Estimation of aerial vehicle state

1. A system for estimating aerial vehicle status, comprising:

an aerial vehicle including a sensor that outputs telemetry data;

a computing device including a processor and a memory; and

a wireless communication link that communicatively couples the aerial vehicle and the computing device,

wherein the memory stores instructions that, when executed by the processor, cause the computing device to:

retrieve the telemetry data from the sensor via the wireless communication link,

detect a failure of the sensor of the aerial vehicle;

determine whether a telemetry alternative is available, including determining whether a sensor of another aerial vehicle is available to provide data similar to that which otherwise would have been provided by the sensor;

in response to determining the telemetry alternative is available, configure the telemetry alternative in response to the failure of the sensor;

execute an estimation algorithm, by an estimation module configured to estimate a status of a parameter and selected from a plurality of estimation modules configured to estimate a state of the aerial vehicle, based at least in part on the telemetry data, and

determine the state of the aerial vehicle based on a result of the estimation algorithm,

wherein the plurality of estimation modules comprises a dependency tree, one or more of the plurality of estimation modules dependent on a prerequisite estimation module.

2. The system of claim 1 , wherein the telemetry alternative includes a backup sensor of the aerial vehicle, a sensor of another aerial vehicle.

3. The system of claim 1 , wherein the memory stores further instructions that, when executed by the processor, cause the computing device to execute a plurality of estimation algorithms by way of the plurality of estimation modules, each having a corresponding input, output, and hierarchy level within the dependency tree, wherein hierarchy levels in the dependency tree define an order by which the plurality of estimation modules are executed.

4. The system of claim 3 , wherein the memory stores further instructions that, when executed by the processor, cause the computing device to execute the plurality of estimation algorithms in the order defined by the hierarchy levels.

5. The system of claim 1 , wherein the executing of the estimation algorithm includes at least one of filtering the telemetry data or supplementing a missing portion of the telemetry data with estimated telemetry data.

6. The system of claim 1 , wherein the executing of the estimation algorithm includes combining a plurality of data from a plurality of sources, respectively, wherein the plurality of data includes at least one of the telemetry data, wind data, temperature data, or infrared data, and wherein the plurality of sources includes at least one of a plurality of sensors of the aerial vehicle or weather data sources.

7. The system of claim 1 , wherein the determining of the state of the aerial vehicle includes determining an amount of gas remaining in the aerial vehicle. input and a corresponding output, and each being independently configurable to be enabled or disabled.

8. The system of claim 1 , wherein the determining of the state of the aerial vehicle includes determining a predicted remaining flight lifetime of the aerial vehicle.

9. The system of claim 1 , wherein the determining of the state of the aerial vehicle includes determining a present state of the aerial vehicle.

10. The system of claim 1 , wherein the executing of the estimation algorithm includes detecting an error in the telemetry data and generating a correction to the error.

11. The system of claim 1 , wherein the memory stores further instructions that, when executed by the processor, cause the computing device to generate an alert based on a predetermined rule and the determined state of the aerial vehicle.

12. The system of claim 1 , wherein the memory stores further instructions that, when executed by the processor, cause the computing device to generate a graphical representation of the determined state of the aerial vehicle.

13. The system of claim 12 , wherein the graphical representation of the determined state of the aerial vehicle includes a linear plot of the determined state of the aerial vehicle against another variable.

14. The system of claim 1 , wherein the estimation algorithm is dependent on an output of another estimation algorithm executed by another estimation module in the dependency tree.

15. The system of claim 1 , wherein the telemetry alternative comprises at least one of the another sensor, a weather data source, or an estimation module.

16. A method for estimating aerial vehicle status, comprising:

retrieving, by way of a wireless communication link, telemetry data from a sensor of an aerial vehicle;

detecting a failure of the sensor of the aerial vehicle;

determining whether a telemetry alternative is available, including determining whether another sensor of another aerial vehicle is available to provide data similar to that which otherwise would have been provided by the sensor;

in response to determining the telemetry alternative is available, configuring the telemetry alternative in response to the failure of the sensor;

executing an estimation algorithm, by an estimation module configured to estimate a status of a parameter and selected from a plurality of estimation modules configured to estimate a state of the aerial vehicle, based at least in part on the telemetry data; and

determining the state of the aerial vehicle based on a result of the estimation algorithm,

wherein the plurality of estimation modules comprises a dependency tree, one or more of the plurality of estimation modules dependent on a prerequisite estimation module.

17. The method of claim 16 , further comprising:

executing a plurality of estimation algorithms by way of the plurality of estimation modules, each having a corresponding input, output, and hierarchy level within the dependency tree, wherein hierarchy levels in the dependency tree define an order by which the plurality of estimation modules are executed.

18. The method of claim 16 , wherein executing the estimation algorithm is dependent on an output of another estimation algorithm executed by another estimation module in the dependency tree.

19. A non-transitory computer-readable medium having stored thereon instructions that, when executed by a processor, cause the processor to:

retrieve, by way of a wireless communication link, telemetry data from a sensor of an aerial vehicle;

detect a failure of the sensor of the aerial vehicle;

determine whether a telemetry alternative is available, including determining whether another sensor of another aerial vehicle is available to provide data similar to that which otherwise would have been provided by the sensor;

in response to determining the telemetry alternative is available, configure the telemetry alternative in response to the failure of the sensor;

execute an estimation algorithm, by the estimation module, based at least in part on the telemetry data; and

determine a state of the aerial vehicle based on a result of the estimation algorithm

wherein the plurality of estimation modules comprises a dependency tree, one or more of the plurality of estimation modules dependent on a prerequisite estimation module.