Cooperative navigation and radio transmission of a fleet of vehicles

Abstract

The invention relates to a network (100) comprising a plurality of entities (1), each entity (1) forming a node of the network (100), wherein each entity (1) comprises: - a positioning device (2) configured to generate a positioning signal (200); - a clock (3) configured to generate time data (205) indicative of a time of generation of the positioning signal (200); and - a data processing device (4) configured to determine, by means of the positioning signal (200) and the time data (205), a propagation time of the positioning signal (200) between two entities (1) of the network (100) and to infer therefrom a distance between the two entities (1).

Description

Technical Field

[0001] This disclosure relates to the general field of geolocation of entities in a network of entities, which may specifically include one or more vehicles, such as autonomous vehicles, fixed stations, etc., to accurately establish the location of entities.

[0002] More specifically, but not exclusively, this disclosure relates to a method for enabling precise geolocation of autonomous aircraft within an autonomous aircraft network and time synchronization of autonomous aircraft within the network. Background Technology

[0003] Current vehicle guidance systems use navigation systems that periodically determine the vehicle's position to compare it to a trajectory to be followed. This position is typically determined using receivers of an absolute satellite positioning system, such as a GNSS (Global Navigation Satellite System) like GPS or Galileo, which provides accuracy limited to a few meters and is susceptible to interference.

[0004] Furthermore, when vehicles travel in groups, such as in the case of swarms of drones flying in the air, the vehicles in the group communicate together via radio links or other means of communication to exchange their positions and trajectories. Each entity in the group then knows the absolute positions of the other members and calculates the distances between them. This information is used to maintain a minimum safe distance to prevent collisions and to control the trajectories of the vehicles (where applicable). Other methods can also be used to measure the distance between two vehicles, such as measuring the strength of received signals (Received Signal Strength Indicator or RSSI).

[0005] However, when the distance between vehicles is small, such as when a swarm of drones flies in close formation and the space between them is less than one meter, the accuracy of GNSS and RSSI systems is insufficient, and the risk of collision is high. Summary of the Invention

[0006] One object of the present invention is to overcome the above-mentioned disadvantages by proposing a network comprising multiple entities, each entity forming a node of the network, wherein each entity comprises: - A positioning device, configured to generate a positioning signal; - A clock, configured to generate time data indicating the generation time of the positioning signal; and - A data processing device configured to determine the propagation time of the positioning signal between two entities in the network by means of the positioning signal and the time data, and thereby infer the distance between the two entities.

[0007] The network according to the invention is advantageously supplemented by the following features, which are adopted independently or in any technically possible combination thereof: Each entity also includes a transceiver device configured to transmit and receive the positioning signal and the time data. - Each positioning device of the entity further includes a satellite positioning system and at least one of the following: an inertial measurement unit and an optical sensor, wherein the positioning signal includes the position of the entity.

[0008] The present invention also relates to entities forming nodes in a network, the entities comprising: - A positioning device, configured to generate a positioning signal; - A clock, configured to generate time data indicating the generation time of the positioning signal; and - A data processing device configured to determine the propagation time of a location signal of another entity in the network by means of the location signal and the time data, and thereby infer the distance between the two entities.

[0009] The entity according to the invention is advantageously supplemented by the following features, which are taken independently or in any technically possible combination thereof: - A transceiver device configured to transmit and receive the positioning signal and the time data. - A satellite positioning system and at least one of the following: an inertial measurement unit and an optical sensor, and then the positioning signal includes the location of the entity.

[0010] The present invention also relates to a method for locating entities in a network according to the present invention, comprising the following steps: - Generate the location signals of the entities in the network; - Generate time data indicating the generation time of the positioning signal; The positioning signal and the time data are received by at least one other entity; and - Based on the positioning signal and the time data, determine the propagation time of the signal between the network entity and the at least one other entity in the network, and thereby deduce the distance between the network entity and the at least one other entity in the network.

[0011] The positioning method according to the invention is advantageously supplemented by one or more of the following steps: - The step of synchronizing the entity with a reference clock time, the reference clock being able to correspond to the clock of one of the entities in the network; - Absolute positioning step, which locates all or part of the other entities in the network to obtain the absolute position of the entity; - The step of determining the absolute position of a fifth entity in the network by trilateration based on the absolute positions of the four entities in the network.

[0012] Advantageously, the steps of receiving the location signal and determining the propagation time are performed by several other entities in the network.

[0013] The step of determining the propagation time may also include using a Kalman filter.

[0014] The present invention also relates to a method for guiding a vehicle, comprising the following steps: - Locating the absolute location of entities in the network, including the vehicle; and -Guided vehicle.

