Classifications

• • 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
  • G01S19/42—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
  • G01S19/38—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
• • 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
  • G01S19/14—Receivers specially adapted for specific applications
• • 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
  • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
  • G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Definitions

• TITLE Navigation and positioning device and method
• the present invention relates to a navigation and positioning device, suitable for being on board a vehicle capable of moving between two distinct geographical positions, the device comprising at least: an inertial measurement unit suitable for providing navigation measurements , a GNSS satellite positioning measurement receiver, a main closed-loop Kalman filter configured to calculate navigation data corrections by hybridization of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit, said corrections being reapplied by looping back to the input of said main Kalman filter.
• the invention also relates to a vehicle comprising such a navigation and positioning device.
• the invention also relates to a navigation and positioning method implemented by such a navigation and positioning device.
• the invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a navigation and positioning method.
• the present invention relates to the navigation of a vehicle capable of moving between two distinct geographical positions, such as a land vehicle, an aircraft, or preferably a naval vehicle such as a ship or even a naval vessel.
• the vehicle generally carries a satellite navigation and positioning system receiver configured to determine, in particular by trilateration, a positioning (i.e. a geolocation position or even a geolocation solution) of the aircraft using estimates distances to visible satellites of the same or several satellite constellations of the satellite navigation and positioning system.
• a positioning i.e. a geolocation position or even a geolocation solution
• Examples of satellite navigation systems are the American GPS system, the European GALILEO system, the Russian GLONASS system, or the Chinese BEIDOU system, etc.
• vehicles also have other navigation systems such as one or more INS inertial measurement unit(s). Navigation System), baro-altimeters, anemometers, etc.
• An inertial measurement unit is made up of a set of inertial sensors (accelerometers, gyrometers) associated with processing electronics, and provides low-noise and precise information in the short term, but its performance degrades in the long term, particularly in the long term. made of the sensors that compose it.
• Such vehicles then implement, for predetermined applications, a position measurement hybridization technique known as INS/GNSS hybridization, capable of providing vehicle location with a precision of the same order of magnitude as the localization by GNSS and very precise attitude and heading angles, while ensuring continuity of service when GNSS is unavailable.
• INS/GNSS hybridization a position measurement hybridization technique
• INS/GNSS hybridization implemented according to current techniques is not optimal for guarding against GNSS errors in the event of satellite failure, GNSS software or hardware fault or even intentional or unintentional interference, nor to provide positioning integrity when such errors occur.
• the aim of the invention is then to propose a navigation and positioning device which at least makes it possible to maintain the integrity of the positioning independently of the vulnerability of the GNSS measurements.
• the subject of the invention is a navigation and positioning device, suitable for being on board a vehicle capable of moving between two distinct geographical positions, the device comprising at least:
• an inertial measurement unit capable of providing navigation measurements
• a main closed-loop Kalman filter configured to calculate navigation data corrections by hybridization of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit
• the device comprising in in addition to a bank of N closed-loop secondary Kalman filters with N a predetermined integer such that each secondary Kalman filter being configured to calculate navigation data corrections solely from the non-satellite positioning data provided at least by said inertial measurement unit, each secondary Kalman filter of index i, with being capable of reconfiguring itself on the main Kalman filter at an instant (j - 1)T from the start of navigation of the vehicle, then periodically according to a period NxT, with T a predetermined duration, the N secondary Kalman filters being identical and independent, the period NxT corresponding to a period of verification of the integrity of said GNSS satellite positioning measurements, the device also being configured to:
• the navigation and positioning device has a particular architecture where the secondary Kalman filters (i.e. Kalman sub-filters) are each capable of reconfiguring themselves periodically, according to a period NxT on the main Kalman filter (i.e. to copy the state vector and the covariance matrix of the main Kalman filter into the state vector and the covariance matrix of the secondary filter) and this successively each in turn.
• the secondary Kalman filters i.e. Kalman sub-filters
• the particular architecture of the navigation and positioning device according to the present invention makes it possible to carry out a time-shifted adjustment.
