Device and method for maintaining reliability of the positioning of a vehicle irrespective of the vulnerability of satellite data

Abstract

Provided is a device for maintaining reliability of the positioning of a vehicle irrespective of the vulnerability of satellite data, comprising: - an inertial measurement unit, - a satellite data receiver, - a main Kalman filter (32) configured to calculate navigation data corrections by continuous hybridization of satellite data and non-satellite data, and additionally a bank of N Kalman sub-filters (SF1, SF2, ... SFi, SFi+1, ... SFN) in parallel, each Kalman sub-filter being configured to: - calculate navigation data corrections by intermittent hybridization, according to a predetermined recalibration frequency FRi, and; - beyond the implementation of said intermittent hybridization, calculate navigation data corrections based solely on the non-satellite data.

Description

[0001] TITLE :

[0002] DEVICE AND METHOD FOR MAINTAINING THE INTEGRITY OF VEHICLE POSITIONING INDEPENDENTLY OF SATELLITE DATA VULNERABILITY

[0003] The present invention relates to a device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data, suitable for being on board a vehicle suitable for moving between two distinct geographical positions, the device comprising at least: an inertial measurement unit suitable for providing navigation measurements, a satellite data receiver, a main closed-loop Kalman filter configured to calculate corrections of navigation data by permanent hybridization of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit.

[0004] The invention also relates to a vehicle comprising such a device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data.

[0005] The invention also relates to a method for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data implemented by such a device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data.

[0006] The invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a method of maintaining the integrity of the positioning of a vehicle regardless of the vulnerability of satellite data.

[0007] 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.

[0008] Currently, it is possible to determine the geographical position of such a vehicle using a GNSS (Global Navigation Satellite System) satellite navigation and positioning system. To do this, the vehicle generally carries a satellite navigation and positioning system receiver configured to determine, in particular by trilateration, a position (i.e. a geolocation position or a geolocation solution) of the aircraft using estimates of distances to the visible satellites of one or more satellite constellations of the satellite navigation and positioning system. Examples of satellite navigation systems are the American GPS system, the European GALILEO system, the Russian GLONASS system, or the Chinese BEIDOU system, etc.

[0009] In addition, vehicles also have other navigation systems such as one or more inertial measurement units (INS), baro-altimeters, anemometers, etc. An inertial measurement unit consists of a set of inertial sensors (accelerometers, gyrometers) associated with processing electronics, and provides low-noise and accurate information in the short term, but its performance deteriorates in the long term, in particular due to the sensors that compose it. Such vehicles then implement, for predetermined applications, a hybridization technique of position measurements known as INS / GNSS hybridization, capable of providing vehicle location with an accuracy of the same order of magnitude as GNSS location and very precise attitude and heading angles, while ensuring continuity of service during GNSS unavailability.

[0010] However, INS / GNSS hybridization implemented using current techniques is not optimal for protecting against GNSS errors in the event of satellite failure, GNSS software or hardware faults, or intentional or unintentional interference, nor for providing accurate positioning when such errors occur.

[0011] The aim of the invention is then to propose a navigation and positioning device which allows at least the integrity of the positioning to be maintained independently of the vulnerability of the GNSS measurements.

[0012] To this end, the invention relates to a device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data, suitable for being on board a vehicle suitable for moving between two distinct geographical positions, the device comprising at least:

[0013] - an inertial measurement unit capable of providing navigation measurements,

[0014] - a satellite positioning data receiver,

[0015] - a main closed-loop Kalman filter configured to calculate navigation data corrections by permanent hybridization of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit, the device further comprising a bank of N Kalman sub-filters in parallel with N a predetermined integer such that N > 1, each Kalman sub-filter being configured to:

[0016] - calculate navigation data corrections by point hybridization, according to a recalibration frequency F Riincluded in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another;

[0017] - apart from the implementation of said point hybridization, calculating navigation data corrections solely from non-satellite positioning data provided at least by said inertial measurement unit.

[0018] Thus, the navigation and positioning device according to the invention has a particular architecture where each Kalman sub-filter is capable of compensating for its drift, relating to the calculation of navigation data corrections solely from non-satellite positioning data provided at least by said inertial measurement unit, by punctually resetting itself to a solution using satellite data, according to a resetting frequency distinct from one sub-filter to another.

[0019] In other words, the particular architecture of the device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention makes it possible to carry out a recalibration offset in time from one sub-filter to another, the recalibration frequency being distinct from one sub-filter to another.

[0020] Apart from this one-time recalibration, none of the Kalman sub-filters use GNSS measurements as input to calculate their navigation data corrections, which makes each of them invulnerable to a possible GNSS error.

[0021] Furthermore, the long-term degradation of the performance of the Kalman sub-filters is limited. Indeed, this degradation is classically due to a drift of the position measurements, received as input, and obtained only from the non-satellite measurements provided at least by said inertial measurement unit, and, according to the present invention, is limited by means of said pointwise recalibration by pointwise hybridization with the satellite data, which amounts to punctually reproducing the processing carried out by the main Kalman filter. In other words, the pointwise hybridization is “worth” reconfiguration on the main Kalman filter.

