WO2024009048A1

WO2024009048A1 - Method for correcting an attitude provided by a dead reckoning navigation system by means of a relative positioning system

Info

Publication number: WO2024009048A1
Application number: PCT/FR2023/051071
Authority: WO
Inventors: David Vissiere; Mathieu Hillion; David LEBEL; Maxime LUCAS
Original assignee: Sysnav
Priority date: 2022-07-08
Filing date: 2023-07-10
Publication date: 2024-01-11
Also published as: FR3137764A1

Abstract

The invention relates to an attitude correction method (107) comprising estimating (116), by means of a dead reckoning navigation system (22), multiple estimated positions of the dead reckoning navigation system (22) in an arbitrary fixed reference frame at times of determination, obtaining (114) positions, evaluated by a relative positioning system (24), of the dead reckoning navigation system (22) in a predetermined fixed reference frame at the determination times and inferring (124) at least one attitude correction parameter by minimising a cost function comparing the evaluated positions with the estimated positions corrected by means of the or each correction parameter.

Description

DESCRIPTION

METHOD FOR REGISTERING AN ATTITUDE PROVIDED BY A MONITORING SYSTEM

DEAD COST NAVIGATION USING A RELATIVE POSITIONING SYSTEM

FIELD OF INVENTION

The present invention relates to dead reckoning navigation techniques, more particularly techniques for resetting an attitude provided by a dead reckoning navigation system. It finds an advantageous application in the case of travel in an urban or “indoor” environment, that is to say inside buildings.

TECHNOLOGICAL BACKGROUND

It is now common to track the position of an object by multi-lateration, by measuring the distances between a receiver attached to the object and at least three sources whose location in the environment is known. This is for example the case with positioning systems of the GNSS type (Global Navigation Satellite System, for example GPS) or taking advantage of the infrastructure of a wireless communication network (for example wifi network, GSM network, etc. .). These methods, however, prove to be very limited because they do not ensure availability and precision of the information, both of which are affected by possible masking between the sources and the receiver. Their use in an urban or “indoor” environment therefore requires deploying an expensive infrastructure with numerous sources distributed throughout the environment. They also prove to be dependent on external technologies such as satellites for GNSS which may be unavailable or even deliberately jammed.

Alternatively, we also know methods known as dead reckoning methods to track the relative position of an object in any environment using a motion sensor measuring the movement of the object. . By relative position, we mean the position of the object in space relative to a point and a reference given at initialization. In addition to the position, these methods also make it possible to obtain the orientation (also called "attitude") of the object with respect to the same initial reference frame, which is given, in dimension 3, by the Euler angles (roll <p, pitch 0, yaw qj) and, in dimension 2, by heading qj. These methods are preferred in case of movement in an environment where position tracking by multi-lateration is difficult, for example urban or “indoor” environments.

There are different types of dead reckoning navigation. The most common is so-called “simple” inertial navigation, as implemented in heavy applications such as the navigation of fighter or airliner planes, submarines, ships, etc. It is based on inertial units generally comprising a minimum of three accelerometers and three gyrometers arranged in a triaxis. Typically, gyrometers “maintain” a reference point, in which a double temporal integration of the accelerometer measurements makes it possible to estimate the movement. It is well known that to be able to use this “simple” inertial navigation method, it is necessary to use very high precision sensors. Indeed, the double temporal integration of an acceleration measurement means that a constant acceleration error creates a position error which increases proportionally to the square of the time.

Another known dead reckoning technique is the technique in which the speed vector information in the object's frame is provided by an external source (for example an odometer for a car, a log for a boat or a Pitot tube for an airplane). It is then sufficient to apply a simple integration to this speed vector information and combine it with orientation information and in particular the heading of the object to know its trajectory. For the same sensor measurement inaccuracy, the temporal drift is then less sensitive.