• none of the secondary Kalman filters use GNSS measurements as input to calculate their navigation data corrections, which makes them each invulnerable to a possible GNSS error.
• the period NxT allows each secondary Kalman filter to take advantage of the short-term precision of the position measurements, received as input, and obtained only from the non-satellite measurements provided at least by said inertial measurement unit.
• the navigation and positioning device comprises one or more of the following characteristics, taken in isolation or in all technically possible combinations:
• the device is also configured to determine said predetermined threshold as a function of a false alarm probability; - in the event of an alarm being raised, the main Kalman filter is also configured to reconfigure itself on a predetermined secondary Kalman filter of index p with
• said predetermined secondary Kalman filter of index p on which the main Kalman filter is capable of reconfiguring itself in the event of an alarm being raised is the secondary Kalman filter among said N secondary Kalman filters whose reconfiguration on the filter of the main Kalman is temporally furthest from the moment the alarm is raised;
• said main Kalman filter is configured to no longer use said GNSS satellite positioning measurements as input from the moment the main Kalman filter initiates its reconfiguration;
• the device is also configured to determine a protection radius with respect to a vulnerability of said GNSS satellite positioning measurements, said protection radius guaranteeing that the value of the distance between the hybrid position provided from said main filter of Kalman and the true position of said vehicle is less than the value of said protection radius, said protection radius depending on the number N of secondary Kalman filters;
• the device is also configured to provide, at output, in parallel, navigation solutions respectively associated with said bank of N secondary Kalman filters, and said main Kalman filter.
• the invention also relates to a vehicle comprising such a navigation and positioning device.
• the invention also relates to a navigation and positioning method implemented by said navigation and positioning device and comprising the following steps implemented in parallel or successively one after the other or vice versa:
• determining a protection radius with respect to a vulnerability of said positioning measurements by GNSS satellites said protection radius guaranteeing that the value of the distance between the position hybrid provided from said main Kalman filter and the true position of said vehicle is less than the value of said protection radius, said protection radius depending on the number of secondary Kalman filters.
• said localization step comprises supplying at output, in parallel, navigation solutions respectively associated with said bank of N secondary Kalman filters, and said main Kalman filter.
• the invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a satellite navigation and positioning method as defined above.
• Figure 1 is a diagram illustrating a navigation and positioning device suitable for implementing INS/GNSS hybridization, and optionally with additional measurements provided by equipment separate from a positioning measurement receiver by GNSS satellites and distinct from said inertial measurement unit;
• Figure 2 is a diagram illustrating the architecture of the Kalman filter bank according to the present invention.
• Figure 3 illustrates the closed loop principle
• Figure 4 is a flowchart of a navigation and positioning method according to the present invention.
• Figure 1 is an overall representation of a navigation and positioning device 10 according to the present invention, suitable for implementing INS/GNSS hybridization, and optionally with additional measurements provided by equipment separate from a measurement receiver positioning by GNSS satellites and distinct from said inertial measurement unit, and comprising at least one inertial measurement unit 12 capable of providing navigation measurements, in particular to a virtual platform 14 for calculation and location, a receiver 16 for measurements of positioning by GNSS satellites, and optionally a receiver 18 of complementary measurements provided by at least one piece of equipment distinct from said receiver 16 of positioning measurements by GNSS satellites and distinct from said inertial measurement unit 12, and finally a set K of Kalman filters.
• the inertial measurement unit 12 consists of a set of inertial sensors such as gyrometers and accelerometers associated with processing electronics and is capable of providing increments 20 of angular rotation and speed of the vehicle in which the device 10 navigation and positioning is on board.
• the virtual calculation platform 14 integrates such angular rotation and speed increments 20 to provide, as input to the set K of Kalman filters, navigation data 22, such as the orientation of the vehicle, in terms of roll , pitch, yaw, heading, etc., the speed of the vehicle for example the speed Vnord in the North direction, the speed Vest in the East direction, the speed Vbas at the bottom of the trajectory etc., and the position of the vehicle for example in latitude, longitude, altitude.
