Patent Description:
There exist a variety of sources gathering aircraft trajectory information. In some scenarios, a retrieval of such information from a trusted source is not possible. In other words, it is not possible to retrieve information from a single independent and recognized source with no other interests rather than providing accurate trajectory data to be used by third-party applications. Document <NPL>". Document <NPL>". Document <CIT> is entitled "Method and a device for recording vehicle trajectory, a computer equipment and a medium". Document <CIT> is entitled "System and method for tracking vehicle mileage using blockchain".

Nowadays, it is not possible to know the time evolution, i.e. historical or real-time evolution, of an aircraft location in a centralized manner from a trusted source. Air Navigation Service Providers, ANSP, manage multiple sources of surveillance information such as Primary and Secondary RADAR Tracks or ADS-B tracks, and combine such surveillance information according to their own systems. This results in a situation where sophisticated technology developments provide different trajectory representations than other less sophisticated infrastructures. The aircrafts manage on-board trajectory information that enable a safe trajectory execution. The on-board trajectory information, although it might be the most accurate, is usually only available to Airline Operating Centers, AOC. There are also profitable entities, or commercial aircraft tracking providers, that provide trajectory information through the internet by making use of ADS-B receptors, wherein ADS-B messages are openly broadcasted. The commercial aircraft tracking providers combine information from a network of receptors, filtering data and filling gaps according to their own requirements.

ANSP, e.g., Federal Aviation Administration, FAA, Eurocontrol or US NAS, airlines and commercial aircraft tracking providers, e.g., FlightAware, FR24 or Aireon, maintain their trajectory information database, which might contain tracking data, i.e., latitude, longitude, altitude and time, kinematic information, i.e. airspeeds and ground speed or kinetic data in the case of airlines i.e., fuel consumption and instantaneous aircraft mass. In some cases, information may be partially available or there may be gaps in the recorded datasets and different representations of the same trajectory can, therefore, be obtained depending on the considered source of data.

Nowadays, there is no trusted system from which a unique and accurate representation may be obtained. Thus, it is not possible to have a unique, synchronized, accurate and trusted representation of a trajectory due to the disparity of trajectory sources, limited accessibility of data and diversity of business interests of the trajectory information providers. This situation may lead to inconsistent representation of the same aircraft trajectory, making almost impossible to know which one reflects reality more accurately.

A purpose of the present disclosure is to provide methods to formally collect and validate vehicle trajectory information, avoiding the lack of trust of some of the current systems. The proposed method may be of use in an Air Traffic Management, ATM, environment, in which information, especially air vehicle trajectory information is a key enabler of advanced traffic management procedures.

The present disclosure provides a computer implemented method for validating a data block for insertion or recording into a vehicle trajectory blockchain comprising the steps of:.

In the present disclosure vehicle may be understood as a means for transportation of goods or people such as wagons, bicycles, motor vehicles, motorcycles, cars, trucks, buses, railed vehicles, trains, trams, watercraft, ships, boats, amphibious vehicles, screw-propelled vehicle, hovercraft, air vehicles, aircraft, airplanes, helicopters, and spacecraft.

In the present disclosure, aggregated trajectory data may be understood as data comprising trajectory information obtained from different trajectory sources of information, such as different or a variety of trajectory data sources, and wherein such trajectory information may have been aggregated. The trajectory data may comprise information about the vehicle state variables throughout a trajectory, data of the weather faced during trajectory by the vehicle and vehicle configuration data. The aggregated trajectory data provides a unique information which is considered as representing a trajectory for which multiple and varied data have been obtained or received. A set of aggregated trajectory data may be understood as aggregated trajectory data representing a trajectory for a vehicle, or a flight for an air vehicle, or more than one trajectory for a vehicle or an air vehicle. In some examples, two sets of aggregated trajectory data comprise, each set, aggregated trajectory data of separate flights of an air vehicle. In some examples, two sets of aggregated trajectory data comprise, each set, separate fights of separate air vehicles. Examples of possible actions performed for aggregating data will be explained further below.

One or more data blocks or blocks of data are generated from the aggregated trajectory data. Examples for generating a data block are explained further below. Such blocks compose or construct or form a blockchain if their content is considered valid. Such a blockchain may be stored in a blockchain database, also called blockchain vehicle trajectory database in the present disclosure.