Most often, the initial attitude is known, for example by initial “alignment” of an inertial device or by provision by sensors other than inertial (for example magnetic). However, the measurement imprecision of inertial sensors induces a temporal drift in the measured attitude, which makes knowledge of the initial attitude obsolete after a more or less long time depending on the precision of the sensors used and leads to inaccuracies in the location of the object. For example, an error of 1% in the heading measurement leads, after a movement of 100 m, to an inaccuracy of 1 m in the location of the object.

To remedy this, it is known to regularly readjust the measurements of a dead reckoning navigation system by means of another positioning system, so as to best maintain the orientation information of the object, in especially the heading information. For example, it is known from WO 2019/020961 to readjust the orientation information using a magnetic heading measurement obtained by a magnetometer carried by the object.

However, this solution does not give complete satisfaction. Indeed, magnetometers suffer from their own inaccuracies and drifts which mean that their measurements are sometimes insufficiently reliable to use them as a basis for adjustment. In addition, this solution requires integrating magnetometers into the object whose position we want to track, which increases the cost.

STATEMENT OF THE INVENTION

An objective of the invention is to propose a simple and economical solution for resetting an attitude provided by a dead reckoning navigation system. Another objective is to allow such registration with great precision over a short distance. Another objective is to allow, in a simple and economical way, precise monitoring of people moving inside a building.

To this end, the subject of the invention is, according to a first aspect, an attitude resetting method for resetting an attitude provided by a dead reckoning navigation system, the resetting method comprising the following steps: estimation, by the dead reckoning navigation system, for each of a plurality of determination instants included in a movement interval during which the dead reckoning navigation system moves along a movement trajectory, of an estimated position of the dead reckoning navigation system in an arbitrary fixed reference at said instant of determination, obtaining, for each instant of determination, an evaluated position of the dead reckoning navigation system at said instant of determination in a predetermined fixed reference, said position evaluated having been evaluated by a relative positioning system, and deduction of at least one attitude adjustment parameter by minimization of a cost function comparing the evaluated positions to the estimated positions corrected by means of the or each adjustment parameter.

According to particular embodiments of the invention, the attitude adjustment method also has one or more of the following characteristics, taken in isolation or according to any technically possible combination(s): the dead reckoning navigation system is carried by a pedestrian, the dead reckoning navigation system system preferably being attached to a foot or ankle of the pedestrian; the dead reckoning navigation system comprises a motion sensor for measuring a movement of the dead reckoning navigation system and a processing unit for deducing from the measured movement an attitude and a position of the dead reckoning navigation system; the relative positioning system is chosen from: a multi-angulation system, a multi-lateration system, a map matching system and a visual positioning system, the relative positioning system preferably comprising a telemetry device on ultra-wideband; the arbitrary fixed reference and the predetermined fixed reference share a common axis, an attitude adjustment parameter consisting of a parameter, preferably an angle, for modification of orientation by rotation around said common axis; the common axis is a vertical axis; the cost function is representative of an average geometric difference between the evaluated positions and the estimated positions after application to the evaluated or estimated positions of a geometric transformation comprising a rotation and, preferably, a translation; the rotation is around an axis of rotation and the translation is in a direction orthogonal to said axis of rotation; the step of deducing the registration parameter comprises calculating a candidate value for the registration parameter, evaluating a precision value of said candidate value, comparing said precision value with a previous precision value associated with a previous registration parameter, and determining the registration parameter as a function of the result of the comparison, the registration parameter depending on the candidate value and the previous registration parameter. the precision value is a function of uncertainties in the estimated positions and the evaluated positions and/or an average geometric difference between the evaluated positions and the estimated positions after application of the candidate value of the registration parameter. the deduction of the adjustment parameter comprises the following sub-steps: oa) calculation of a first candidate value for the adjustment parameter by minimization of a cost function comparing the evaluated positions for N instants of determination at the positions estimated for said N instants of determination corrected by means of the adjustment parameter, ob) calculation of a first precision value associated with said first candidate value, oc) calculation of a second candidate value for the adjustment parameter by minimization of a cost function comparing the positions evaluated for N-1 determination instants, corresponding to said N determination instants minus the oldest determination instant, to the positions estimated for said N-1 determination instants corrected by means of the or each registration parameter, od) calculation of a second precision value associated with said second candidate value, oe) comparison of the first and second precision values, and of) selection of the first candidate value when the first precision value reflects the best precision; when the precision value reflecting the best precision is constituted by the second precision value, the deduction of the registration parameter comprises the following additional sub-steps: o deletion of the evaluated position and the estimated position for the instant of determination older, and o repetition of substeps a) to e) with a number N reduced by 1; and the dead reckoning navigation system has an accuracy in distance traveled of the order of a few percent, for example between 1 and 3%, and a few tens of degrees per hour, for example between 30 and 80 degrees per hour, in heading drift, and the relative positioning system has a precision of a few tens of centimeters, for example between 20 cm and 1 m, in position.