[0022] In other words, the recalibration frequency allows each Kalman sub-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 the said inertial measurement unit, while avoiding the calculation drift associated with the medium / long term.

[0023] According to other advantageous aspects of the invention, the device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data comprises one or more of the following characteristics, taken individually or in all technically possible combinations:

[0024] - the N Kalman sub-filters are identical and independent, the period 1 / F Ri corresponding to a period of verification of the integrity of said GNSS satellite positioning measurements;

[0025] - the device is also configured to:

[0026] - check the integrity of said GNSS satellite positioning measurements by comparing, with a predetermined threshold, the difference between the state of each sub-filter, outside the implementation of said point hybridization, and the state of the main Kalman filter, and

[0027] - in the event of a deviation greater than said predetermined threshold, raise an alarm to signal a vulnerability of said GNSS satellite positioning measurements;

[0028] - the device is also configured to determine said predetermined threshold based on a probability of false alarm;

[0029] - in case of alarm lifting, the main Kalman filter is also configured to reconfigure itself on a predetermined Kalman sub-filter of index p with 1 ≤ p ≤ N.

[0030] - said predetermined Kalman sub-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 Kalman sub-filter among said N Kalman sub-filters whose implementation of said point hybridization is temporally the furthest from the alarm being raised;

[0031] - 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;

[0032] - in the event of an alarm being raised, each Kalman sub-filter of index i ≠ p is also configured to reconfigure itself on said predetermined Kalman sub-filter of index p;

[0033] - the device is also configured to determine a protection radius with respect to a vulnerability of said GNSS satellite positioning measurements, said protection radius ensuring that the value of the distance between the hybrid position 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 N of Kalman sub-filters; - the device is also configured to provide, at output, in parallel, navigation solutions respectively associated with said bank of N Kalman sub-filters, and with said main Kalman filter.

[0034] The invention also relates to a vehicle comprising such a device for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data.

[0035] The invention also relates to a method for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data and comprising the following steps implemented in parallel or successively one after the other or vice versa:

[0036] - localization of said vehicle using the corrections provided respectively by the main Kalman filter and by the bank of N Kalman sub-filters,

[0037] - verification of the integrity of said GNSS satellite positioning measurements, said verification comprising:

[0038] - the determination of the state of each Kalman sub-filter, outside the implementation of said point hybridization (i.e. if one of the sub-filters is in recalibration by point hybridization its state is not determined because it will then be identical to that of the main Kalman filter), and the state of the main Kalman filter,

[0039] - the determination of a threshold suitable for comparison with the difference between the state of each Kalman sub-filter and the state of the main Kalman filter,

[0040] - the comparison of the difference between the state of each sub-filter, outside the implementation of said point hybridization, with the state of the main Kalman filter at said threshold,

[0041] - in the presence of a deviation greater than said predetermined threshold:

[0042] - the raising of an alarm to signal a vulnerability of said GNSS satellite positioning measurements,

[0043] - the reconfiguration of the main Kalman filter on a predetermined Kalman sub-filter of index p with 1 ≤ p ≤ N,

[0044] - deselection of the main Kalman filter input dedicated to GNSS satellite positioning measurements from the moment the main Kalman filter initiates its reconfiguration,

[0045] - the reconfiguration of each Kalman sub-filter of index i ≠ p on said predetermined Kalman sub-filter of index p,

[0046] - in the absence of a deviation greater than said predetermined threshold, 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 and the true position of said vehicle is less than the value of said protection radius, said protection radius depending on the number of Kalman sub-filters.

[0047] According to a particular aspect of said method, said localization step comprises providing as output, in parallel, the navigation solutions respectively associated with said bank of N Kalman sub-filters, and with said main Kalman filter.

[0048] The invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a method for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data as defined above.

[0049] These characteristics and advantages of the invention will appear more clearly on reading the description which follows, given solely by way of non-limiting example, and made with reference to the appended drawings, in which:

[0050] - [Fig 1] Figure 1 is a diagram illustrating a navigation and positioning device capable of implementing INS / GNSS hybridization, and optionally with additional measurements provided by equipment separate from a satellite data receiver and separate from said inertial measurement unit;

[0051] - [Fig 2] Figure 2 is a diagram illustrating the architecture of the Kalman filter bank according to the present invention;

[0052] - [Fig 3] Figure 3 illustrates the closed loop principle;

[0053] - [Fig 4] Figure 4 is a flowchart of a method for maintaining the integrity of a vehicle's positioning regardless of the vulnerability of satellite data.

[0054] Figure 1 is an overall representation of a device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention, capable of implementing an INS / GNSS hybridization, and optionally with complementary measurements provided by equipment separate from a satellite data receiver and separate 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 satellite data receiver 16 (i.e. a receiver for positioning measurements by GNSS satellites), and optionally a receiver 18 of complementary measurements provided by at least one equipment separate from said satellite data receiver 16 and separate 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 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data is embedded.

[0055] The virtual computing 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.