For verifying that the data blocks comprise valid data, mining is performed. In the present disclosure, mining may involve blockchain miners which add trajectory data to a private or public blockchain. In a blockchain, data blocks are secured by blockchain miners and are connected to each other forming a chain. Blockchain operations are generally verified in decentralized systems wherein miners contribute with computing resources to verify the source of data or the data. The process of verifying trajectories is called mining and examples of mining are detailed further below. If mining a data block verifies that the block is data block comprising valid vehicle data, the methods of the present disclosure validate the data block for insertion or recording into a vehicle trajectory blockchain.

In the present disclosure, the term "blockchain" is utilized in relation to the vehicle trajectory blockchain where a blockchain may be understood as growing list of data records or data blocks hardened against tampering and revision and includes data structure blocks and optionally programs or executables. The growing list may continuously grow. Each data block contains a timestamp and information linking the block to a previous block where a "blockchain" consists of blocks that hold timestamped batches of valid data. Such valid data is provided by the method for validating a data block of the present disclosure. Each block may include a hash of the prior block linking the blocks together, where a "hash" is a hash function that is utilized to map data of arbitrary size to data of a fixed size. In order to add more security, a cryptographic hash function may be utilized that assists in verifying the authenticity of the entry in the block.

A vehicle trajectory blockchain may be stored in a blockchain vehicle trajectory database. A blockchain vehicle trajectory database may be understood as a database comprising trajectory data blocks or one or more trajectory data blockchains which have been validated by a blockchain miner. The blockchain vehicle trajectory database may structurally be composed of a type of a data storage device such as, for example, a solid-state memory, read-access memory ("RAM"), read-only memory ("ROM"), electromechanical storage device such as, for example, a hard-drive, or other equivalent devices or components. The blockchain vehicle trajectory database may include a database of organized collection of meta-data of trajectory related information that may include, for example, for a specific date and time: position, altitude, latitude, weather conditions, atmospheric temperature, etc. of a vehicle. The blockchain vehicle trajectory database may be a distributed database that may be linked to a network where the database includes a cryptographic hash of preceding records in the database and is accessible to users of the distributed database. As such, the blockchain vehicle trajectory database may include meta-data of the trajectory information about a vehicle, wherein a vehicle may be an air vehicle, or may be an aircraft. The blockchain vehicle trajectory database may include targeting location information e.g., the ending second location such as an airport, base, port, target, etc., and may also include spatial information about the geography and two and/or three-dimensional maps.

The method according to the present disclosure may further comprise inserting or adding or recording the data block in a vehicle trajectory blockchain wherein the vehicle trajectory blockchain comprises robust and accurate vehicle trajectory data representing vehicle trajectories. The method may further comprise storing the vehicle trajectory blockchain into a blockchain vehicle trajectory database. Both the vehicle trajectory blockchain and the blockchain vehicle trajectory database provide for organized data where vehicle trajectory information may be provided in an improved and simplified manner. In particular, vehicle trajectory information can be provided even in the case when a set of trajectory sources are unreliable or suffer disruption. The vehicle trajectory data or data block may be recorded in a blockchain vehicle trajectory database with an increased security against tampering.

In the present disclosure, providing aggregated trajectory data may be understood as providing data comprising trajectory information obtained from different trajectory sources of information, such as different or a variety of trajectory data sources, and wherein such trajectory information obtained from a variety of data sources may have been aggregated by any method such as:.

In some examples, providing one or more sets of aggregated trajectory data comprises generating aggregated trajectory data by a method comprising:.

In some examples, receiving vehicle data trajectory comprises receiving one or more of.

In some examples, reconstructing vehicle or air vehicle data trajectory may comprise combining, results from a weather model, WM, and results from a vehicle performance model for generating a reconstructed trajectory. Reconstructing vehicle or air vehicle data trajectory may comprise combining: the trajectory data, results from a weather model, WM, and results from a vehicle performance model for generating a reconstructed trajectory.

A weather model, WM, may be understood as a model providing information about the evolution of one or more atmospheric variables in time in a geographic area. Such geographic area may be represented as a set of points in a 3D grid defined by latitude, longitude and altitude. The one or more atmospheric variables may comprise temperature, pressure, humidity, wind speed and direction.

A vehicle performance model may be understood a representation of an actual vehicle performance, which enables a computation of parameters of a vehicle. In the case where the vehicle is an aircraft, an air vehicle performance model or APM performance model may be understood as a representation of the actual air vehicle performance, for example an aircraft performance, which enables the computation of the drag, thrust and fuel consumption at a trajectory point as a function of flight conditions, such as altitude, speed and atmosphere temperature.