The invention also relates, according to a second aspect, to a method for locating an object in a predefined space, the method comprising the following steps: starting the dead reckoning navigation system, attitude resetting of the navigation system dead reckoning using a relative positioning system comprising an infrastructure installed at an access point to the predefined space, so as to obtain an attitude adjustment parameter, said attitude adjustment implementing a attitude resetting method according to any one of the preceding claims, position resetting of the dead reckoning navigation system using a relative positioning system comprising an infrastructure installed at said access point to the predefined space, so as to obtain a position adjustment parameter, and calculation, by the dead reckoning navigation system, by means of the attitude adjustment parameter and the position adjustment parameter, of a calculated position of the system dead reckoning navigation in the predetermined benchmark.

According to a particular embodiment of the invention, the location method also has the following characteristic: the infrastructure is on board a vehicle itself equipped with a location and orientation system making it possible to calculate the position of the infrastructure in the predetermined benchmark.

The invention also relates, according to a third aspect, to a dead reckoning navigation system comprising a movement sensor for measuring a movement of the dead reckoning navigation system and a processing unit for deducing an attitude from the measured movement. and a position of the dead reckoning navigation system in a fixed reference frame, the processing unit being configured to implement an attitude adjustment method according to the first aspect to reset said attitude.

According to a fourth aspect, the subject of the invention is a computer program product comprising code instructions for the execution of an attitude adjustment method according to the first aspect when said program is executed by a processor.

Finally, according to a fifth aspect, the invention relates to a storage means readable by computer equipment on which is recorded a computer program product comprising code instructions for the execution of an attitude adjustment method according to the first aspect.

BRIEF DESCRIPTION OF THE FIGURES

Other characteristics and advantages of the invention will appear on reading the description which follows, given solely by way of example and made with reference to the appended drawings, in which: Figure 1 is a top view of a system for locating an object in a predefined space according to an exemplary embodiment of the invention, Figure 2 is a perspective view of a detail of the location system of Figure 1, Figure 3 is a diagram of a location box of the location system of Figure 1, Figure 4 is a diagram illustrating a example of an object localization method in a predefined space implemented by the system of Figure 1, Figure 5 is a diagram illustrating a course adjustment step of the method of Figure 4, and Figure 6 is a diagram illustrating a sub-step of deducing a heading adjustment parameter of the heading adjustment step of Figure 5.

DETAILED DESCRIPTION OF AN EXAMPLE OF WORK

The location system 10 shown in Figure 1 is intended for the location of objects of interest 12 within a predefined space 14. For this purpose, the location system 10 comprises a plurality of location boxes 16 each attached to a respective object of interest 12. Here, the location system 10 also includes a location infrastructure 18 arranged at at least one access point 19 to the predefined space 14.

With reference to Figure 2, each object of interest 12 is here constituted by a pedestrian. The invention is particularly advantageous in such a use because it allows a very small footprint of the boxes 16, which can thus be easily carried in an ergonomic manner by pedestrians. As a variant (not shown), the objects of interest 12 consist of any mobile object whose position knowledge is desired, for example a wheeled vehicle, a drone, etc.