• navigation data 22 such as the orientation of the vehicle, in terms of roll , pitch, yaw, heading, etc.
• the speed of the vehicle for example the speed Vnord in the North direction, the speed Vest in the East direction, the speed Vbas at the bottom of the trajectory etc.
• the position of the vehicle for example in latitude, longitude, altitude.
• the GNSS satellite positioning measurement receiver 16 is capable of providing, according to arrow 24, information on the position and speed of the vehicle by triangulation from the signals emitted by moving satellites visible from the vehicle.
• the information provided may be temporarily unavailable because the receiver must have a minimum of four satellites in direct view of the positioning system to be able to make a point.
• They are also of variable precision, depending on the geometry of the constellation at the base of the triangulation, and noisy because they are based on the reception of very low level signals coming from distant satellites having low transmission power. But they do not suffer from long-term drift, the positions of the satellites passing through their orbits being known precisely over the long term. Noise and errors can be related to satellite systems, the receiver or signal propagation between the satellite transmitter and the GNSS signal receiver.
• the optional receiver 18 for complementary measurements 26 provided by at least one piece of equipment distinct from said receiver 16 for positioning measurements by GNSS satellites and distinct from said inertial measurement unit 12 provides for example a reset on zero movement when the vehicle is stationary, a measurement Electromagnetic log and a dynamic model of the vehicle, a Doppler log or speed measurement in water when the equipment is a DVL (Doppler Velocity Log), depth measurement, radar registration, imaging , by opportunity signals etc.
• the hybridization implemented by the set K of Kalman filters consists of mathematically combining the measurements 22, 24, 26 provided respectively by the inertial measurement unit 12, the receiver 16 for GNSS satellite positioning measurements, and the optional receiver 18 of complementary measurements 26 to obtain position and speed information by taking advantage of the three elements 12, 16 and 18.
• Kalman filtering is based on the possibilities of modeling the evolution of the state of a physical system considered in its environment, by means of a so-called “evolution” equation (a priori estimation), and of modeling of the dependency relationship existing between the states of the physical system considered and the measurements of an external sensor, by means of a so-called “observation” equation to allow adjustment of the states of the filter (a posteriori estimation).
• the effective measurement or "measurement vector” makes it possible to make an a posteriori estimate of the state of the system which is optimal in the sense that it minimizes the covariance of the error made on this estimate.
• the estimator part of the filter generates a posteriori estimates of the system state vector using the difference observed between the effective measurement vector and its a priori prediction to generate a corrective term, called innovation.
• This innovation after multiplication by a gain vector of the Kalman filter, is applied to the a priori estimate of the state vector of the system and leads to obtaining the optimal a posteriori estimate.
• the Kalman filtering implemented by the set K of Kalman filters models the evolution of the errors of the inertial measurement unit 12 and delivers the a posteriori estimate of these errors which is used to correct the positioning point and speed of inertial measurement unit 12.
• the correction 28 of the errors by means of their estimation made by the set K of Kalman filters is then carried out at the input of the virtual platform 14 according to a so-called “closed loop” architecture as illustrated by Figure 1 making it possible to keep navigation errors low and therefore remain in the linear domain of the set K of Kalman filters.
• the virtual platform 14 uses such a correction 28 to develop the optimal estimate 30 of the position and speed of the vehicle.
• Hybridization is called “loose” (or hybridization in geographic axes) when the GNSS satellite positioning measurement receiver 16 provides the position and speed of the vehicle resolved by the GNSS receiver.
• the hybridization is said to be “tight” when the receiver 16 for positioning measurements by GNSS satellites provides the information extracted upstream by the GNSS receiver which is the pseudo-distances and the pseudo-velocities (quantities directly resulting from the measurement of the time of propagation and the Doppler effect of the signals emitted by the satellites towards the receiver).
• the set K of Kalman filters according to the present invention has a particular architecture illustrated by Figure 2.