[0015] The present invention also relates to a method for a secure system for synchronizing network transmission, comprising the following steps: - Generate time data indicating the generation time of the signal; - Time data is received by at least one other entity; and - Based on the time data, the security system synchronizes the transmissions of the entity and the at least one other entity. Attached Figure Description

[0016] Other features, objects, and advantages of the invention will become apparent from the following description, which is purely illustrative and not restrictive, and should be read in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic overview of a network according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a network entity system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a system of another entity of a network according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the power of a waveform of a signal emitted by an entity in a network as a function of time, according to an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating a group of different entities belonging to a network according to an embodiment of the present invention; Figure 6 This is a schematic overview illustrating a group of entities belonging to a network according to an embodiment of the present invention; Figure 7 This is a schematic overview illustrating the guidance of a network entity according to an embodiment of the present invention; Figure 8 This is a flowchart illustrating the steps of an exemplary method for locating entities in a network according to an embodiment of the present invention; Figure 9 This is a flowchart illustrating the steps of an exemplary method for guiding an entity in a network according to an embodiment of the present invention; Figure 10 This is a flowchart illustrating the steps of an exemplary method for a security system for synchronizing the transmission of network entities according to an embodiment of the present invention.

[0017] Throughout the accompanying drawings, similar elements have the same reference numerals. Detailed Implementation

[0018] In the following, this disclosure will be more specifically directed to a network 100 comprising multiple entities 1 (e.g., autonomous aircraft). This is not limiting, as this disclosure applies to any other type of entity 1, such as a land vehicle or any fixed or mobile device, whether autonomous or not.

[0019] Therefore, network 100 includes multiple entities 1, each entity 1 forming a node of network 100. That is, each entity 1 constitutes the infrastructure or hardware medium for redistribution or termination of information transmitted through network 100.

[0020] Network 100 is preferably a self-organizing network, such as a Flight Ad Hoc Network (FANET) or Vehicle Ad Hoc Network (VANET), meaning that network 100 is decentralized and entities 1 propagate information transmitted between them according to dynamically and autonomously established routes. This allows each entity 1 to communicate with all other entities 1 within the communication range of network 100.

[0021] Each entity 1 includes: a positioning device 2 configured to generate a positioning signal 200, a clock 3 configured to generate time data 205 indicating the generation time of the positioning signal 200, and a data processing device 4 configured to determine the propagation time of the positioning signal 200 between two entities 1 belonging to the network 100 by means of the positioning signal 200 and the time data 205 and infer the distance between the two entities 1 therefrom.

[0022] More specifically, each entity 1 of network 100 iteratively generates a location signal 200 associated with time data 205. Time data 205 may be a timestamp that precisely indicates the time of generation of the location signal 200.

[0023] Preferably, entity 1 includes a transceiver device 5. Each entity 1 equipped with the transceiver device 5 can broadcast its location signal 200 indiscriminately to any member within the range of network 100. Furthermore, each entity 1 can receive the location signal 200 from entities 1 within the range via its transceiver device 5. Transceiver device 5. In the remainder of this disclosure, the entity 1 that receives the location signal 200 from another entity 1 is referred to as receiving entity 1a, while the other entity 1 is referred to as transmitting entities 1b, 1c, 1d, and 1e.

[0024] Therefore, in order to determine the distance between receiving entity 1a and transmitting entity 1b, the data processing device 4 of receiving entity 1a receives time data 205 associated with the positioning signal 200 from transmitting entity 1b. The time data 205 is compared with its reception time to obtain a time difference, which constitutes an accurate estimate of the flight time (propagation time) of the positioning signal 200 (following the so-called "time of arrival" method). The obtained time difference allows the relative distance between entities 1a and 1b to be inferred by multiplying the time difference by the velocity of the positioning signal 200. This relative distance is also referred to as the relative position of transmitting entity 1b relative to receiving entity 1a. The accuracy of this distance measurement depends directly on the accuracy of clock 3, which is synchronized to obtain optimal accuracy.

[0025] To ensure the accuracy of the distance measurement between two entities 1 by the data processing device 4, it is preferable that the clocks 3 are synchronized relative to a reference clock 31, such as an atomic clock or a microatomic clock. Synchronization of the clocks 3 of network 100 can be performed according to the Precision Time Protocol (PTP) from the IEEE 1588v2 standard. The reference clock 31 preferably has an accuracy on the order of 10 nanoseconds, which allows for distance measurements with an accuracy of approximately 30 centimeters. In this example, the reference clock 31 can be carried by entity 1, which in turn includes a precision time server 32 that ensures the distribution of the time and frequency of the reference clock 31 broadcast within network 100, that is, the synchronization and tuning of the clocks 3 of other entities 1. Naturally, the precision time server 32 can be integrated into any type of entity 1 belonging to network 100, such as a fixed or mobile ground station. When a member of network 100 is outside the direct communication range of the precision time server, the time and frequency of the reference clock 31 can be relayed to that member by other entities 1 of network 100, which are within the transceiver device 5 of entity 1 including the precision time server 32.

