Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
  • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
  • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
  • G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
  • G01C21/188—Compensation of inertial measurements, e.g. for temperature effects for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
  • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
  • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
  • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
  • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
  • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/42—Determining position
  • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
  • G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/13—Receivers
  • G01S19/20—Integrity monitoring, fault detection or fault isolation of space segment
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
  • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
  • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
  • G01S19/393—Trajectory determination or predictive tracking, e.g. Kalman filtering

Definitions

• DESCRIPTION TITLE Method for determining at least one protection radius associated with at least one navigation parameter, the method being implemented by an electronic determination device
• the present invention relates to a method for determining a radius of protection associated with at least one navigation parameter of a wearer, such as the position, speed, attitudes, and/or heading of the wearer.
• the present invention also relates to an electronic determination device configured to implement such a determination method.
• the present invention also relates to a computer program product capable of implementing such a determination method.
• the invention relates to the field of integrated localization of a carrier, for example a mobile carrier.
• integral localization is meant an estimation of navigation parameter(s), such as the position, speed, attitudes, and/or heading of a carrier and the provision of a protection radius associated with the ( x) navigation parameter(s) considered. Thus, it is guaranteed that an error in estimating the navigation parameter remains within the protection radius, according to a predefined probability. It is known to estimate navigation parameters such as the position, speed, attitudes and heading of the wearer by carrying out a hybridization from a GNSS (Global Navigation Satellite System) position estimated by a system satellite positioning and inertial measurements from an inertial measurement unit (IMU). When carrying out such an estimation, errors are likely to disrupt the estimation of the wearer's navigation parameters.
• GNSS Global Navigation Satellite System
• the first type of error is generally modeled by a random variable which follows a continuous probability law. It is often assumed that the distribution of errors of the first type follows a normal law. By definition, the normal distribution is a probability distribution, often called Gaussian. In this case, it is clear that the values of the errors of the first type are not bounded. However, the distribution of errors of the first type being known, it is possible to determine a bound which guarantees, for a predefined probability, that errors of the first type remain included in said bound. Errors of the first type are hereinafter called “rare and normal errors”.
• rare and normal errors most often come from intrinsic characteristics of the sensors used and which have an impact on the estimation of the wearer's navigation parameters.
• a respective protection radius of at least one navigation parameter of the wearer such as position, speed, attitudes and/or heading.
• the second type of error concerns bounded but unmodeled errors. Errors of the second type are included in an interval, formed by two limits, but for which the distribution model is unknown. Errors of the second type are called “bounded errors” in the rest of the description.
• bounded errors correspond for example to errors linked to the use of incorrect ephemeris for calculating the GNSS position, or to a satellite clock failure in one of the satellites necessary for calculating the GNSS position. It is not possible to know or predict the distribution or temporal evolution of errors of the second type. Only the interval of evolution of the error is known with a probability which guarantees that the error remains between the limits of this interval with a level of confidence characterized by this probability.
• Document US9341718B2 attempted to provide a bounded error model. Analogously, in the article “Merging Kalman Filtering and Zonotopic - State Bounding for Robust Fault Detection under noisysy Environment” by C.
• an object of the invention is to improve the determination of the protection radius associated with a navigation parameter.
• the subject of the invention is a determination method intended to limit an error induced on at least one navigation parameter of a carrier, in particular a position, a speed, attitudes, and/or a heading of the carrier, the error being induced by a measurement error whose temporal evolution is unknown but whose limit is known and the probability of not exceeding this limit is also known; the limit and the probability being known for a plurality of instants at which the method is implemented, the fact of limiting the induced error being obtained by determining at least one protection radius associated with the wearer's navigation parameter(s), the method being implemented by an electronic determination device and comprising the following steps: - reception, at successive reception times, of a measurement from of a sensor, such as a GNSS receiver, in particular a GNSS
• the steps of calculating N transfer matrices and determining the protection radius from these N transfer matrices make it possible to take into account, simply and quickly, bounded errors in determining the protection radius.