The predefined space 14 typically consists of a building interior. This is for example an industrial site, the pedestrians 12 then typically being technicians working on said industrial site. Alternatively, the predefined space 14 is an intervention site, for example a building on fire or a hostage-taking location, the pedestrians 12 then being firefighters or infantrymen intervening on said site.

Each location box 16 is typically attached to a limb, here a leg, preferably a foot or an ankle, of the pedestrian 12. For this purpose, each location box 16 comprises, as visible in Figure 3, a device for attachment 20 constituted here by a bracelet for example with a hook-and-loop strip which encloses the member and allows the secure connection. As a variant (not shown), the attachment member 20 is constituted by all element allowing an integral connection of the location box 16 with the object of interest 12.

Still with reference to Figure 3, the location box 12 includes a dead reckoning navigation system 22. It also includes a relative positioning system 24. In the example shown it also includes a communication system 26, typically a wireless communication system, for communicating the location box 12 with an external device such as a mobile terminal 29 (Figure 2), for example a multifunction mobile, or even a remote server (not shown). Optionally it includes a storage module 28.

The dead reckoning navigation system 22 comprises a motion sensor 30 for measuring a movement of the dead reckoning navigation system 22 and a processing unit 32 for deducing from the measured movement an attitude and a position of the dead reckoning navigation system. estimates 22 in a predetermined fixed reference, for example the Est-North-Haut reference (better known by the acronym ENU, from the English “East-North-Up”). By “fixed reference point”, we mean here and in the following that the reference point is immobile in the terrestrial frame of reference.

In the example described here, the dead reckoning navigation system 22 is configured to work in a two-dimensional reference frame and to provide only a heading and two position coordinates of the dead reckoning navigation system 22 in a horizontal plane of the predetermined benchmark. As a variant (not shown), the dead reckoning navigation system 22 is configured to work in a three-dimensional reference frame and therefore to provide a roll angle, a pitch angle and a yaw angle of the dead reckoning navigation system 22, as well as its three position coordinates in the predetermined reference frame. Those skilled in the art will easily be able to transpose the example given here from the two-dimensional case to the three-dimensional case.

The motion sensor 30 comprises a gyrometer 40 for measuring an angular speed of the dead reckoning navigation system 22 according to a system of three orthogonal axes defining a mobile reference frame secured to the housing 16, i.e. measuring the three components of a speed vector angular in said mobile reference. We thus understand that the gyrometer 40 can in fact designate a set of three gyrometers associated with one of the three axes, in particular in tri-axis (i.e. each capable of measuring one of the three components of the angular velocity vector).

The motion sensor 30 also includes a member 42 for acquiring a linear speed of the dead reckoning navigation system 22, that is to say the displacement. This acquisition member 42 can make it possible to obtain the linear speed directly or indirectly, and thus be of varied type. For example, the acquisition member 42 may consist of one or more accelerometers (not shown). These accelerometers are advantageously arranged in a tri-axis, typically according to the same system of three orthogonal axes as the gyrometer 40. They are sensitive to external forces other than gravitational applied to the sensor 30, and make it possible to measure a specific acceleration. The linear speed is then obtained by temporal integration of this acceleration.

Alternatively, when the object 12 is a wheeled vehicle, the acquisition member 42 consists of at least two odometers each for one wheel of the vehicle, for example the two rear wheels. By odometer we mean equipment capable of measuring the speed of a wheel by counting the revolutions (“tachometer”). Generally, odometers have a part fixed to the wheel (for example a magnet), and detect each passage of this fixed part (called "top") so as to count the number of revolutions per unit of time, which is the frequency of rotation. Other techniques are known, for example the optical detection of a mark on the wheel, or the magnetometer of patent FR 2 939 514 which detects the rotation of a metallic object such as a wheel. Here the “speed” of a wheel is a scalar, that is to say the norm of the speed of the wheel in the terrestrial frame of reference (assuming no slippage). If the radius of the wheel is known, measuring the rotation frequency makes it possible to estimate this speed standard.