[0056] The satellite data receiver 16 (i.e. GNSS receiver) is capable of providing, according to arrow 24, information on the position and speed of the vehicle by triangulation from the signals transmitted by satellites moving in view visible to the vehicle. The information provided may be temporarily unavailable because the receiver must have a direct view of a minimum of four satellites of the positioning system to be able to fix it. It is also of variable precision, depending on the geometry of the constellation at the base of the triangulation, and noisy because it relies on the reception of very low-level signals from distant satellites with low transmission power. But it does not suffer from long-term drift, the positions of the satellites moving in 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. In addition, satellite data can be erroneous due to satellite failures. This incomplete data must then be identified so as not to distort the position from the GNSS receiver.

[0057] The optional receiver 18 of complementary measurements 26 provided by at least one piece of equipment separate from said satellite data receiver 16 and separate from said inertial measurement unit 12 provides, for example, zero displacement recalibration when the vehicle is stationary, an Electromagnetic Log measurement and a dynamic model of the vehicle, a Doppler log or a measurement of speed in the water when the equipment is a DVL (Doppler Velocity Log), a depth measurement, recalibration by radar, by imaging, by opportunity signals, etc.

[0058] 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 of 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.

[0059] 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 the relationship of dependence 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 a recalibration of the states of the filter (a posteriori estimation). In a Kalman filter, the effective measurement or "measurement vector" makes it possible to carry out 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 state vector of the system by 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.

[0060] 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 and velocity point of the inertial measurement unit 12.

[0061] 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 to 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.

[0062] The hybridization is called "loose" (or hybridization in geographic axes) when the satellite data receiver 16 provides the position and speed of the vehicle resolved by the GNSS receiver 16.

[0063] The hybridization is said to be "tight" when the satellite data receiver 16 provides the information extracted upstream by the GNSS receiver, which are the pseudo-distances and the pseudo-speeds (quantities directly derived from the measurement of the propagation time and the Doppler effect of the signals emitted by the satellites in the direction of the receiver). With such a device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data by closed-loop INS / GNSS hybridization where the point resolved by the GNSS receiver 16 is used to recalibrate the information coming from the inertial measurement unit 12, it is necessary to monitor the defects affecting the information provided by the satellites because the receiver 16 which receives them will propagate these defects to the inertial measurement unit 12, causing poor recalibration of the latter.

[0064] To do this, the set K of Kalman filters according to the present invention has a particular architecture 100 illustrated by figure 2.

[0065] The set K firstly comprises a main closed-loop Kalman filter 32 configured to implement a permanent hybridization of the satellite positioning data provided by said receiver 16 and 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 GNSS satellite positioning measurements 24, and measurements 34 provided both by said inertial measurement unit 12 and by said optional receiver 18 of complementary measurements, in order to calculate corrections 36 of navigation data. By permanent hybridization, it is meant that the hybridization is constantly implemented outside the reconfiguration period of the main Kalman filter 32 as detailed below in the event of a detected lack of integrity of the satellite data.The set K further comprises, according to the present invention, a bank SF of N Kalman sub-filters SF1, SF2, ...SF. i , SF i+1 , ... SF N , in parallel with each other, and operating at the deviations (i.e. the correction established by the main filter being applied, as detailed below, to the propagation phase of each Kalman sub-filter) with N a predetermined integer such that N ≥ 1, or even preferentially N>1, each Kalman sub-filter being configured to:

[0066] - calculate navigation data corrections by point hybridization, according to a recalibration frequency F R included in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another;

[0067] - apart from the implementation of said punctual hybridization, calculating navigation data corrections solely from non-satellite positioning data provided at least by said inertial measurement unit. The recalibration is, for example, suitable for being carried out every minute (i.e. a recalibration frequency F R equal to once per minute, or every day (i.e. once per twenty-four hours), or every two days (i.e. once per forty-eight hours), so that we consider, for example, that the resetting frequency FR is included in the range defined by the maximum limit "once per minute" and the minimum limit "once per forty-eight hours" with the possibility of being equal to one of these limits.

[0068] For example, the first Kalman SF subfilter 1 (i=1) implements a point hybridization, according to a registration frequency F R1, for example, non-limiting of the order of one minute, of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit. In other words, the first Kalman sub-filter SF1 uses the satellite data once per minute and does not use them otherwise outside of this single time per minute, which amounts to the fact that once per minute, SF1 operates in an identical manner to the main Kalman filter 32.

[0069] The second Kalman SF subfilter 2(i=2) implements a point hybridization, according to a registration frequency F R2, for example, non-limiting of the order of half an hour (ie 30 minutes), of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit. In other words, the second Kalman sub-filter SF2 uses the satellite data once every half hour (ie every 30 minutes) and does not use them otherwise outside of this single time per half hour, which amounts to the fact that once per half hour, SF2 operates in an identical manner to the main Kalman filter 32.

[0070] The third Kalman SF subfilter 3(i=3) implements a point hybridization, according to a registration frequency F R3, for example, not limited to the order of time, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit. In other words, the second Kalman sub-filter SF3 uses the satellite data once per hour and does not use them otherwise apart from this single time per hour, which amounts to the fact that once per hour, SF3 operates in an identical manner to the main Kalman filter 32, and so on for the following sub-filters SF 4(i=4) to SF N the N ième sub-filter which, for example, implements point hybridization, according to a recalibration frequency F R3 , for example not limited to the order of the day (i.e. every twenty-four hours).