[0026] On the other hand, the positioning device 2 of each entity 1 may also include a satellite positioning system 21, such as GNSS. The satellite positioning system 21 may optionally be combined with an inertial measurement unit 22 or an optical sensor 23, in which case the optical sensor 23 performs recalibration on a fixed reference frame or landmark. Thus, entity 1 can determine its position based on the satellite positioning system 21 and transmit its position to entity 1 of the network 100 within the range of the transceiver device 5 within the positioning signal 200. The position is associated with time data 205, which subsequently indicates the time at which the position was determined.

[0027] In this case, the data processing device 4 of the receiving entity 1a, which receives the positioning signal 200 including such absolute position from the transmitting entity 1b, implements a fusion (or mixing) method to obtain a precise absolute position from the fusion of the relative and absolute positions of the transmitting entity 1b.

[0028] Therefore, as Figure 4 As shown, the positioning signal 200 may include in its waveform an upslope 201 indicating a rise in signal power, an overshoot 202, a preamble 203, a pattern 204, time data 205, position and / or absolute position 206, a data sequence 207, and a downslope 208 indicating the end of the positioning signal 200 upon arrival at the positioning device 2. This waveform contains time data 205 at its physical layer level and the protocol of the IEEE 1588v2 standard at these MAC layer levels.

[0029] Network 100 allows for precise location of any entity 1, thanks to location method S implemented, for example, by data processing device 4 receiving entity 1a, which may include the following steps.

[0030] During step S1, the positioning device 2 generates a positioning signal 200 for entity 1a of network 100. The positioning signal 200 can include the position of entity 1a, for example in the form of coordinates provided by its positioning device 2.

[0031] During step S2, time data 205 indicating the generation time of positioning signal 200 is generated using the clock 3 of entity 1a. Where appropriate, time data 205 then indicates the time when the position was determined by positioning device 2.

[0032] During step S3, the transceiver 5 of receiving entity 1a receives a positioning signal 200 and time data 205 transmitted by the transceiver 5 of another entity 1b. The positioning signal 200 may symmetrically include the position of the other entity 1b, which is determined by the positioning device 2.

[0033] During step S4, the data processing device 4 uses time data 205 to determine the propagation time of the signal between entity 1a and entity 1b in order to infer the relative distance between entity 1a and the other entity 1b. In other words, the distance between entity 1a and entity 1b is calculated as previously described by using the flight time and propagation speed of the positioning signal 200. The data processing device 4 receiving entity 1a may optionally use a Kalman filter to further improve the accuracy of the relative distance measurement. Furthermore, the relative distance between entities 1a and 1b is also calculated based on their positions determined by the positioning device 2, which is broadcast and timestamped. The propagation time can then be derived from this relative distance. A Kalman filter may be used where appropriate.

[0034] Advantageously, entity 1a can also obtain the relative distance between entities 1a and 1b by calculating the distance between the positions of unit 1a and unit 1b, based on the position broadcast within the positioning signal 200 of another entity 1b. This second relative distance can be used to calculate the second propagation time of the positioning signal 200 between entities 1a and 1b by dividing the second relative distance by the propagation speed of the signal. This second propagation time can be fused or mixed with the propagation time derived from the time data 205 to obtain a more accurate propagation time. Using this more accurate propagation time in calculating the distance between entities 1a and 1b allows for further improvement in the accuracy of the calculation in step S4.

[0035] Optionally, the entity's clock 3 can be time-synchronized during step S0, preferably using the precise time protocol of the IEEE 1588v2 standard. This synchronization allows for better accuracy in measuring the distance between entities 1a and 1b. Where appropriate, clock 3 can be synchronized relative to a reference clock 31 during step S0 to further improve positioning accuracy.

[0036] During step S5, the positions of other entities 1b broadcast within the positioning signal 200 are fused with the relative distances of those entities 1b and the position of entity 1a to obtain a more precise position, namely, the absolute position 206 of the other entities 1b. More specifically, entity 1a uses its coordinates from its positioning device 2, the coordinates of the other entities 1b included in the positioning signal 200, and the relative distances of the other entities 1b calculated in step S4 to determine the absolute position 206 of the other entities 1b, which is more precise than a position obtained solely by the positioning device 2 or by using relative distances. Advantageously, the absolute position 206 can therefore be used to recalibrate the inertial measurement unit 22.