The combination of trajectory data, a weather model, WM, and a vehicle performance model, PM, may be performed to infer a full trajectory of an aircraft from surveillance data based, for example, on a 4D position.

In some examples air vehicle trajectory features, also referred to as state variables, may be received by any one of the methods according to the disclosure, for example, a latitude, a longitude, a height and a time of trajectory may be received: for example, <NUM> feet, (<NUM>°, <NUM>'N); (<NUM>°, <NUM>'W), @23h12. The weather model WM may provide the speed of wind, pressure and direction for such air vehicle trajectory and the vehicle performance model, for example an air vehicle performance model, APM, may provide a speed in two or more points of the trajectory and cinematic values. With the trajectory data, such two or more points and the results of the weather model, a Trajectory Reconstruction Engine, TRE, may provide "reconstructed trajectory data" which in the present disclosure is complete vehicle or air vehicle trajectory data, as it will be further explained below.

A reconstruction of aircraft trajectory data may be computed by integrating a system of equations representing an Aircraft Motion Model, AMM. For some Air Traffic Management, ATM, applications, <NUM>-degree-of-freedom systems may be well suited for such purpose. Information about the aircraft performance and weather and/or atmosphere conditions may be required for correctly referencing such <NUM>-degree-of-freedom systems of equations. As previously said, a Trajectory Reconstruction Engine, TRE, may reconstruct vehicle data trajectory. The TRE is an engine to compute an actual full trajectory data, which may be air vehicle trajectory data, from a portion of data, for example, 4D positions of the trajectory, aided by a WM and an aircraft performance model, APM. The TRE may infer some aircraft state variables such as if an aircraft is using engine thrust, or if an aircraft has its flaps out, the rotation speed or any other parameter. The TRE may leverage received trajectory data to infer other additional aircraft state variables. For inferring such state variables from received data, methods according to the present disclosure may be based on a system of equations representing an Aircraft Motion Model, AMM, as explained, or may be based on Kalman filters or may be based on any other method related to modelling aircraft performance through adaptive aircraft performance models using actual flight recorded data. Such methods for inferring the state variables may model vehicle or air vehicle performance through adaptive vehicle performance models using actual trajectories data.

After reconstructing vehicle trajectory data the method provides a reconstructed trajectory or one or more reconstructed trajectories, wherein the one or more reconstructed trajectories are composed of one or more trajectory parameters such as speed and/or frequency of data acquisition, and/or fuel consumption for the vehicle, and/or CO2 emissions during the trajectory and/or noise footprint.

After providing one or more reconstructed trajectories, the methods of the present disclosure comprise fusing such one or more reconstructed trajectories. Fusing one or more reconstructed trajectories may be performed by a Trajectory Data Fusion Engine.

In some examples, fusing the reconstructed trajectories comprises at least one of the following actions:.

Some examples of fusing reconstructed trajectories are described further below.

In some examples, the result of fusing the reconstructed trajectory is providing a set of aggregated trajectory data. In some examples, the result of fusing the reconstructed trajectory is providing a plurality of sets of aggregated trajectory data.

As seen, methods according to the disclosure may receive trajectory datasets representing a unique vehicle trajectory or flight provided by different considered trajectory sources. The information from each source may be enhanced by a Trajectory Reconstruction Engine, TRE, which may perform the reconstructing vehicle data trajectory and thereafter a Trajectory data Fusion Engine may fuse the reconstructed trajectory. In this way, any disparity of information provided by the different considered trajectory sources may be homogenized. Such fusing may provide one or more sets of aggregated trajectory data.

After providing one or more sets of aggregated trajectory data, the methods of the present disclosure comprise generating a data block from the one or more sets of aggregated trajectory data, such that the data block serves as input into a blockchain miner.