[0071] Note that the recalibration duration as such is notably less than the period 1 / F Ri. More precisely, the recalibration time as such generally depends on the inertial measurement unit (also called inertial measurement unit), and is a fraction of the inverse of the recalibration frequency 1 / F Ri , for example twenty seconds if the resetting frequency is one resetting every two hundred seconds. Note that this resetting duration can be fixed according to a first optional variant, for example twenty seconds for all the sub-filters or variable, according to a second optional variant of the present invention, the resetting frequency F R , and / or the resetting duration then being distinct from one sub-filter to another and / or associated with a triggering time (i.e. start time of the activity of the sub-filter considered) distinct from one sub-filter to another.

[0072] For example, if we consider the N ièmesub-filter which implements once a day (i.e. every twenty-four hours) a recalibration on a solution using satellite data, the duration of recalibration as such is of the order of a hundred seconds, whereas if we consider the 1 er SF sub-filter 1(i=1) which implements a point hybridization, according to a registration frequency F R1 , for example non-limiting of the order of one minute, the resetting time as such is less and for example of the order of forty seconds.

[0073] Additionally, each Kalman sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N, apart from the implementation of said point hybridization, is configured to calculate corrections 42 of navigation data, solely 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 solely from the measurements 34 provided by said inertial measurement unit 12 and provided by said optional receiver 18 of complementary measurements, and does not accept as input, to carry out this calculation apart from the implementation of said point hybridization, unlike the main Kalman filter 32, the positioning measurements 24 by GNSS satellites.

[0074] According to a more basic embodiment, not shown, each Kalman sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N, apart from the implementation of said point hybridization, is configured to calculate corrections 42 of navigation data, solely from the non-satellite positioning data provided by said inertial measurement unit, while ignoring the non-satellite data provided by the optional receiver 18.

[0075] According to an optional variant, the N Kalman sub-filters SF1, SF2, ...SF i , SF i+1 , . . . SF N are identical and independent, the period 1 / F Ri , distinct from one sub-filter to another, corresponding to a period of verification of the integrity of said GNSS satellite positioning measurements 24, by means of each sub-filter separately.

[0076] According to a particular variant of the present invention, the device 10, part of which is shown in FIG. 2, is also configured to control the integrity of said GNSS satellite positioning measurements by comparing, with a predetermined threshold, the difference between the state 44 of each sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N , apart from the implementation of said point hybridization, and the state 46 of the main Kalman filter 32. The element 48 of figure 2 determines such a deviation and compares it to a predetermined threshold 50.

[0077] In the event of a deviation greater than said predetermined threshold 50, the device 10 is configured to raise, according to the arrow 52 of FIG. 2, an alarm capable of signaling a vulnerability of said GNSS satellite positioning measurements.

[0078] As an optional addition, the device 10 is also configured, by means of a calculation tool not shown in FIG. 2, to determine said predetermined threshold 50 as a function of a probability of false alarm, as detailed below in relation to FIG. 4.

[0079] As an optional addition, as illustrated by the embodiment represented by Figure 2, in the event of an alarm being raised illustrated by arrow 52, ​​the main Kalman filter 32 is also configured to reconfigure itself, according to arrow 54, on a Kalman sub-filter SF P predetermined index p with 1 ≤ p ≤ N. By "reconfigure", we mean that the main Kalman filter 32 is capable of copying the state vector and the covariance matrix of the Kalman subfilter SF P .

[0080] According to a complementary variant of this optional addition, said SF sub-filter Pof predetermined Kalman of index p on which the main Kalman filter 32 is capable of reconfiguring itself, according to arrow 54, in the event of an alarm being raised, is the Kalman sub-filter among said N Kalman sub-filters whose implementation of said point hybridization is temporally the furthest from the alarm raising time.

[0081] According to another complementary variant of this optional addition, said main Kalman filter 32 is configured to no longer use as input said GNSS satellite positioning measurements 24 from the moment when the main Kalman filter 32 initiates its reconfiguration. In other words, as soon as the reconfiguration of the main Kalman filter 32 is commanded, the GNSS satellite positioning measurements 24 (whose vulnerability is detected) are no longer used, for example by sending a command to deselect these measurements as input to the set K of Kalman filters. According to another complementary variant of this optional addition, in the event of an alarm 52 being raised, each Kalman sub-filter of index i ≠ p is also configured to reconfigure itself on said predetermined Kalman sub-filter of index p, which makes it possible to restore a set K with the main Kalman filter 32 and the sub-filters SF1, SF2, ... SF i , SF i+1, ... SF N completely healthy.

[0082] According to another optional complementary aspect, the device 10 is also configured to determine a protection radius 58 with respect to a vulnerability of said GNSS satellite positioning measurements, said protection radius ensuring 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 Kalman sub-filters.