• the assembly K firstly comprises a main closed-loop Kalman filter 32 configured to implement a hybridization of the satellite positioning data provided by said receiver and the non-satellite positioning data provided at least by said inertial measurement unit , in other words a hybridization of position measurements, received as input, and obtained respectively from said positioning measurements 24 by GNSS satellites, and measurements 34 provided both by said inertial measurement unit 12 and by said optional receiver 18 of additional measurements, in order to calculate corrections 36 of navigation data.
• a main closed-loop Kalman filter 32 configured to implement a hybridization of the satellite positioning data provided by said receiver and the non-satellite positioning data provided at least by said inertial measurement unit , in other words a hybridization of position measurements, received as input, and obtained respectively from said positioning measurements 24 by GNSS satellites, and measurements 34 provided both by said inertial measurement unit 12 and by said optional receiver 18 of additional measurements, in order to calculate corrections 36 of navigation data.
• the assembly K further comprises, according to the present invention, a bank 38 of N secondary Kalman filters SF 1 , SF2, ...SF i , SF i+ i, ...SF N , operating at the deviations (ie the correction established by the main filter being applied, as detailed below, to the propagation phase of each secondary Kalman filter) with N a predetermined integer such that N > 1, or preferably N>1, each secondary Kalman filter of index i , with 1 ⁇ i ⁇ N, being able to reconfigure itself (ie to copy the state vector and the covariance matrix of the main Kalman filter 32), according to arrow 40 on the main Kalman filter at a time (j - 1)T from the start of vehicle navigation, then periodically over a period NxT, with T a predetermined duration.
• each secondary Kalman filter SF 1 , SF 2 , ... SFi, SF i + i, ... SF N is configured to calculate corrections 42 of navigation data, only from the non-satellite positioning data provided at least by said inertial measurement unit, in particular here by hybridization of position measurements, received as input, and obtained only from the measurements 34 supplied by said inertial measurement unit 12 and supplied by said optional receiver 18 of complementary measurements, and does not accept as input, unlike the main Kalman filter 32, GNSS satellite positioning measurements 24.
• each secondary Kalman filter SF 1 , SF 2 , ...SFi, SF i+ i, ... SF N is configured to calculate corrections 42 of navigation data, only from the non-satellite positioning data provided by said inertial measurement unit, dispensing with the non-satellite data provided by the optional receiver 18.
• the N secondary Kalman filters SF 1 , SF 2 , ... SFi, S +1, ... SF N are identical and independent, the period NxT corresponding to a period of verification of the integrity of said 24 positioning measurements by GNSS satellites.
• the device 10 is also configured to check, at each time n + 1, the integrity of said positioning measurements by GNSS satellites by comparing, to a threshold predetermined, the difference between the state 44 of each secondary filter SF 1 , SF 2 , ... SFi, SF + 1, ... SFN and the state 46 of the main Kalman filter 32.
• the element 48 of Figure 2 determines such a difference and compares it to a predetermined threshold 50.
• the device 10 is configured to raise, according to arrow 52 in Figure 2, an alarm capable of signaling a vulnerability of said positioning measurements by GNSS satellites at said instant n + 1.
• the device 10 is also configured, by means of a calculation tool not shown in Figure 2, to determine said predetermined threshold 50 as a function of a probability of false alarm, as detailed below in relation with figure 4.
• the main Kalman filter 32 is also configured to reconfigure itself, according to arrow 54, on a predetermined secondary Kalman filter SF P of index p with 1 ⁇ p ⁇ N.
• reconfigure we mean that the main Kalman filter 32 is capable of copying the state vector and the covariance matrix of the secondary Kalman filter SF P.
• said predetermined secondary Kalman filter SF P of index p on which the main Kalman filter 32 is capable of being reconfigured, according to arrow 54, in the event of alarm 52 being raised is the secondary Kalman filter among said N secondary Kalman filters whose reconfiguration 40 on the main Kalman filter 32 is temporally furthest from the instant n + 1 of alarm raising.