A data block may be understood in the present disclosure as a set of data representing different trajectories sharing a common feature, wherein a common feature may be a geographical area and/or a timeframe. For example, a data block may comprise information about at least part of all the flight trajectories in a common geographical area, for example, flight trajectories from a heliport in the Grand Canyon in Arizona, on 5th of April <NUM> from 10am to 11pm, not necessarily performed by a same air vehicle. For example, a data block may comprise information about N flight trajectories with, for example, N=<NUM>, or N=<NUM> or N=<NUM>. In a further example, a data block may comprise information about at least part of all the flight trajectories in a common route, for example, flight trajectories from an airport in South Africa to an airport in New Zealand, on 23rd of November <NUM>. The set of data representing trajectories in a data block may be organized by a processing means as a matrix representation wherein each of the rows or columns, or more generally, each record, may represent a trajectory, for example, a flight in the case where the vehicle is an air vehicle such as a helicopter or an aircraft. In some examples, generating a data block from the one or more sets of aggregated trajectory data comprises generating:.

Each generated data block may be composed of the generated header, the hash of the header of a previous block in the blockchain, and the set of trajectories, for example trajectory in a record.

The generation of a data block results in a block of a blockchain and a hash for such data block. When constructing the data block, a previous block is read in order to verify whether the chain presents a correct order; this prevents the blockchain from being corrupted. Exceptionally, a genesis block, being the first block of a block chain, is a case without reference to a previous block. The generated data block is to be added to a blockchain if the methods according to this disclosure validate the data block for insertion into a vehicle trajectory blockchain. Examples of validation and insertion of a data block into a blockchain may comprise any of the known methods in the art for chaining blocks of a data block into a blockchain.

After generating a data block from the one or more sets of aggregated trajectory data the methods of the present disclosure comprise mining the data block to verify whether the data block comprises valid vehicle data.

In some examples, mining the data block may be performed by a miner. In the present disclosure, a miner or data miner or blockchain miner may be understood as a processor or set of instructions configured to secure and verify vehicle trajectories or air vehicle trajectories. Advantageously, maintenance of the blockchain instead of maintaining individual databases by data owners may be the only maintenance requirement. A blockchain which is created from blocks mined by a data miner may be stored in a blockchain vehicle trajectory database. A blockchain vehicle trajectory database provides accessibility to aircraft trajectory data that have been accepted by a whole community of miners as the most accurate representation of actual operations.

In some examples, mining the data block to verify whether the data block comprises valid vehicle data comprises:.

In response to verifying that the data block comprises valid vehicle data, the method comprises validating the data block for insertion into a vehicle trajectory blockchain. The method may further comprise inserting or adding or recording such block into a vehicle trajectory blockchain. The addition of a new data block into the blockchain may lead to an unrealistic representation of the trajectory: i.e., a dataset that does not represent a flyable trajectory, because every single datum may come from a different source. The steps of mining, processing, confirmation and filtering are therefore advantageous prior to adding, recording or storing the data block into the vehicle trajectory blockchain or, further, prior to adding the blockchain into a blockchain vehicle trajectory database. The mining step double-checks that the data block is realistic and filters data, i.e., removes data blocks or data points, to obtain a true representation of an actual trajectory. In general terms, it may be better to have a reduced dataset rather than an extended one in which some data could potentially be challenged.

After mining the data block, the methods of the present disclosure comprise, if the data block comprises valid vehicle data, validating the data block for insertion into a vehicle trajectory blockchain, wherein the vehicle trajectory blockchain comprises robust and accurate vehicle trajectory data representing vehicle trajectories. If the verification is not positive, then the data block is not validated for insertion into a blockchain vehicle trajectory database. If the verification is positive, the validation may comprise inserting a flag into the block representing a valid data block or may comprise storing the data block in a blockchain data base or may comprise sending the data block to a blockchain queue wherein data blocks await to be inserted into a blockchain or blockchain database.

In some examples, the method may comprise rejecting inaccurate vehicle data, wherein inaccurate vehicle data comprises one or more representations of vehicle trajectories which are not valid. In such examples if the data block does not comprise valid vehicle data, or in other words, examples if the data block comprises inaccurate vehicle data, the data block is not validated for insertion into a vehicle trajectory blockchain and the data block is rejected. In such examples, the data block is not validated for insertion into a vehicle trajectory blockchain. If the speed of a vehicle is negative, and/or if the geographical area covered by an air vehicle is outside of the geographical scope of interest, and/or any other criteria, the data block may be rejected.

In the case of using a public blockchain, the method may comprise an incentive mechanism for miners, such as individuals which record or store new data blocks into the blockchain. For example, every miner may obtain a token representing a type of remuneration or a token that may be used to get priority access to some advanced services. In the case of a private blockchain, e.g., owned by the Federal Aviation Administration, FAA, or the Single European Sky ATM Research, SESAR, then there may be dedicated miners set by the owner who may straightforwardly record data.