• the risk that the error in the wearer's navigation parameter is greater than the protection radius is minimized without requiring a significant computational load.
• the method has the effect of limiting the error induced on the navigation parameters of a carrier, such as the position, speed, attitudes and/or heading of the carrier.
• the induced error is generated by a measurement error whose temporal model is not known but whose bound is known deterministically or with a given probability of not exceeding this bound.
• the determination method comprises one or more of the following characteristics, taken in isolation or in all technically possible combinations: - for each instant of reception, the measurement from the sensor comprises M components, and the method further comprises for each reception instant, between the reception step and the step of determining an estimated state vector, an evaluation step comprising: - for each component of the measurement coming from the sensor, calculation of a unit gain of the filter; and - evaluation of a gain from the M unit gains, during the step of determining the estimated state vector and the step of calculating the error propagation matrix and the influence matrix of the bounded error, the gain of the estimation filter being the evaluated gain; - for each reception instant, during the first calculation step, the estimation error propagation matrix at said reception instant is equal to: ⁇ ⁇ ( ⁇ ⁇ )( ⁇ ⁇ ⁇ ( ⁇ ⁇ ) ⁇ ( ⁇ ⁇ )), where: - F(T N ) is the propagation matrix of the state vector at said reception instant; - I is the identity matrix; - K
• the invention also relates to an electronic device for determining at least one protection radius associated with a navigation parameter of a carrier, the electronic determination device comprising technical means suitable for implementing a determination method such as described above.
• the invention also relates to a computer program product comprising software instructions which, when executed by a computer, are capable of implementing such a determination method.
• Figure 2 is a flowchart of a determination method according to the invention, implemented by the determination device of Figure 1; and - [Fig.3]
• Figure 3 is an explanatory diagram of a registration step of the method of Figure 2, illustrated in an example.
• a carrier 5 is mobile in an environment.
• the carrier 5 carries a sensor capable of providing measurements, such as a GNSS receiver 10 capable of receiving GNSS signals, an inertial positioning device 11 capable of providing inertial measurements and an electronic determination device 15 configured to determine at least one protection radius associated with at least one navigation parameter of the carrier 5.
• GNSS a satellite positioning system (Global Navigation Satellite System).
• the receiver 10 is a barometric sensor, a Loch sensor, an odometer, a vision sensor, a LIDAR sensor (from English, Laser Imagining Detection And Ranging), a SONAR sensor (from English, Sound Navigation And Ranging), a RADAR sensor (from English, Radio Detection And Ranging), a Doppler DVL velocity sensor (from English, Doppler Velocity Log), or a Pitot tube.
• the carrier 5 is for example an aircraft, such as a drone, a plane or a helicopter, moving in space in three dimensions, or a land or maritime vehicle moving in a plane in two dimensions, or by example a railway vehicle moving in a single direction following a railway track.
• the GNSS receiver 10 is configured to receive GNSS signals from satellite(s) belonging to the same GNSS system, such as for example the GPS system.
• the GNSS receiver 10 comprises for example a reception antenna 12 known per se and a calculation module 13.
• the antenna 12 is configured to receive GNSS signals from a plurality of satellites and transmit them in the form of electrical signals to the module calculation 13. Without loss of generality, it will be considered in the remainder of the description that the measurement from the sensor is a GNSS position. It is clear that what will be described subsequently can also be generalized to other types of measurements from other sensors.
• the calculation module 13 is for example capable of determining a GNSS position of the receiver 10 from the GNSS signals received by the antenna 12, using techniques known per se.
• the GNSS position for example, has the form of a vector comprising three components: a GNSS longitude, a GNSS latitude and a GNSS altitude.
• the GNSS position includes rare and normal errors on the one hand and bounded errors on the other hand. Bounded errors are included in a finite interval but the probability that they take certain values in this interval is indeterminable. More specifically, the bounded errors linked to the horizontal position of the carrier 5 are included in the interval [-HIL; HIL], where HIL is a value of a horizontal error threshold capable of changing over time.
• the bounded error linked to the position vertical of the carrier 5 is included in the interval [-VIL; VIL], where VIL is a value of a vertical error threshold capable of changing over time.