[0037] Of course, the positioning method S can be implemented simultaneously by all or part of the entities 1 of the network 100, so that each entity 1 knows the relative distance and absolute position 206 of all or part of the other entities 1.

[0038] Specifically, the positioning method S can be implemented to determine the position of the receiving entity 1a, excluding the functional positioning device 2, based on the absolute positions 206 of the four transmitting entities 1b, 1c, 1d, and 1e, each equipped with a positioning device 2. To this end, during step S6, the data processing device 4 of the receiving entity 1a uses the distances between the four transmitting entities 1b, 1c, 1d, and 1e of the network 100 to determine the absolute position 206 of the receiving entity 1a through trilateration.

[0039] Synchronization of clock 3 with reference clock 31 enables improved accuracy of relative distance measurements. Due to step S5, network 100 is able to compensate for inaccuracies in the position provided by satellite positioning system 21, thus enabling each entity 1 to accurately determine the position of other entities 1 that are members of network 100. This is particularly advantageous when entity 1 is an autonomous drone flying in close formation or swarm.

[0040] In the case that entity 1 is a vehicle, entity 1 also includes a guidance unit 7. Then, due to the positioning method described above, network 100 implements guidance method E according to the determined absolute position 206 of receiving entity 1a, making it possible for receiving entity 1a to be guided by another transmitting entity 1b.

[0041] Then, the transmitting entity 1b generates guidance instructions for the receiving entity 1a based on the absolute position 206 thus determined. If the receiving entity 1a is an autonomous vehicle, the guidance instructions can be received by the driving unit 71 of the receiving entity 1a, and appropriate commands can be generated to modify the vehicle's trajectory. Conversely, when the receiving entity 1a is a driven vehicle, the guidance instructions can be displayed, for example, on an interface visible to the driver.

[0042] The iterative implementation of positioning method S enables the transmitting entity 1b to know the trajectory, velocity, and acceleration of the receiving entity 1a based on the continuous absolute position of the receiving entity 1a. Guiding instructions can then be generated to maintain a predetermined safe distance 9 between entity 1a and other entities 1b, 1c, 1d, and 1e of network 100.

[0043] This guidance method E can also be used, for example, in the case of a landing method. In this case, the transmitting entities 1b, 1c, 1d, and 1e can be fixed stations, and the landing point 10 can be designated as a point equidistant from these four stations. Then, when the absolute position 206 of the receiving entity 1a is the position of the equidistant point 10, the guidance instructions can include dwell instructions.

[0044] Alternatively, if none of entities 1a, 1b, 1c includes satellite positioning system 21, or if such a system cannot establish their positions, for example in the event of interference, network 100 still enables guidance method E to be implemented using only the relative positions of each entity. Based on the continuous relative positions of each entity 1a, 1b, 1c with respect to other entities, the trajectories, velocities, and relative accelerations of entities 1a, 1b, 1c can be established. Guidance instructions can then be generated to maintain the predetermined safe distance 9 between entity 1a and other entities 1b, 1c of network 100 by comparing the respective relative distances with a predetermined safe distance 9.

[0045] Furthermore, the synchronization of the clock 3 of entity 1 in network 100 enables the implementation of a method for a secure system 51 for synchronizing transmissions transmitted and received by entity 1 within network 100.

[0046] For this purpose, time data 205 indicating the generation time of the synchronization signal is generated. The signal transmitted by the first entity 1 is received by the other entity 1 via their respective transceiver devices 5.

[0047] At least one other entity 1 receives time data 205. Based on this time data 205, a security system 51 for the transmissions of entity 1 and at least one other entity 1 is synchronized. The security system 51 is, for example, a TRANSEC (Transmission Secure) device for controlling frequency hopping in the frequency used by the transceiver device 5 of entity 1. Time synchronization then allows for more precise frequency hopping, which reduces latency and limits potential communication losses between entities 1, and enhances the security of their exchanges.

[0048] Because of the time data 205 exchanged by entity 1, network 100 enables precise positioning of entity 1 and the implementation of the described method. This provides numerous additional advantages, including sub-meter accuracy in determining the relative positions between entities 1, sharing of the position and trajectory of each entity 1, coordinated close platooning by maintaining a predetermined safe distance when entity 1 is a vehicle, and ensuring the security of transmission. Therefore, network 100 enables positioning, navigation, and time synchronization (position navigation timing) of entity 1 with accuracy far superior to existing systems.