Optionally, the motion sensor 30 further comprises a stride detector (not shown) to detect when the foot of the pedestrian 12 is on the ground, as described for example in document WO 2017/060660.

In the example shown, the processing unit 32 is constituted by a programmable machine, such as a DSP (“Digital Signal Processor” in English) or a microcontroller. It includes a processor or CPU (“Central Processing Unit” in English) 44 and a memory 46 of the RAM (“Random Access Memory” in English) and/or ROM (“Read Only Memory” in English) type. The processor 44 is configured to execute instructions loaded in the memory 46. When the dead reckoning navigation system 22 is powered on, the processor 44 is capable of reading instructions from the memory 46 and executing them. These instructions form a computer program causing the calculation, by the processor 44, of the heading and the position of the dead reckoning navigation system 22 in the predetermined fixed reference, for example by implementing the method described in WO 2017/060660 or FR 2 939 514.

As a variant (not shown), the processing unit 32 is constituted by a machine or a dedicated component, such as an FPGA (“Field-Programmable Gate Array” in English) or an ASIC (“Application-Specific Integrated Circuit” in English). The processing unit 32 also comprises a buffer memory 49 for the temporary storage of information necessary for calculating the heading position and the position of the dead reckoning navigation system 22 in the predetermined fixed reference.

Optionally, the dead reckoning navigation system 22 also includes a network of magnetometers 48 linked to the housing 16, that is to say they each have a movement substantially identical to that of the housing 16 in the terrestrial reference frame, and spatially spaced from each other. Each magnetometer 48 is a three-axis magnetometer capable of measuring a magnetic field along three axes. For this purpose, each magnetometer 48 is typically constituted by three single-axis magnetometers (not shown) oriented along axes substantially perpendicular to each other. These axes are preferably the same as those of the system of three orthogonal axes of the gyrometer 40.

The network of magnetometers 48 is suitable, due to its particular geometry, to authorize the determination, at each instant of measurement of the magnetometers 48, of a spatial gradient of the measured magnetic field, in particular of the coefficients of this gradient along each of the axes of the mobile reference linked to the housing 16. Each coefficient of said gradient is for example determined by a method using the vector measurements of the magnetic field carried out by the magnetometers 48, associated with optimization methods of the least square or median filter type or associated with the properties intrinsics of the magnetic field described by Maxwell's equations. However, any other conventional method suitable for calculating the coefficients of the spatial gradient of the magnetic field is suitable.

The processing unit 32 is then typically configured to adjust the determination of the speed of the dead reckoning navigation system 22 by implementing the method described in EP 2 541 199.

The dead reckoning navigation system 22 typically has an accuracy of the order of a few percent, for example between 1 and 3%, in distance traveled and a few tens of degrees per hour, for example between 30 and 80 degrees per hour. , in course drift.

The relative positioning system 24 is capable of identifying a relative position of a point secured to the dead reckoning navigation system 22 relative to a reference system having a known position in the predetermined fixed reference, and of deducing the position of the dead reckoning navigation system 22 in the predetermined fixed reference. For this purpose, the relative positioning system 24 comprises a sensor 50 capable of measuring a parameter making it possible to locate the point attached to the reference system, and a processing unit 52 for deducing from this parameter a position of the navigation system at esteems it 22 in the predetermined fixed reference. Preferably, the relative positioning system 24 is constituted by a multi-lateration system, in particular by a proximity multi-lateration system. The infrastructure 18 then comprises, at the level of the or each access point 19, at least three beacons 54 (Figure 2) (or "anchors") each having a known position in the predetermined fixed reference and with which the system of relative positioning 24 is configured to communicate. For this purpose, the sensor 50 is typically constituted by a wireless communication system capable of communicating with the beacons 54 and of deducing the distance with each beacon 54, for example by measuring the round trip distance (better known as acronym “TWR”, from the English “two-way ranging”).