[0083] Indeed, to quantify the integrity of a position measurement in applications such as naval or aeronautical applications, where integrity is critical, such a parameter of protection radius of the position measurement is generally used. The protection radius generally corresponds to a maximum position error for a given probability of error occurrence, that is to say that the probability that the position error exceeds the announced protection radius without an alarm being sent to a navigation system, is lower 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 satellite constellation, for example a satellite failure.The value of the protection radius of a positioning system is a key value specified by clients wishing to acquire a positioning system. The evaluation of the value of the protection radius generally results from probability calculations using the statistical characteristics of the precision 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 Earth and for all possible trajectories followed by the positioning system. The results of these simulations make it possible to provide the client 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 determination of the protection radius implemented according to the present invention using the particular architecture 100 of the aforementioned set K of Kalman filters is described below in more detail in relation to FIG. 4.

[0084] According to another optional complementary aspect, 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 with said bank 38 of N Kalman sub-filters, via the navigation solution determination modules 102 and 104 respectively.

[0085] In other words, the device 10 according to the present invention allows parallel navigation by distinct Kalman filters, namely via the navigation solutions 62 associated with the N Kalman sub-filters SF1, SF2, ... SF i , SF i+1 , ... SF N and via the navigation solutions 60 respectively associated with the main Kalman filter 32. Such an architecture 100 thus makes it possible to provide secondary navigation solutions (associated with each sub-filter), in terms of position, speed, attitude, in parallel with the solution provided by the main filter, such secondary navigation solutions being suitable for being useful for certain types of navigation, particularly underwater.

[0086] For example, for the position, at each cycle of the main Kalman filter 32, the device 10 according to the present invention is capable of applying the correction Cor SF of each Kalman sub-filter SF1, SF2, ... SF i , SFi+1 , ... SF N in the main position state X n+1 / n (ie associated with the main INS / GNSS solution delivered by the main Kalman filter 32, n and n + 1 being successive time instants) to obtain the position state associated with the SF sub-filter: and the same for the latitude Lat SF , there longitude Lon SF , and the altitude Alt SF , such as:

[0087] Lat SF = Lat INS / GNSS + Horn SF (Lat), Lon SF = Long INS / GNSS + Horn SF (Lon)

[0088] Alt SF = Alt INS / GNSS + Horn SF (Alt)

[0089] According to a variant not shown, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention 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 produced 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 localization, the element 48 of FIG. 2 configured to determine a difference between the state of each sub-filter, outside the implementation of said point hybridization, 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 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data is then capable of storing such software or software bricks, and the processor is then capable of executing them.

[0090] In a variant not shown, the set K of Kalman filters, the virtual platform 14 for calculation and localization, the element 48 of FIG. 2 configured to determine a difference between the state of each sub-filter and the state of the main Kalman filter, and to 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 (Field Programmable Gate Array), or in the form of a dedicated integrated circuit, such as an ASIC (Application Specific Integrated Circuit).

[0091] When a part of the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention is produced in the form of one or more software programs, that is to say in the form of a computer program, this part is furthermore capable of being recorded on a medium, not shown, readable by a computer. 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. By way of example, 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 even an optical card. A computer program comprising software instructions is then stored on the readable medium.

[0092] Figure 3 illustrates the closed-loop principle applied to the main Kalman filter 32, with the position state X of the main Kalman filter 32, and P its covariance matrix. A propagation module 64 of the main Kalman filter 32 is configured to propagate the state using the navigation equations, and a recalibration module 66 makes it possible to estimate the state using the GNSS measurements provided by said satellite data receiver 16 and the measurements of the optional receiver 18 of complementary measurements provided by at least one piece of equipment separate from said satellite data receiver 16 and separate from said inertial measurement unit 12. The closed-loop propagation and recalibration equations are for the recalibration implemented by the module 66: and for the propagation implemented by module 64: with F the propagation matrix, Q the model noise matrix, R the measurement noise covariance matrix, H the observation matrix, K the Kalman gain and Z the observation vector obtained from receivers 16 and 18,

[0093] X n+1 / n The propagated position state vector after propagation between the two successive time instants n and n + 1. The correction Cor n+1 is applied by a correction module 68 to the navigation data to obtain the X position state n+1 / n+1 and stored in memory M2, as well as the covariance matrix P n+1 / n in memory Mi, for a following iteration at time n + 1.

[0094] This principle also applies to each Kalman sub-filter SF1, SF2, ... SF i , SF i+1 , ...SF N , each sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF Nusing 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 separate from said satellite data receiver 16 and separate from said inertial measurement unit 12, a set K of Kalman filters, and, apart from the implementation of said point hybridization, without using the GNSS measurements from the satellite data receiver 16 (i.e. when the sub-filter considered does not implement point hybridization, this sub-filter does not use any of the GNSS measurements from the satellite data receiver 16).

[0095] More precisely, for each Kalman sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N , we use the classical Kalman filter equations by applying the Cor INS / GNSS correction of the main Kalman filter 32 at the time of propagation.