[0049] These advantages are particularly evident when the first entity 1 is a fighter jet carrying multiple second entities 1 (which are munitions). The fighter jet, including the reference clock 31 and the satellite positioning system 21, serves as a reference node for allocating precise time and as a reference point for navigating other entities in the network 100 entities, which may lack these components due to carrying capacity or cost reasons.

[0050] Subsequently, the ammunition separates from the fighter jet. Then, network 100 enables the measurement of the relative positions between various entities 1 and provides the absolute position of each entity.

[0051] In the event of a temporary loss of communication, network 100 enables the radio connection established via transceiver device 5 of entity 1 to restore precise time synchronization, gradually determine the relative position of entity 1, and broadcast the absolute position of each entity 1 within range to other entities via network 100.

Claims

1. A network (100) comprising a plurality of entities (1), each entity (1) forming a node of the network (100), wherein, Each entity (1) includes: - Positioning device (2), configured to generate positioning signal (200); - Clock (3), configured to generate time data (205) indicating the generation time of the positioning signal (200); and - A data processing device (4) is configured to determine the propagation time of the positioning signal (200) between two entities (1) in the network (100) by means of the positioning signal (200) and the time data (205), and thereby infer the distance between the two entities (1).

2. The network (100) according to claim 1, wherein, Each entity (1) also includes a transceiver device (5) configured to transmit and receive the positioning signal (200) and the time data (205).

3. The network (100) according to any one of claims 1 or 2, wherein, Each positioning device (2) of entity (1) further includes a satellite positioning system (21) and at least one of the following: an inertial measurement unit (22) and an optical sensor (23), wherein the positioning signal (200) includes the position of the entity (1).

4. An entity (1) of nodes forming a network (100), said entity (1) comprising: - Positioning device (2), configured to generate positioning signal (200); - Clock (3) is configured to generate time data (205) indicating the generation time of the positioning signal (200); and - A data processing device (4) is configured to determine the propagation time of the location signal (200) of another entity (1) of the network (100) by means of the location signal (200) and the time data (205), and thereby infer the distance between the two entities (1).

5. The entity (1) according to claim 4 further includes a transceiver device (5) configured to transmit and receive the positioning signal (200) and the time data (205).

6. Entity (1) according to any one of claims 4 and 5, wherein, The positioning device (2) further includes a satellite positioning system (21) and at least one of the following: an inertial measurement unit (22) and an optical sensor (23), wherein the positioning signal (200) includes the position of the entity (1).

7. A method S for locating an entity (1b) of a network (100) according to any one of claims 1 to 3, comprising the following steps: S1: The location signal (200) of entity (1a) of the generation network (100); S2: Generate time data (205) indicating the generation time of the positioning signal (200); S3: The positioning signal (200) and the time data (205) are received by at least one other entity (1b); and S4: Based on the positioning signal (200) and the time data (205), determine the propagation time of the signal between an entity (1a) of the network (100) and at least one other entity (1b) of the network (100), and then deduce the distance between the entity (1a) of the network (100) and at least one other entity (1b) of the network (100).

8. The positioning method S according to claim 7, comprising step S0 of synchronizing the entity (1) with a reference clock (31) that is capable of corresponding to the clock (3) of one of the entities (1) of the network (100).

9. The positioning method S according to any one of claims 7 and 8, for positioning entity (1a) via another entity (1b), wherein, Steps S3 and S4 are implemented by a plurality of other entities (1b, 1c, 1d, 1e) of the network (100).

10. The positioning method S according to any one of claims 7 to 9, wherein, Step S4 includes using a Kalman filter.

11. The positioning method S according to any one of claims 9 to 10 further includes an absolute positioning step S5: positioning all or part of the other entities (1b) of the network (100) to obtain the absolute position (206) of the entity (1).

12. The positioning method S according to claim 11 further includes step S6: determining the absolute position (206) of the fifth entity (1a) of the network (100) by trilateration based on the absolute positions (206) of the four entities (1b, 1c, 1d, 1e) of the network (100).

13. A method E for guiding a vehicle (1), comprising the following steps: - The absolute position (206) of entity (1) of the positioning network (100) according to claim 12, wherein entity (1) includes the vehicle (1); and -Guide the vehicle (1).

14. A method P for synchronizing a secure system (51) for transmissions in a network (100) according to any one of claims 1 to 3, comprising the following steps: - Generate time data (205) indicating the generation time of the signal; - The time data (205) is received by at least one other entity (1); and - Based on the time data (205), a security system (51) synchronizes the transmission of the entity (1) and the at least one other entity (1).

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