• VIL is a value of a vertical error threshold capable of changing over time.
• These thresholds are for example directly provided at the output of the receiver 10 and are for example calculated in accordance with the RAIM (Receiver Autonomous Integrity Monitoring) algorithm defined by the RTCA DO-229 standard.
• the calculation module 13 is configured to form an error terminal S from the horizontal HIL and vertical VIL threshold values.
• the error bound S includes three components, the first two of which are equal to the horizontal error threshold HIL. The third component is then equal to the vertical error threshold value VIL.
• the calculation module 13 is further configured to send, to the determination device 15, the calculated GNSS position as well as the error terminal S.
• the inertial positioning device 11 comprises for example an inertial measurement unit or IMU (from the 'English Inertial Measurement Unit) configured to measure linear accelerations and angular velocities of the carrier 5 in three mutually orthogonal directions.
• the inertial positioning device 11 is configured to determine, from these accelerations and these angular velocities, the inertial position of the carrier 5, according to a technique known per se, for example by applying a triple integration.
• this technique includes for example a first integration of the attitude of the wearer 5 and then, a projection of the orientation of different axes of the sensors and a double integration of the results.
• the inertial position has for example the form of a vector of three components: an inertial longitude, an inertial latitude and an inertial altitude.
• the inertial positioning device 11 is configured to further transmit to the determination device 15 the determined inertial position.
• the determination device 15 comprises an input module 17, a processing module 20 and an output module 25.
• the input module 17, the processing module 20 and the output module 25 are each produced in the form of software stored in one or more storage means (such as a hard disk or a flash disk) and implemented by one or more processors, memory (RAM) and other computer components known in self. These components are then included in the same computer or in different computers/servers.
• the computers/servers are connected by a local or global network.
• at least part of these modules 17, 20 and 25 takes the form, at least partially, of an independent electronic component, such as for example a programmable logic circuit of the FPGA type (from the English field-programmable gate array) or other.
• the input module 17 is configured to receive, at a plurality of reception times T N , the GNSS position and the error terminal S (T N ) from the GNSS receiver 10, and the inertial position from the monitoring device. inertial positioning 11.
• the input module 17 is configured to transmit to the processing module 20, the information received, namely: the GNSS position, the error terminal S(T N ) and the inertial position received at the instant reception T N .
• the formulation “W(T N )” designates the value of the quantity “W” at the reception instant T N.
• the processing module 20 is configured to process the information received to determine the protection radius RP(TN) associated with a navigation parameter of the carrier 5.
• the processing module 20 is configured to process the information received as described below in relation to the determination method according to the invention.
• the processing module 20 includes an estimation filter, comprising a gain KR, an observation matrix H and a propagation matrix F of an estimated state vector X.
• the gain KR, the observation matrix H, the propagation matrix F and the estimated state vector X are capable of evolving over time. For this reason, they will subsequently be respectively denoted under the references KR(TN), H(TN), F(TN), and X(TN).
• the estimation filter is for example a Kalman filter in one of its forms such as an Extended Kalman Filter.
• the processing module is in particular configured to carry out, for each instant of reception TN, a fusion of data between the GNSS position and the inertial position, from the estimation filter and according to a technique known per se. This data fusion makes it possible to estimate the estimated state vector X(T N ).
• the observation matrix H(T N ) is the matrix determining the observable components of the estimated state vector X(T N ).
• observationable components we mean the measured components of the estimated state vector. In the example presented, the observable components correspond to the positions of the carrier 5.
• the propagation matrix F(T N ) is the matrix connecting the estimated state vector X(T N ) at the reception instant T N to the vector estimated state X(T N+1 ) at the following reception time T N+1 .
• the classic formulation of the Kalman filter makes it possible to reset the estimate of a state vector at each reception instant T N using a measurement vector z(T N ) for example equal to the difference between the GNSS position and the inertial position received at the reception time T N .