[0096] The propagation and recalibration equations are therefore implemented for the recalibration within each Kalman sub-filter operating at the deviations (i.e. the correction established by the main filter being applied, as detailed below, to the propagation phase of each Kalman sub-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 32 containing only the observations obtained from the receiver 18, and not from the satellite data receiver 16 when the sub-filter considered does not implement a point hybridization, H SF the observation matrix which contains the lines of H of the main Kalman filter 32 linked to the observations of the sub-filter considered in turn (i.e. in other words H SFcontains zeros for the part associated with GNSS satellite positioning measurements) K SF is the gain of the Kalman filter for the sub-filter considered, P SF is the covariance matrix of the Kalman filter for the sub-filter considered.

[0097] An example of operation of the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention is now described below in relation to FIG. 4.

[0098] More specifically, the method 70 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data implemented by said device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data comprises the steps described below implemented in parallel or successively one after the other or vice versa.

[0099] According to step 72, as indicated previously, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention implements a localization of said vehicle using the corrections provided respectively by the main Kalman filter and by the bank of N Kalman sub-filters.

[0100] According to an optional aspect, such a location is suitable for allowing parallel navigation by distinct Kalman filters, namely via the navigation solutions 60 associated with the N Kalman sub-filters SF1, SF2, ... SF i , SF i+1 , ... SF N and via the navigation solutions 62 respectively associated with the main Kalman filter 32.

[0101] In parallel with step 72, or successively to this step 72 or vice versa (i.e. before this step 72), a step 74 of verifying the integrity of said GNSS satellite positioning measurements is implemented by the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention. According to a particular embodiment illustrated by FIG. 2, said verification 74 notably comprises a sub-step 76 of determining:

[0102] - the state of each sub-filter, when the sub-filter considered does not implement a point hybridization, according to a recalibration frequency F Riincluded in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another, and

[0103] - the state of the main Kalman filter, between two successive time instants n and n + 1, and the gap E between the state of each sub-filter and the state of the main Kalman filter.

[0104] Optionally, said verification step 74 also comprises a sub-step 78 of determining a threshold S suitable for being compared to the difference E between the state of each sub-filter and the state of the main Kalman filter.

[0105] As an alternative, not shown, to sub-step 78 of determining a threshold S, said threshold S is directly provided and determined outside of said device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data.

[0106] Then, during step 80, the navigation and positioning device 10 according to the present invention implements the comparison with said threshold S, at each instant n + 1, of the difference E, between the state of the main Kalman filter 32 and the state of each sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N which is not undergoing point hybridization according to a registration frequency F Riincluded in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another.

[0107] In other words, if at time n+1, consider the SF sub-filter i is undergoing point hybridization (i.e. recalibration on a GNSS solution), this SF sub-filter i is ignored during said comparison.

[0108] During a step 82, the lifting of an alarm A is triggered or not.

[0109] More precisely, in the absence of a deviation greater than said predetermined threshold S, said absence being represented by the branch 84, no alarm is raised, and during a sub-step 86, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data then implements the determination R_P 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 Kalman sub-filters.

[0110] On the other hand, in the presence of a deviation greater than said predetermined threshold, said presence being represented by the branch 88, the raising of an alarm capable of signaling a vulnerability of said GNSS satellite positioning measurements at said instant n + 1 is triggered as well as a subsequent step 90 of reconfiguration of the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data.

[0111] Step 90 comprising a first sub-step 92 of reconfiguration Ri of the main Kalman filter 32 on a predetermined Kalman sub-filter of index p with 1 ≤ p ≤ N, a second sub-step 94 of reconfiguration R2 of each Kalman sub-filter of index i ≠ p on said predetermined Kalman sub-filter of index p, a third sub-step 96 of deselection GNSS_D of the input of the main Kalman filter dedicated to the positioning measurements by GNSS satellites from the moment when the main Kalman filter initiates its reconfiguration.

[0112] Below, steps of said method 70 according to the present invention are detailed in more detail.

[0113] In particular, during sub-step 76, the gap between the state of each sub-filter (when said sub-filter considered does not implement a point hybridization) 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 resulting from the main Kalman filter 32, but not certain solutions resulting from the sub-solutions provided by the N sub-filters capable of carrying out a time-shifted recalibration according to the present invention. Such a difference between the different solutions respectively associated with the different filters of the set K of Kalman filters will result in a gap between the position states of the sub-filter and the main filter X n+1 / n more or less important depending on the state studied, and inconsistent with the covariance of the deviation of the states, the X position states in question corresponding for example to heading states, speed position states, etc.

[0114] During sub-step 80, we seek to control over time for each sub-filter the deviation by comparing it, via a predetermined threshold, to the covariance of the deviation of the states.

[0115] Indeed, considering that the 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 rows (respectively columns) related 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 the person skilled in the art that the expectation of (( - X SF )(X - X SF ) T ) is equal to the difference of covariance matrix P SF - P, which when developed comes back to an expectation of equal to P the covariance matrix of the main Kalman filter 32.

[0116] According to an optional additional aspect, as described previously, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data according to the present invention itself determines during step 78, said threshold used to compare the deviation to the covariance of the deviation of the states.

