of a UAS 102b waiting on a contingency C2 link 214a-b (e.g., and sharing a C2 channel 212n with another UAS 102c) until sufficient spectrum resources are available to establish a standard C2 link <NUM>. Similarly, an expected wait time E [T'] may be a statistical mean wait time T' for an entering UAS 102d (e.g., when the GRS <NUM> is in the danger state) until either a contingency C2 link 214a-b or standard C2 link <NUM> is available.

In embodiments, congestion submetrics based on, or derived from, the expected wait time E [T] may include a standard deviation σE[T] of E [T]; for example, a higher standard deviation σE[T] may be associated with a higher degree of urgency. Similarly, congestion submetrics may include a maximum wait time Tmax, e.g., the highest recorded wait time within a given timespan.

In embodiments, the fusion engine <NUM> may similarly generate E [ (N-n) ] metrics and submetrics related to the availability of C2 channels 212a-n over time, e.g., the relationship between the total number N of allocated C2 channels and the changing number of n UAS in service over time (and thus the number of unoccupied/unused C2 channels). For example, the channel availability metric E [ (N-n) ] may correspond to an expected number of C2 channels 212a-n available over time. In embodiments, channel availability submetrics may include (but are not limited to) a standard deviation of E [ (N-n) ] and a mean idle time corresponding to the duration that n = <NUM>, or when no UAS 102b-c are in service to the GRS <NUM>.

In embodiments, congestion metrics generated by the fusion engine <NUM> may provide the centralized spectrum arbitrator <NUM> with the ability to observe and anticipate hourly or daily traffic patterns for the GRS <NUM> (as well as every other GRS in the operating environment <NUM> reporting via a fusion engine <NUM>).

Referring now to <FIG>, the operating environment <NUM> is disclosed. In embodiments, the UAS 102d entering the coverage area <NUM> may need to establish a C2 link <NUM> to the GRS <NUM>. However, the GRS <NUM> may be in an off-nominal or critical state such that sufficient spectrum resources may not immediately permit this. For example, the UAS 102b-c may share a C2 channel 212n via contingency C2 links 214a-b, e.g., for a duration exceeding a normal shared-channel wait time for the GRS <NUM> at that time of day. Further, the UAS 102c may be within the peripheral area <NUM> between the coverage areas <NUM>, <NUM>, and its entry into the coverage area <NUM> may be imminent.

In embodiments, the GRS <NUM> may signal the UAS 102c to determine if the UAS 102c is able to prematurely establish a C2 link (124a) to the GRS <NUM> serving the coverage area <NUM> and, if so, request the UAS execute the switchover (although, e.g., the UAS may not be required to execute the switchover unless mandated by the centralized spectrum arbitrator <NUM>). If, for example, the UAS 102c can receive a sufficiently strong signal from the GRS <NUM>, the UAS 102c may attempt to switch over to that GRS sooner than it ordinarily would (e.g., the UAS 102c may still be fully or partially within the coverage area <NUM>). Should the UAS 102c successfully switch over to the GRS <NUM>, the UAS may terminate its contingency C2 link 214b to the GRS <NUM>, freeing up spectrum resources that may be used to establish either a standard C2 link <NUM> (or a contingency C2 link, if a standard C2 link is not yet possible) to the entering UAS 102d.

In some embodiments, use of the congestion metrics and/or submetrics may be affected by special circumstances and/or corner cases. For example, while increasing N (the number of C2 channels 212a-n allocated to the GRS <NUM>) may be a standard response to congestion metrics indicating oversubscription of the GRS, if the GRS <NUM> is located at or serves an airport (e.g., an origin point (<NUM>, <FIG>)), increasing N may result in bottlenecking at other GRS (<NUM>) within the operating environment <NUM>. Instead, the centralized spectrum arbitrator <NUM> may space takeoffs from the airport proximate to the GRS <NUM> to regulate CNPC traffic flow into the operating environment <NUM>, as wait time on the ground or runway is not critical.

In some embodiments, congestion metrics may indicate an oversubscribed, as well as an undersubscribed, GRS. In fairly redistributing spectrum resources where they are most needed, the central control facility may allocate spectrum resources away from undersubscribed GRS (e.g., where S consistently fails to approach N, or does not consistently remain above N) in order to allocate more spectrum resources to high-demand GRS where bottlenecking may occur due to a lack of available C2 channels 212a-n.