• Equations 1 are recursive, that is to say that the knowledge of the state variables X(TN), the gain KR(TN), the measurement vector z(TN), the observation matrix H( TN) and the covariance matrix P(TN) for the reception instant TN are necessary to calculate the estimated state vector X(T N+1 ) and the covariance matrix P(T N+1 ) for the following reception instant T N+1 .
• the processing module preferably includes in its memory a transfer matrix shift register and a threshold shift register whose usefulness will be detailed below.
• the output module 25 is connected to the processing module 20.
• output module 25 is configured to transmit to a user or to another electronic device not shown, the determined protection radius RP(T N ) and optionally the navigation parameter with which the protection radius RP(T N ) is associated. If the output module 25 is configured to communicate with a user, this communication is carried out, for example, using a screen not shown.
• the determination method implemented by the electronic determination device 15 according to the invention will now be explained with reference to Figure 2 presenting a flowchart of this method and to Figure 3 illustrating a step of this method. Initially, the carrier 5 moves in an environment and the GNSS receiver 10 receives, through its antenna 12, GNSS signals from a plurality of satellites. The calculation module 13 calculates the information mentioned above and transmits it to the determination device 15.
• the inertial positioning device 11 calculates the inertial position and transmits it to the input module 17.
• N is the number of reception times T i .
• the processing module 20 includes the evaluation of a gain KR(TN) of the estimation filter.
• the unit gains correspond to the gains used during successive adjustments component by component of the measurement vector received at the reception instant TN.
• the processing module applies, for example, the following equation, recursive to the number of measurements: [ MATH 2] where: - I is the identity matrix, - ⁇ designates the matrix product, - (TN) is the gain calculated at the time of reception TN for a measurement vector z(TN) comprising “M” component(s), and ⁇ ⁇ +1( ⁇ ⁇ ) is the observation matrix associated with the unit gain Kj+1(TN) calculated at the reception instant T N for the j+1-th component of the measurement vector z (T N ).
• Equation 2 originates from the fact that the gain K R (T N ) must respect the following equation: where: - for all j, ⁇ ⁇ , ⁇ ( ⁇ ⁇ ) is the j-th column of the gain K R (T N ), and - for all j, Hj(TN) is the j-th line of the observation matrix H(TN).
• the measurement vector z(TN) comprises three components since the GNSS position and the inertial position respectively comprise three components.
• Equation 2 gives a gain K R (T N ) equal to: [ MATH 4]
• the estimated state vector (X(T N )) of the carrier 5 is determined from the gain K R (T N ) evaluated during the evaluation step 120, the observation matrix H(T N ) and the propagation matrix F(T N ), for example according to equation 1 by initializing the estimated state vector X(T1) to zero for the first moment of reception T1.
• the processing module 20 calculates an estimation error propagation matrix A(TN) of the state from the propagation matrix of the state vector F( TN), the gain KR(TN) of the estimation filter and the observation matrix H(TN).
• the estimation error propagation matrix A(T N ) is calculated from the gain K R (T N ) of the filter estimate.
• each bounded error of the bounded error vector ⁇ ⁇ ⁇ ( ⁇ ⁇ ) has an unknown value, between the HIL value; VIL of the associated component in the error bound S(TN) and the opposite of the value –HIL; -VIL of the associated component in the error terminal S(TN).
• [ MATH 11 ] ⁇ (3,3) ⁇ ( ⁇ 3) ⁇ ⁇ ( 3,2
• the second calculation step 150 and the registration step 160 are preferably implemented simultaneously.
• the processing module 20 shifts each shift register to free a memory slot in each shift register.
• the processing module 20 multiplies each of the first N-1 values of the transfer shift register by the error propagation matrix A (TN) calculated at the instant reception TN and writes in the freed box of this register the influence matrix of the bounded error B(TN) calculated at said reception instant TN.
• the processing module 20 registers, in the freed box of the threshold register(s), the error terminal S(TN) received at the reception instant TN.
• each shift register includes a predetermined number of memory slots. This predetermined number of memory slots is also called “shift register depth”.