The miners may not only be responsible for validating data blocks, but also, they can be devoted to recording or storing new data blocks and to compute some specific tasks. For example, the miners may compute the difference between a datum coming from the aggregated trajectory data, e.g., the pressure and altitude at a specific time, and may select as true the one which is closer to the average values. Such strategy may be different for different state variables or different implementations of the methods of the present disclosure. Once this process is executed for at least part of all state variables from the beginning to the end of the trajectory, a potential trajectory data block to be added to a blockchain is ready.

The present disclosure further describes a vehicle trajectory blockchain comprising one or more data blocks validated by any of the methods for validating a data block of the present disclosure. In other words, the vehicle trajectory blockchain of the present disclosure may comprise a data block header, wherein the header may contain information i.e. about a common feature throughout different trajectories or covered geographical area, a hash of the header of a previous block in the blockchain, and a set of trajectories, wherein the trajectories are validated, for example by a miner. The described blockchain comprises therefore robust and accurate vehicle trajectory data representing vehicle trajectories.

In some examples, the methods of the present disclosure comprise.

Such examples provide a method for determining a vehicle trajectory, comprising retrieving vehicle trajectory data from a vehicle trajectory blockchain.

Advantageously vehicle or air vehicle trajectory data may be retrieved such that it is ensured that the received or retrieved data is untampered and valid air vehicle trajectory data. The vehicle trajectory data may be retrieved by a retrieving system. Retrieving may be performed directly from the blockchain or from a blockchain vehicle trajectory database where one or more blockchains are stored, and where the vehicle trajectory data is ultimately retrieved from.

A method for retrieving an air vehicle trajectory data may comprise the steps of any one of the methods according to the present disclosure, wherein the vehicle is an air vehicle, for example an aircraft or helicopter. The method for retrieving an air vehicle trajectory data may comprise:.

In some examples, the method for retrieving an air vehicle trajectory data may comprise:.

The present disclosure further describes a blockchain generation system comprising:.

In some examples, the blockchain generation system comprises:.

In some examples, the blockchain generation system comprises.

In some examples, the blockchain generation system may comprise an air vehicle trajectory retrieving system.

An air vehicle trajectory retrieving system may comprise:.

An air vehicle trajectory retrieving system may be a system using blockchain technology for the provision of trajectory information. A retrieving system may implement the steps of the methods described herein for retrieving air vehicle trajectory data from a blockchain air vehicle trajectory database, wherein the air vehicle trajectory database comprises one or more data blocks validated by any one of the methods for validating a data block described in the present disclosure.

As it may be apparent from the present disclosure, features such as a decentralized aircraft trajectory database supported by the blockchain may provide robust and universal access to accurate aircraft trajectory data representing actual trajectories. Furthermore, rejection of untrusted or inaccurate representations of actual trajectories may be provided by the methods of the present disclosure. In some examples, trajectory data reconstruction and fusion prior to recording data onto the blockchain is provided.

Some of the advantages provided by the methods and systems of the present disclosure are:.

The disclosed methods and systems may enable the development of a System Wide Information Management, SWIM, infrastructure that may be the core of future ATM environments. The current ATM systems may share information among ATM actors, i.e., ANSP, AOC, Air Traffic Control, ATC and the aircraft. The lack of trust of data sources, especially those providing trajectory information, may however preclude the implementation of most advanced capabilities. The disclosed methods and systems solve this problem and they may be potentially used worldwide by the ATM actors.

The following detailed description of examples refers to the accompanying drawings, which illustrate specific examples of the disclosure. Other examples having different structures and operations do not depart from the scope of the present disclosure. Reference numerals may refer to the same element or component in the different drawings.

The present disclosure may be implemented by a system, a method, and/or a computer program product.

Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture, or ISA, instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and procedural programming languages, such as the "C" programming language or similar programming languages. In some examples, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus or systems, and computer program products according to examples of the disclosure.

<FIG> is a flow chart of an example of a method <NUM> according to the present disclosure. In block <NUM> the method comprises providing one or more sets of aggregated trajectory data, a set of aggregated trajectory data comprising at least aggregated trajectory data defining a trajectory of a vehicle; in block <NUM> the method comprises generating a data block from the one or more sets of aggregated trajectory data, such that the data block serves as input into a blockchain miner; in block <NUM> the method comprises mining the data block to verify whether the data block comprises valid vehicle data; in block <NUM> the method comprises, if the data block comprises valid vehicle data, validating the data block for insertion into a vehicle trajectory blockchain.