• said main Kalman filter 32 is configured to no longer use said GNSS satellite positioning measurements 24 as input from the moment when the main Kalman filter 32 initiates its reconfiguration.
• the GNSS satellite positioning measurements 24 (whose vulnerability is detected) are no longer used, for example by sending a command to deselect these measurements by input of the set K of Kalman filters.
• the device 10 is also configured to determine a protection radius 58 with respect to a vulnerability of said positioning measurements by GNSS satellites, said protection radius guaranteeing that the value of the distance between the hybrid position 30 provided from said main Kalman filter 32 and the true position of said vehicle is less than the value of said protection radius 58, said protection radius 58 depending on the number N of secondary Kalman filters.
• the protection radius generally corresponds to a maximum position error for a given probability of error occurrence, i.e. the probability that the position error exceeds the announced protection radius without an alarm is sent to a navigation system, is less than this given probability value.
• the calculation is based on two types of error which are on the one hand normal measurement errors and on the other hand errors caused by an operating anomaly of the constellation of satellites, for example a satellite failure.
• the value of the protection radius of a positioning system is a key value specified by purchasers wishing to acquire a positioning system.
• the evaluation of the value of the protection radius generally results from probability calculations using the statistical precision characteristics of GNSS measurements and the behavior of inertial sensors. These calculations are explained formally and allow simulations for all GNSS constellation cases, for all possible positions of the positioning system on the terrestrial globe and for all possible trajectories followed by the tracking system. positioning. The results of these simulations make it possible to provide the principal with protection radius characteristics guaranteed by the proposed positioning system. Most often these characteristics are expressed in the form of a value of the protection radius for 100% availability or an unavailability duration for a required value of the protection radius.
• the device 10 is also configured to provide, at output, in parallel, navigation solutions 60 and 62 respectively associated with said main Kalman filter, and said bank SF of N secondary Kalman filters.
• the device 10 allows parallel navigation by distinct Kalman filters, namely via the navigation solutions 62 associated with the N secondary Kalman filters SF 1 , SF 2 , ... SF i , SF i + i, ... SF N and via the navigation solutions 60 respectively associated with the main Kalman filter 32.
• Such an architecture thus makes it possible to provide secondary navigation solutions, in terms of position, speed, attitude, in parallel with the solution provided by the main filter, such secondary navigation solutions being able to be useful for certain types of navigation, particularly underwater.
• the device 10 is capable of applying the Cor SF correction of each secondary Kalman filter (ie sub-filter) SF 1 , SF 2 ,. .. SFi, SF i+i , ... SF N in the main position state 1 being successive temporal instants) to obtain the position state associated with the SF subfilter: and the same for the Lat SF latitude, the longitude Lon SF , and altitude Alt SF , such that:
• the navigation and positioning device 10 comprises a processing unit formed for example of a memory and a processor associated with the memory, and the device 10 is at least partly made in the form of software, or a software brick, executable by the processor, in particular the set K of Kalman filters, the virtual platform 14 for calculation and location, the element 48 of Figure 2 configured to determine a difference between the state of each secondary filter and the state of the main Kalman filter, and compare this difference to a predetermined threshold 50, and optionally the calculation tool configured to determine said threshold 50.
• the memory of the device 10 of navigation and positioning is then able to store such software or software bricks, and the processor is then able to execute them.
• the set K of Kalman filters, the virtual calculation and location platform 14, the element 48 of FIG. 2 configured to determine a difference between the state of each secondary filter and the state of the main Kalman filter, and compare this difference to a predetermined threshold 50, and optionally the calculation tool configured to determine said threshold 50 are each produced in the form of a programmable logic component, such as an FPGA (from the English Field Programmable Gate Array), or in the form of a dedicated integrated circuit, such as an ASIC (Application Specific integrated Circuit).
• a programmable logic component such as an FPGA (from the English Field Programmable Gate Array)
• ASIC Application Specific integrated Circuit
• the computer-readable medium is, for example, a medium capable of storing electronic instructions and of being coupled to a bus of a computer system.