[0117] In particular, during this sub-step 78, according to a false alarm probability noted P fa we seek to establish a real threshold value such that: e t p n+1 / n being respectively provided by the Kalman subfilter considered (when said sub-filter considered does not implement a point hybridization) and by the main Kalman filter, the Kalman sub-filter containing less information than the main Kalman filter 32, then by construction .

[0118] Furthermore, the difference also follows, by construction of the filters of Kalman a centered Gaussian distribution of standard deviation . Considering for example, a distribution of a Gaussian law centered at zero and with a standard deviation equal to one. The detection threshold is chosen for this example so that 1% of the time an error is detected which is not present (P fa = 0.01), which in this example leads to K fa = 1.96, which mathematically returns for a centered variable X and standard deviation equal to one to , and therefore to the threshold S such that: - Thus, as illustrated by test substep 82, when, according to branch 84, no alarm is raised because there is then no problem detected on the GNSS measurements. On the other hand, according to branch 88, when, a anomaly in GNSS measurements is detected and an alarm is raised.

[0119] It should be noted that test 82 is performed, 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.

[0120] As indicated previously, in the absence 84 of a deviation greater than said predetermined threshold S, no alarm is raised, and during a sub-step 86, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data then 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 Kalman sub-filters.

[0121] To determine such a protection radius, which is fully predictive, from the covariances of the main Kalman filter 32 and the Kalman sub-filters SF1, SF2, ... SF i , SF i+1 , ... SF N, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data introduces a probability of non-detection P nd .

[0122] In particular, taking as an example the state of latitude noted X lat , the protection radius R p is then defined as follows: with Σ N the sum over the N Kalman sub-filters, P lat the diagonal of the covariance matrix corresponding to the latitude state X lat .

[0123] Considering the simplest case where N =1, which amounts to using a single Kalman sub-filter, |X iat - lat vraie | is bounded with the state of this Kalman sub-filter which potentially can detect the GNSS failure (i.e. a vulnerability of the GNSS measurements): Moreover, as seen previously, at the time of detection , so that the whole issue of the protection radius RPlat lies in the fact that at this same moment of detection: - So taking , and considering that suit une centered Gaussian law of standard deviation. The determination of the protection radius comes down to finding the coefficient K nd such that: , so that it is then possible to guarantee that if the gap is less than , at the time of the GNSS failure, then with a probability of non-detection of the failure of P nd and then:

[0124] Considering the most complex case where N ≠ 1 , which amounts to using a plurality of Kalman sub-filters, making no assumption about the duration of the failure except that the failure cannot be undetected for , where is the period maximum duration of the periods corresponding to the recalibration period of each sub-filters of index i, then the protection radius preferentially corresponds to the maximum value of the protection radii of each of the sub-filters such that: , and this as long as the failure detection has not alarm raised. Once the alarm is raised, the protection radius can propagate with the error value in the following way: so it is then preferable to stop the recalibration mechanism by point hybridization with satellite data 24 of each Kalman sub-filter SF1, SF2, ... SF i , SF i+1 , ... SF N according to a resetting frequency F Ri included in a predetermined frequency range.

[0125] It should be noted that the previous example of determining the protection radius developed from the latitude state is generalizable to other states such as other position states (longitude, altitude) or even to speed or attitude and heading states. With regard to the reconfiguration sub-step 90, it should be noted that the architecture of the set K of Kalman filters proposed has the ability to offer a navigation solution not corrupted by the GNSS failure. Indeed, once the alarm is raised, just like the Kalman sub-filters SF1, SF2, ... SF i , SF i+1 , ... SF Nwere, prior to this alarm being raised, periodically and offset reconfigured on the main Kalman filter 32, it is possible to reconfigure the main Kalman filter 32 on an uncorrupted Kalman sub-filter, the choice of which depends on the desired application, a preferential and conservative choice being to take the Kalman sub-filter whose implementation of said punctual hybridization (i.e. the recalibration using punctually the GNSS data 24) is temporally the furthest from the alarm being raised, assuming that the GNSS failure cannot be undetected for , where is the period of maximum duration of the periods corresponding to the recalibration period of each sub-filter of index i. Thus during the reconfiguration, we overwrite the covariance matrix of the main Kalman filter 32 with that of the selected healthy sub-filter.

[0126] It should be noted that the positioning performance obtained using each sub-filter can be evaluated using a circular error probability, for example a CEP 50 corresponding to a probable circular error of 50%, which is the radius of the circle within which 50% of the values ​​of a two-dimensional measurement sample are located. In particular, a recalibration on a solution using satellite data, lasting one hundred seconds, for an implementation of the recalibration by point hybridization at a frequency of once every twenty-four hours makes it possible to cancel (or at least to drop) punctually and periodically (i.e. every twenty-four hours) the value of the CEP 50 which increases again at the end of the recalibration because it is representative of the drift of the Kalman sub-filter when it does not use satellite data outside of these hundred seconds of recalibration

[0127] Those skilled in the art will understand that the invention is not limited to the embodiments described, nor to the particular examples of the description, the embodiments and variants mentioned above being suitable for being combined with each other to generate new embodiments of the invention.