<FIG> is a flow chart of an example of a method <NUM>, which is implemented in a blockchain generation system <NUM>. In more detail, <FIG> shows:.

<FIG> is a flow chart of an example of a method <NUM> for providing one or more sets of aggregated trajectory data according to the present disclosure. The method <NUM> comprises in block <NUM>, receiving vehicle trajectory data, wherein vehicle trajectory data comprises data received from at least one trajectory data source. The method <NUM> comprises, in block <NUM>, reconstructing vehicle trajectory data, providing reconstructed trajectory. The method <NUM> comprises, in block <NUM>, fusing the reconstructed trajectory, providing aggregated trajectory data in one or more sets.

<FIG> is a flow chart of an example of a method <NUM> for providing, by a system <NUM>, one or more sets of aggregated trajectory data according to the present disclosure. <FIG> shows.

Some examples of providing one or more sets of aggregated trajectory data A, defining the previously seen Trajectory: Aggeneys Airport to Auckland Airport; 5th April <NUM>@<NUM> may comprise:.

First, vehicle trajectory data for a same trajectory are received <NUM>:.

As seen, trajectory data sources <NUM>, <NUM> and <NUM> provide different state variables for a same trajectory and for a same air vehicle, i.e. trajectory data source <NUM> and <NUM> provide different net thrust and trajectory data source <NUM> does not provide a net thrust.

Secondly, the TREs <NUM>, based on the trajectory data, the results from the weather model WM and the results from an air vehicle performance model APM, provide <NUM> reconstructed trajectories, wherein some of the state variables are inferred, some other state variables are completed, and other state variables may add information missing in the source trajectory data. Examples of Reconstructed trajectories comprising different state variables are the following, wherein a state variable may comprise a value or a set of values, structured as data vector or data matrix, etc.:.

Finally, the set A of aggregated trajectory data <NUM> is provided by fusing <NUM>, by the Trajectory Data Fusion Engine, TDFE <NUM>, the <NUM> reconstructed trajectories, by, for example, averaging the values shown in the <NUM> reconstructed trajectories:.

Such that the provided set aggregated trajectory data A is:
Aggregated trajectory data A = aggregated freq data A; aggregated fuel consumption A; aggregated speed A; aggregated emissions A; aggregated net thrust A; aggregated noise footprint A; aggregated Pressure A, aggregated Speed of wind A, aggregated maximum altitude A.

is an example system <NUM> for generating a blockchain comprising a processor <NUM> and a memory <NUM>.

<FIG> is an example blockchain generation system <NUM> comprising:.

As seen in <FIG>, the miner <NUM> further comprises a processing module for processing trajectory data included in data blocks as explained in the present disclosure, a confirmation module configured to confirm the trajectory data included in data blocks as explained in the present disclosure and a filtering module for filtering data as explained in the present disclosure. For example, it may be validated that the set of data respect the minimum frequency of data points, for example, <NUM> data point per second, or it may be validated that the dispersion of the data is below a threshold.

The example system of <FIG> also shows a blockchain vehicle trajectory database <NUM> where the blockchain <NUM> may be stored.

is an example an air vehicle trajectory retrieving system <NUM> comprising:.

Advantageously, the air vehicle trajectory data retrieved by the air vehicle trajectory retrieving system <NUM> is air vehicle data with a security against tampering. Such air vehicle data, for example aircraft data, comprises timestamped batches of valid data.

<FIG> is a flow chart of an example of a method <NUM> according to the present disclosure. The method <NUM> of <FIG> comprises, in block <NUM>, providing one or more sets of aggregated trajectory data, a set of aggregated trajectory data comprising at least aggregated trajectory data defining a trajectory of a vehicle; in block <NUM> the method comprises generating a data block from the one or more sets of aggregated trajectory data, such that the data block serves as input into a blockchain miner; in block <NUM> the method comprises mining the data block to verify whether the data block comprises valid vehicle data; in block <NUM> the method comprises, if the data block comprises valid vehicle data, validating the data block for insertion into a vehicle trajectory blockchain; in block <NUM> the method comprises, if the data block does not comprise valid vehicle data, or in other words, if the data block comprises inaccurate or invalid vehicle data, rejecting <NUM> the data block for storage into a vehicle trajectory blockchain.