• the processing module 20 shifts each shift register, the transfer matrix V(N-1,L) calculated at the previous instant TN-1 and for the moment the oldest TL present in the transfer shift register, is evicted from the transfer shift register.
• the error terminal S(T L ) received at the same earliest instant T L is expelled from the threshold shift register(s).
• the depth of the shift register is therefore equal to N-L+1.
• the depth of each shift register is for example equal to 100, 50 or 10.
• the processing module 20 determines the navigation parameter of the carrier 5 from the estimated state vector navigation is the vertical position of the carrier 5, that is to say its altitude.
• Each horizontal-horizontal transfer submatrix ⁇ h,h ( ⁇ , ⁇ ) is therefore a matrix of dimensions 2-2.
• Each horizontal-vertical transfer submatrix ⁇ h, ⁇ ( ⁇ , ⁇ ) is therefore a matrix of dimensions 2-1.
• the variable ⁇ in subscript is either equal to 1 if the depth of the shift register is greater than the number of values stored in said register, or to L if the shift register is already full and the depth of the register is equal to N- L+1.
• the processing module 20 calculates for example each unit contribution PL(Ti) from the following equation: where: - ⁇ ⁇ is the square root function, - ⁇ ⁇ ⁇ ( ⁇ ) is the function for calculating the eigenvalue(s), - max( ⁇ ) is the maximum function, and - ⁇ ⁇ is the matrix transpose.
• the processing module 20 performs the following actions.
• Each vertical-horizontal transfer submatrix ⁇ ⁇ ,h ( ⁇ , ⁇ ) is therefore a matrix of dimensions 1-2.
• Each submatrix vertical-vertical transfer ⁇ ⁇ , ⁇ ( ⁇ , ⁇ ) is therefore a matrix of dimension 1-1. That is, each vertical-vertical transfer matrix ⁇ ⁇ , ⁇ ( ⁇ , ⁇ ) is a scalar number.
• the processing module calculates for example each unit contribution PL(Ti) from the following equation: where
• the protection radius RP(TN) is then for example calculated by the following equation: [MATH 15]
• a second alternative embodiment, for example combinable with the first alternative embodiment, is now presented. This variant can for example be used for each loss instant T P for which the GNSS position and/or the error terminal S(T P ) is lost or invalidated. For these moments, the method does not include the evaluation step 120.
• the estimated state vector that is to say without adjustment. This amounts to setting the gain K R (T N ) to zero for these instants.
• the processing module 20 freezes the threshold shift register. In other words, the processing module does not perform any shifting of the threshold shift register.
• the determination of the protection radius RP(TN) is improved.
• the probability that the error on the navigation parameter is greater than the protection radius RP(TN) is, for example, less than 10 -7 /h.
• the calculation of the protection radius RP(TN) is simple and quick to implement.
• the optional evaluation step 120 allows real-time adjustment using the gain K R (T N ) of the estimation filter while limiting the risk that numerical approximations affect the characteristic(s) of the matrices of the estimation filter. estimate.
• the determination of the protection radius RP(T N ) is further improved since it takes into account bounded errors on the one hand and rare and normal errors on the other hand.
• the determination method is more robust since it allows the protection radius to continue to be determined even when the GNSS position is lost.

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• Engineering & Computer Science (AREA)
• Radar, Positioning & Navigation (AREA)
• Remote Sensing (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Computer Networks & Wireless Communication (AREA)
• Automation & Control Theory (AREA)
• Position Fixing By Use Of Radio Waves (AREA)
• Navigation (AREA)
• User Interface Of Digital Computer (AREA)

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• 2022
  • 2022-03-23 FR FR2202568A patent/FR3133915B1/fr active Active
• 2023
  • 2023-03-15 EP EP23712001.9A patent/EP4496982A1/de active Pending
  • 2023-03-15 US US18/848,520 patent/US20260086248A1/en active Pending
  • 2023-03-15 WO PCT/EP2023/056635 patent/WO2023180143A1/fr not_active Ceased
  • 2023-03-15 CN CN202380036834.5A patent/CN119137446A/zh active Pending

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