• the readable medium is an optical disk, a magneto-optical disk, a ROM memory, a RAM memory, any type of non-volatile memory (for example EPROM, EEPROM, FLASH, NVRAM), a magnetic card or an optical card.
• a computer program comprising software instructions is then stored on the readable medium.
• Figure 3 illustrates the principle of the closed loop applied to the main Kalman filter 32, with the position state X of the main Kalman filter 32, and P its covariance matrix.
• a module 64 for propagating the main Kalman filter 32 is configured to propagate the state using the navigation equations, and a registration module 66 makes it possible to estimate the state using the GNSS measurements provided by said receiver 16 of positioning measurements by GNSS satellites and measurements from the optional receiver 18 of complementary measurements provided by at least one piece of equipment distinct from said receiver 16 for positioning measurements by GNSS satellites and distinct from said inertial measurement unit 12.
• the propagation and registration equations in closed loop are for the adjustment implemented by module 66: and for the propagation implemented by module 64: with F the propagation matrix, Q the model noise matrix, R the covariance matrix of the measurement noise, H the observation matrix, K the Kalman gain and Z the observation vector obtained from the receivers 16 and 18 , obtain the position state 1.
• each secondary Kalman filter ie sub-filter
• SF 1 , SF 2 , ... SFi, SF i+i , ... SF N each sub-filter SF 1 , SF 2 , . .. SFi, SF i+i , ... SF N using the observation matrix H, the measurement noise R and the measurements Z of the observations from the receiver 18 of complementary measurements provided by at least one piece of equipment distinct from said receiver 16 of positioning measurements by GNSS satellites and distinct from said inertial measurement unit 12, a set K of Kalman filters, but in no case the GNSS measurements coming from the receiver 16 of positioning measurements by GNSS satellites.
• the propagation and registration equations are therefore for the registration implemented within each secondary Kalman filter operating on the differences (ie the correction established by the main filter being applied, as detailed below, to the propagation phase of each secondary Kalman filter): and for propagation: with Cor n the correction from the main Kalman filter 32, Z SF the observation vector which is a subset of Z of the main Kalman filter 32 containing only the observations obtained from the receiver 18, and not from the receiver 16 of GNSS satellite positioning measurements, H SF the observation matrix which contains the lines of H of the main Kalman filter 32 linked to the observations of the secondary filter considered in turn (ie in other words H SF contains zeros for the part associated with the GNSS satellite positioning measurements) K SF is the gain of the Kalman filter for the secondary sub-filter considered, P SF is the covariance matrix of the Kalman filter for the secondary sub-filter considered.
• the navigation and positioning method 70 implemented by said navigation and positioning device 10 comprises the steps described below implemented in parallel or successively one after the other or vice versa.
• the navigation and positioning device 10 implements a localization of said vehicle using the corrections provided respectively by the main Kalman filter and by the bank of N Kalman filters secondary.
• such a location is suitable for allowing parallel navigation by distinct Kalman filters, namely via the navigation solutions 60 associated with the N secondary Kalman filters SF 1 , SF 2 , ... SFi, SF i+ i, ... SF N and via the navigation solutions 62 respectively associated with the main Kalman filter 32.
• step 74 of verifying the integrity of said positioning measurements by GNSS satellites is implemented by the navigation device 10 and positioning according to the present invention.
• said verification 74 notably comprises a sub-step 76 of determining the state of each filter secondary and the state of the main Kalman filter, between two successive time instants n and n + 1, and the difference E between the state of each secondary filter and the state of the main Kalman filter.
• said verification step 74 also includes a sub-step 78 for determining a threshold S suitable for being compared to the difference E between the state of each secondary filter and the state of the main Kalman filter.
• said threshold S is directly provided and determined outside of said navigation and positioning device 10.
• the navigation and positioning device 10 implements the comparison, at each instant n + 1, of the difference E, between the state of each secondary filter SF 1 , SF2, ... SFi, SF i +1, ... SFN and the state of the main Kalman filter 32, said threshold S.