[0128] The present invention thus proposes an architecture of a set of Kalman filters with time-shifted recalibration due to a distinct recalibration frequency from one sub-filter to another, making it possible to maintain the integrity of the positioning independently of the vulnerability of the GNSS measurements by comparison.

[0129] -on the one hand, the primary position resulting from the classic INS / GNSS hybridization carried out by means of a main Kalman filter 32 using all available measurements as input: GNSS, external position, zero displacement recalibration when the vehicle is stationary, electromagnetic log measurement and a dynamic model of the vehicle, Doppler log or DVL, depth measurement, recalibration by radar, by imaging, recalibration by opportunity signals, etc.

[0130] - with on the other hand a subset of secondary positions provided by a bank of N Kalman sub-filters not using GNSS measurement input for a certain duration (apart from the implementation of said point hybridization according to a recalibration frequency F Riincluded in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another), which amounts to using partial measurements.

[0131] Such control is not carried out on only one satellite at a time, which avoids limiting the application area.

[0132] In addition, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data is, according to an optional aspect, capable of permanently offering a set of navigation solutions, some of which have not used GNSS measurements for a certain time, typically from several hours to several days.

[0133] Furthermore, according to an optional embodiment, the device 10 for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data is also capable of providing a protection beam against a vulnerability of the GNSS measurements and capable of triggering a reconfiguration of the main Kalman filter on a solution of a Kalman sub-filter if a vulnerability of the GNSS measurements is detected. Thus, a healthy fallback solution is permanently available in the event of detection of a problem on the GNSS signals.

[0134] In other words, the present invention makes it possible to maintain the integrity of the location, to warn when the GNSS signals are not reliable, to reconfigure itself on a solution not tainted by the vulnerability of the GNSS measurements, in other words, to reconfigure the main Kalman filter on a "healthy" Kalman sub-filter, and to have available a panel of navigation solutions deduced from Kalman sub-filters having navigated without the GNSS measurement for a variable time.

Claims

CLAIMS 1. Device (10) for maintaining the integrity of the positioning of a vehicle independently of the vulnerability of satellite data, suitable for being on board a vehicle suitable for moving between two distinct geographical positions, the device comprising at least: - an inertial measurement unit (12) capable of providing navigation measurements, - a receiver (16) of satellite positioning data, - a main closed-loop Kalman filter (32) configured to calculate navigation data corrections by permanent hybridization of satellite positioning data provided by said receiver and non-satellite positioning data provided at least by said inertial measurement unit, the device being characterized in that it further comprises a bank of N sub-filters (SF1, SF2, ... SF i , SF i+1 , ... SF N) of Kalman in parallel with N a predetermined integer such that N > 1, each Kalman sub-filter being configured to: - calculate navigation data corrections by point hybridization, according to a recalibration frequency F Ri included in a range of predetermined frequencies, of satellite positioning data provided by said receiver and of non-satellite positioning data provided at least by said inertial measurement unit, said resetting frequency being distinct from one sub-filter to another; - apart from the implementation of said point hybridization, calculating navigation data corrections solely from non-satellite positioning data provided at least by said inertial measurement unit.

2. Device (10) according to claim 1, in which the N Kalman sub-filters are identical and independent, the period 1 / F Ricorresponding to a period of verification of the integrity of said GNSS satellite positioning measurements.

3. Device (10) according to claim 2, wherein the device is also configured to: - check the integrity of said GNSS satellite positioning measurements by comparing, with a predetermined threshold, the difference between the state of each sub-filter, outside the implementation of said point hybridization, and the state of the main Kalman filter, and - in the event of a deviation greater than said predetermined threshold, raise an alarm to signal a vulnerability of said GNSS satellite positioning measurements.

4. Device (10) according to claim 3, wherein the device is also configured to determine said predetermined threshold as a function of a probability of false alarm.

5. Device (10) according to claim 3 or 4, wherein, in the event of an alarm being raised, the main Kalman filter is also configured to reconfigure itself on a predetermined Kalman sub-filter of index p with 1 ≤ p ≤ N.

6. Device (10) according to claim 5, in which said predetermined Kalman sub-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 Kalman sub-filter among said N Kalman sub-filters whose implementation of said point hybridization is temporally the furthest from the time of alarm raising.

7. Device (10) according to claim 5 or 6, wherein said main Kalman filter is configured to no longer use said GNSS satellite positioning measurements as input from the moment when the main Kalman filter initiates its reconfiguration.

8. Device (10) according to any one of claims 5 to 7, wherein in the event of an alarm being raised, each Kalman sub-filter of index i ≠ p is also configured to reconfigure itself on said predetermined Kalman sub-filter of index p.

9. Device (10) according to any one of the preceding claims, wherein the device is also configured to determine a protection radius with respect to a vulnerability of said GNSS satellite positioning measurements, said protection radius ensuring that the value of the distance between the hybrid position 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 N of Kalman sub-filters.

10. Device (10) according to any one of the preceding claims, in which the device is also configured to provide, at output, in parallel, navigation solutions respectively associated with said bank of N Kalman sub-filters, and with said main Kalman filter.

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