Referring to <FIG>, the graph <NUM> is disclosed. The graph <NUM> may track S (y-axis <NUM>), or the probability distribution of the number n of UAS (<NUM>, <FIG>) simultaneously served by the GRS (<NUM>, <FIG>) over time (x-axis <NUM>).

In embodiments, the fusion engine (<NUM>, <FIG>) may track S over time (<NUM>) as UAS <NUM> enter and leave the coverage area (<NUM>, <FIG>) served by the GRS <NUM>, establishing and then terminating standard C2 links (<NUM>, <FIG>) or contingency C2 links (212a-b, <FIG>) as spectrum resources allow. For example, the graph <NUM> may correspond to a time window (e.g., an hour), beginning at an initial time T<NUM> (<NUM>), wherein UAS traffic handled by the GRS <NUM> increases on a roughly linear basis. At a time T<NUM> (<NUM>), the GRS <NUM> may enter the off-nominal state as S exceeds N and approaches W, and at a time T<NUM> (<NUM>) the GRS may enter the critical state as S exceeds W. Accordingly, the fusion engine <NUM> may track, over the total time represented by the graph <NUM>, the time portions <NUM>, <NUM>, <NUM> during which the GRS <NUM> is respectively in the nominal state, the off-nominal state, and the critical state.

Referring now to <FIG>, the probability distribution function <NUM> (PDF) is disclosed. The PDF <NUM> may plot the likely saturation f(S) of the GRS (<NUM>, <FIG>) over a predetermined time period, e.g., partially based on the graph <NUM> of the distribution S of UAS (<NUM>, <FIG>) in service to the GRS overtime. The PDF <NUM> may include x-axis <NUM> corresponding to S and PDF curve <NUM> corresponding to f(S).

In embodiments, the PDF curve <NUM> may represent an ideal, or at least an effective, deployment of the fusion engine (<NUM>, <FIG>) wherein S is most likely less than N and the likelihood of S exceeding W (<NUM>) is extremely low. For example, the law of large numbers suggests that the PDF curve <NUM> may present as a more or less normal bell curve PDF, where any deviations from a normal distribution S are still close approximations and the maximum n may serve as an outlier.

In embodiments, the centralized spectrum arbitrator (<NUM>, <FIG>) may integrate the area under a portion of the PDF curve <NUM> based on a particular design threshold, e.g., the area <NUM> under the curve from N to infinity (e.g., the likelihood of S exceeding N)_or the area <NUM> under the curve from W to infinity (e.g., the likelihood of S exceeding W). For example, large or increasing values may indicate an oversubscribed GRS <NUM> and very small values may indicate an undersubscribed GRS.

Referring now to <FIG>, the PDF <NUM> is shown. The PDF <NUM> may plot the distribution f(T) (<NUM>) of wait times T (e.g., the expected wait times E [ T ]) on contingency C2 links (214a-b, <FIG>)) as well as the distribution f(T') (<NUM>) of wait times T' (e.g., expected wait times E [T'] in the critical state when no spectrum resources are available to an entering UAS (102d, <FIG>).

In embodiments, as the wait time T' should be extremely short as noted above, the distribution f(T') (<NUM>) should be extremely narrow. It may further be noted that the distribution f(T) (<NUM>) of wait times T may be similar in shape to the PDF curve <NUM> (e.g., the distribution of f(S)). For example, the fusion engine <NUM> may normalize congestion metrics regardless of the number N of C2 channels 212a-n allocated to any particular GRS or the actual shape of the curve. The normalized PDF <NUM> may be adapted to other point-to-multipoint waveforms (e.g., other than CNPC) as a unified metric for assessing the distribution of spectrum resources throughout a network of GRS or other UAS control stations. Broadly speaking, the use of PDF <NUM>, <NUM> to track the distribution of GRS saturation (e.g., f(S)) and/or wait times (e.g., f(T), f(T')) may provide for unified metrics and/or submetrics normalized for every GRS (<FIG>: <NUM>, <NUM>, <NUM>) throughout the operating environment (<FIG>: <NUM>) and untethered to, e.g., either the particular hardware or software components of any single GRS or the number N of C2 channels 212a-n allocated to any single GRS (which N may vary throughout the operating environment <NUM>).