• a step 82 the raising of an alarm A is triggered or not.
• the navigation and positioning device 10 puts then implements the determination R P of a protection radius with respect to a vulnerability of said positioning measurements by GNSS satellites, said protection radius guaranteeing that the value of the distance between the hybrid position provided from said main filter of Kalman 32 and the true position of said vehicle is less than the value of said protection radius, said protection radius depending on the number of secondary Kalman filters.
• the difference between the state of each secondary filter and the state of the main Kalman filter is determined because if a GNSS measurement is erroneous, it will corrupt the main INS/GNSS solution from the main Kalman filter 32, but not certain solutions from the sub -solutions provided by the N secondary filters capable of carrying out a time-shifted adjustment according to the present invention.
• sub-step 80 we seek to control the deviation over time for each sub-filter by comparing it, via a predetermined threshold, to the covariance of the deviation of the states.
• observation matrices of each sub-filter H SF and measurement noise R SF are sub-matrices of the observation matrices H and measurement noise R of the main Kalman filter 32 where the lines (respectively columns) linked to the GNSS measurements have been set to zero (the rest being identical between sub-filter and main filter), and that the propagation matrices F and model noise Q are identical between sub-filter and main filter, then it is demonstrable by recurrence by those skilled in the art that the expectation is equal to the difference in matrix of covariance P SF - P, which by expanding amounts to an expectation of equal to P the covariance matrix of the main Kalman filter 32.
• the navigation and positioning device 10 itself determines during step 78, said threshold used to compare the difference X n+1/n to the covariance of the difference of the states.
• branch 88 when a an anomaly in the GNSS measurements is detected and an alarm is raised.
• test 82 is carried out, depending on the application, on certain controlled states such as position, speed, attitudes, sensor fault states, etc., and this for the N sub-filters of the architecture.
• the navigation and positioning device 10 implements the determination of a protection radius with respect to a vulnerability of said GNSS satellite positioning measurements, said protection radius guaranteeing that the value of the distance between the hybrid position provided from said main Kalman filter 32 and the true position of said vehicle is less than the value of said protection radius, said protection radius depending on the number of secondary Kalman filters.
• the navigation and positioning device 10 introduces a probability of non-detection P nd .
• the protection radius R p is then defined as follows: with the sum over the N secondary Kalman filters, P iat the diagonal of the covariance matrix corresponding to the latitude state
• the determination of the protection radius amounts to finding the coefficient such that: so that it is then possible to guarantee that if the deviation is lower than at the time of the GNSS failure, then with a probability of non-detection of the failure of P nd and then:
• the protection radius preferably corresponds to the maximum value of the protection radii of each of the sub-filters such that: and this as long as the fault detection did not raise an alarm.
• the protection ray can propagate with the error value in the following way: so that it is then preferable to stop the reconfiguration mechanism according to arrow 40 in Figure 2 of each secondary Kalman filter SF 1 , SF 2 , ... SF i , SF i + i, ... SF N on the main Kalman filter 32.
• the previous example of determining the protection radius developed from the latitude state can be generalized to other states such as other position states (longitude, altitude) or even to states of speed or attitude and heading.
• the architecture of the set K of Kalman filters proposed has the ability to propose a navigation solution not corrupted by the GNSS failure. Indeed, once the alarm is raised, just like the secondary Kalman filters SF 1 , SF 2 , ... SFi, SF i + i, ...
• SF N were, prior to this alarm raising, reconfigured periodically and offset from the main Kalman filter 32, it is possible to reconfigure the main Kalman filter 32 on an uncorrupted secondary Kalman filter, the choice of which is specific to depending on the desired application, a preferential and conservative choice being to take the secondary Kalman filter which was reset the oldest over the main Kalman filter 32 assuming that the GNSS failure cannot be undetected for more than (N - l). T hours.