Further, the disclosure comprises examples according to the following clauses.

Clause <NUM>. A computer implemented method for validating a data block for insertion into a vehicle trajectory blockchain comprising the steps of:.

Clause <NUM>. The method of clause <NUM> further comprising inserting the data block in a vehicle trajectory blockchain, wherein the vehicle trajectory blockchain comprises robust and accurate vehicle trajectory data representing vehicle trajectories.

Clause <NUM>. The method of clause <NUM> wherein providing one or more sets of aggregated trajectory data comprises generating aggregated trajectory data by a method comprising:.

Clause <NUM>. The method of clause <NUM> wherein receiving vehicle data trajectory comprises receiving one or more of.

Clause <NUM>. The method of clause <NUM> wherein reconstructing vehicle data trajectory comprises combining results from a weather model and results from a vehicle performance model for generating a reconstructed trajectory.

Clause <NUM>. The method of clause <NUM> wherein fusing the reconstructed trajectory, comprises at least one of:.

Clause <NUM>. The method of clause <NUM> wherein generating a data block from the one or more sets of aggregated trajectory data comprises generating a header; and a hash of the header of a previous block in the blockchain.

Clause <NUM>. The method of clause <NUM> wherein mining the data block to verify whether the data block comprises valid vehicle data comprises:.

Clause <NUM>. The method of clause <NUM> further comprising rejecting inaccurate vehicle data, wherein inaccurate vehicle data comprises one or more representations of vehicle trajectories which are not valid.

Clause <NUM>. The method of clause <NUM>, further comprising remunerating a mining entity performing the mining.

Clause <NUM>. The method of clause <NUM>, wherein the mining is performed by a miner, and the method further comprises obtaining a token by the miner, wherein the token represents a remuneration.

Clause <NUM>. The method of clause <NUM> further comprising.

Clause <NUM>. The method of clause <NUM> further comprising adding the validated data block in a vehicle trajectory blockchain and retrieving air vehicle trajectory data from the air vehicle trajectory blockchain.

Clause <NUM>. The method of clause <NUM> further comprising storing the validated data block in a blockchain vehicle trajectory database.

Clause <NUM>. A blockchain generation system comprising:.

Clause <NUM>. The blockchain generation system of clause <NUM> comprising:.

Clause <NUM>. The blockchain generation system of clause <NUM> comprising.

Clause <NUM>. An aircraft trajectory retrieving system comprising:.

Clause <NUM>. The aircraft trajectory retrieving system of clause <NUM> comprising:.

Clause <NUM>. The aircraft trajectory retrieving system of clause <NUM> comprising.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various examples of the present disclosure.

The terminology used herein is for the purpose of describing particular examples and is not intended to be limiting of examples of the disclosure. It will be further understood that the terms "include," "includes," "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present examples has been presented for purposes of illustration and description but is not intended to be exhaustive or limited to examples in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of examples.

Claim 1:
A computer implemented method (<NUM>) for validating a data block for insertion into a vehicle trajectory blockchain comprising the steps of:
- providing (<NUM>) one or more sets of aggregated trajectory data (<NUM>), a set of aggregated trajectory data comprising at least aggregated trajectory data defining one or more trajectories of one or more vehicles; the aggregated trajectory data comprising trajectory information obtained from a variety of trajectory data sources (401_i, 401_j, 401_k), and wherein such trajectory information has been aggregated (<NUM>);
wherein providing (<NUM>) one or more sets of aggregated trajectory data comprises generating the aggregated trajectory data by a method (<NUM>) comprising:
- receiving (<NUM>) vehicle trajectory data, wherein vehicle data trajectory comprises data received from the variety of trajectory data sources (401_i, 401_j, 401_k);
- reconstructing (<NUM>) the vehicle trajectory data, providing one or more reconstructed trajectories; and
- fusing (<NUM>) the one or more reconstructed trajectories, providing aggregated trajectory data (<NUM>) in one or more sets;
- generating (<NUM>) a data block (<NUM>) from the one or more sets of aggregated trajectory data (<NUM>);
- mining (<NUM>) the data block to verify whether the data block comprises valid vehicle data; and
- if the data block comprises valid vehicle data, validating (<NUM>) the data block for insertion into a vehicle trajectory blockchain.