Referring now to <FIG>, the method <NUM> may be implemented by the GRS <NUM> and fusion engine <NUM> according to example embodiments of the inventive concepts disclosed herein and may include the following steps. At a step <NUM>, a GRS establishes a C2 link on a C2 channel to one or more UAS, e.g., each UAS operating within, or entering, its coverage area or transmission range.

At a step <NUM>, when the number n of UAS in service (e.g., via C2 link with the GRS) is not less than the number N of C2 channels allocated to the GRS, the GRS establishes C2 contingency links whereby two or more UAS share a C2 channel (e.g., via time slotting or time slicing) until enough spectrum space allows for each UAS to maintain a standard C2 link on its own C2 channel.

At a step <NUM>, a fusion engine configured for execution on the GRS collects wait times for each UAS waiting for a standard C2 link on an unshared C2 channel. For example, the fusion engine may collect wait times T for each UAS waiting on a contingency C2 link (e.g., whereby the UAS shares a C2 channel with another UAS) for a standard C2 link. In some embodiments, the fusion engine collects wait times T' for each UAS entering the coverage area that must wait for either a contingency C2 link or a standard C2 link to open up.

At a step <NUM>, the fusion engine generates dynamic variables S associated with probability distributions of the number n of UAS in service (either via standard C2 links or contingency C2 links on shared C2 channels) over time. At a step <NUM>, the fusion engine generates congestion metrics for the GRS by fusing the collected wait times and generated probability distributions. For example, the fusion engine generates time metrics associated with expected (e.g., mean) wait times (e.g., E [T] and/or E [T']), and submetrics based on the expected wait times, e.g., standard deviations of the expected wait times and maximum wait times. In some embodiments, the fusion engine generates channel availability metrics associated with an expected number of available C2 channels (e.g., E [ (N-n) ]), and submetrics based on the channel availability metrics, e.g., standard deviations of E [ (N-n) ] and expected idle times, e.g., when no UAS are in service and all C2 channels are available. In some embodiments, the fusion engine tracks the durations of GRS operating states, e.g., a nominal state wherein S < N; an off-nominal or saturated state wherein S ≥ N and S < W, (where W is the maximum number of UAS concurrently servable by the GRS via the at least one set of contingency C2 links); and a critical or danger state of the GRS wherein, S ≥ W (e.g., where no C2 channels may be available even for C2 contingency links).

The method <NUM> may additionally include method steps <NUM> and <NUM>. Referring also to <FIG>, at the step <NUM>, the fusion engine signals a UAS in service based on the generated congestion metrics, e.g., to request the UAS attempt to switch over to a different (e.g., less saturated) GRS to free spectrum resources.

Referring also to <FIG>, at the step <NUM>, the fusion engine forwards generated congestion metrics to a centralized spectrum arbitrator (e.g., central server).

Claim 1:
A ground radio station, GRS, comprising:
a communications interface comprising one or more antenna elements (<NUM>) and one or more transceivers (<NUM>) operatively coupled to the one or more antenna elements, the communications interface associated with N command and control, C2, channels (<NUM>), where N is an integer;
a traffic manager (<NUM>) operatively coupled to the communications interface, the traffic manager configured to:
establish one or more concurrent C2 links (<NUM>) to n unmanned aircraft systems, UAS, (<NUM>) in service, where n is an integer, each C2 link associated with a C2 channel of the N C2 channels;
when n ≥ N, establish at least one set of contingency C2 links corresponding to a C2 channel of the N C2 channels, each set of contingency C2 links associated with two or more UAS sharing the corresponding C2 channel;
and
at least one fusion engine (<NUM>) communicatively coupled to the traffic manager, the fusion engine configured to:
collect one or more wait times corresponding to each of the two or more UAS sharing the corresponding C2 channel, wherein the one or more wait times includes a wait time for each UAS on a shared C2 channel on a contingency link waiting for a non-shared channel on a standard C2 link;
generate one or more dynamic variables S associated with the n UAS in service over time, wherein the dynamic variable S is a probability distribution over time of the number n of UAS in service to the GRS; and
generate one or more congestion metrics associated with the N C2 channels by fusing the one or more wait times and the one or more dynamic variables S.