• the architecture of the navigation and positioning device 10 according to the embodiment of Figures 1 and 2 was tested by considering the example of application considering the trajectory of a vehicle corresponding to a surface building at 10 m/s ( 19.4 kts) for 4 days, a GNSS longitude drift command after 69.4 hours (250,000 seconds) of navigation, the drift taking the value 0.25 m/s (0.46 kts), the use, within this vehicle, of a high performance INS inertial unit having a typical gyrometric drift of 0.01 7h, a multi-filter architecture of the set K as described previously and consisting of twelve secondary Kalman filters (sub-filters) reset every 24h with a time difference of 2 hours between them, a probability of false alarm P fa taken at 10 -5 /hour and a probability of non-detection taken at 0.1% to calculate the detection threshold S and the protection radius.
• such an architecture of the navigation and positioning device 10 detects a GNSS longitude drift after 3 hours 30 minutes, i.e. a position drift of 1.6 NM, and the determined protection radius converges towards 6.2NM and is much greater than the difference between hybrid position and true position at the time of detection.
• the hybrid position provided by the main Kalman filter 32 and the GNSS position provided for example by a GPS have less than 10 meters of error compared to the true position, while the positions provided by the twelve secondary Kalman filters are within a radius of 0.5 NM around the true position in agreement with the inertial performance of the chosen INS inertial unit.
• the positions are all contained within the protection radius determined according to the present invention.
• the GPS position and hybrid position 62 provided by the primary Kalman filter drifted by approximately 1.6 NM in longitude while the positions 60 provided by the secondary Kalman filters SF 1 , SF2, ... SF i , SE+1, ... SF N generally remained within a radius of 0.5 NM around the true position. Only a secondary Kalman filter was partially trained because it was reset to the primary Kalman filter after the drift on GNSS longitude appeared. Thus, the protection radius determined according to the present invention covers the hybrid position well.
• the present invention thus proposes an architecture of a set of Kalman filters with time-shifted registration making it possible to maintain the integrity of the positioning independently of the vulnerability of the GNSS measurements by comparison - on the one hand of the primary position resulting from the classic INS/GNSS hybridization carried out via a main Kalman filter 32 using all available measurements as input: GNSS, external position, zero displacement adjustment when the vehicle is stationary, electromagnetic log measurement and a dynamic model of the vehicle, Doppler log or DVL, depth measurement, registration by radar, by imaging, registration by opportunity signals, etc.
• Such control is not only carried out on a single satellite at a time, which avoids limiting the application domain.
• the navigation and positioning device 10 is, according to an optional aspect, capable of permanently offering a set of navigation solutions including some have not used GNSS measurements for some time, typically several hours to several days.
• the navigation and positioning device 10 is also capable of providing a protection radius against a vulnerability of GNSS measurements and capable of triggering a reconfiguration of the main Kalman filter on a solution of a filter secondary Kalman if a vulnerability in GNSS measurements is detected.
• a healthy fallback solution is always available in the event of detection of a problem with the GNSS signals.
• the present invention makes it possible to maintain the integrity of the location, to warn when the GNSS signals are not reliable, to reconfigure on a solution not tainted by the vulnerability of the GNSS measurements, in other words, to reconfigure the primary Kalman filter on a “healthy” secondary Kalman filter, and to have available a panel of navigation solutions deduced from secondary Kalman filters having navigated without GNSS measurement for a variable time.

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• Engineering & Computer Science (AREA)
• Radar, Positioning & Navigation (AREA)
• Remote Sensing (AREA)
• Computer Networks & Wireless Communication (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Computer Security & Cryptography (AREA)
• Navigation (AREA)
• Position Fixing By Use Of Radio Waves (AREA)

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• 2022
  • 2022-07-04 FR FR2206754A patent/FR3137461B1/fr active Active
• 2023
  • 2023-07-03 EP EP23735798.3A patent/EP4551973A1/de active Pending
  • 2023-07-03 US US18/879,239 patent/US20250389853A1/en active Pending
  • 2023-07-03 WO PCT/EP2023/068219 patent/WO2024008640A1/fr not_active Ceased

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