Preferably, the sensor 50 is constituted by an ultra-wide band telemetry device capable of communicating with the beacons 54 and measuring its distance from the beacons 54 via the ultra-wide band protocol (better known by the acronym UWB , from the English “Ultra Wide Band”), which allows precision in measuring the position of around ten centimeters, typically between 20 cm and 1 m. As known to those skilled in the art, the ultra-wideband protocol is a radio communication protocol based on the transmission of very short pulses (of the order of a nanosecond) over a wide frequency spectrum. Communications thus benefit from a wide bandwidth (500 to 1350 MHz) in the range 0.5 to 9.5 GHz (central frequency) depending on the channel used. Alternatively, the sensor 50 is capable of communicating with the beacons 54 via the Bluetooth protocol or the Wi-Fi protocol.

Alternatively, the multi-lateration system is constituted by a GNSS system.

The processing unit 52 is then configured to deduce from distance measurements and known positions of the beacons 54 the relative position of the sensor 50 in the predetermined fixed reference frame, typically by multi-lateration or by optimization, and to deduce from this position, as well as the position of the sensor 50 relative to the dead reckoning navigation system 22, the position of the dead reckoning navigation system 22 in the predetermined fixed reference.

According to another embodiment (not shown), the relative positioning system 24 is constituted by a multi-angulation system, the sensor 50 then being capable of measuring at least one angle between the observation directions of two beacons each having a known position in the predetermined fixed reference. The processing unit 52 is then configured to deduce from the angle measurement(s) and the known position of the beacons 54 the position of the sensor 50 in the predetermined fixed reference frame, typically by multi-angulation, and to deduce of this position, and the position of the sensor 50 relative to the dead reckoning navigation system 22, the position of the dead reckoning navigation system 22 in the predetermined fixed reference.

According to yet another embodiment (not shown), the relative positioning system 24 is constituted by a card matching system. The sensor 50 is then capable of measuring a parameter of the environment, for example the relief or the magnetic field, and the processing unit 52 is capable of matching this measurement with a map of said parameter which it stores in memory. , so as to deduce the position of the sensor 50 in the predetermined fixed reference.

According to a fourth embodiment (not shown), the relative positioning system 24 is constituted by a visual positioning system. The sensor 50 is then constituted by an imager associated with an image processing system. The imager is configured to acquire images of the environment and the processing system to detect in each image a remarkable point, for example a target, whose position is known in the predetermined fixed reference frame. The processing unit 52 is then configured to deduce a relative position of the sensor relative to the remarkable point, and to deduce from this relative position, as well as from the known position of the remarkable point and from the position of the sensor 50 relative to the dead reckoning navigation system 22, the position of the dead reckoning navigation system 22 in the predetermined fixed reference.

As a variant (not shown), the imager is fixed (it belongs to the infrastructure 18) and it is the remarkable point (typically the target) which is carried by the housing 16. As a further variant, we can provide a configuration motion capture in which several targets are carried by the box 16 and detected by a fixed imager.

In the example shown, the processing unit 52 is constituted by a programmable machine, such as a DSP (“Digital Signal Processor” in English) or a microcontroller. It includes a processor or CPU (“Central Processing Unit” in English) 56 and a memory 58 of the RAM (“Random Access Memory” in English) and/or ROM (“Read Only Memory” in English) type. The processor 56 is configured to execute instructions loaded into the memory 58. When the relative positioning system 24 is powered on, the processor 56 is capable of reading instructions from the memory 58 and executing them. These instructions form a computer program causing the calculation, by the processor 56, of the position of the dead reckoning navigation system 22 in the predetermined fixed reference from the parameter measured by the sensor 50. As a variant (not shown), the processing unit 52 is constituted by a machine or a dedicated component, such as an FPGÀ (“Field-Programmable Gate Array” in English) or an ÀSIC (“Application-Specific Integrated Circuit” in English).

In the example shown, the processing unit 52 of the relative positioning system 24 is distinct from that 32 of the dead reckoning navigation system 22. Alternatively (not shown) these processing units 32, 52 are combined.

The communication system 26 is configured to implement short-range wireless communication, for example Bluetooth or Wi-Fi (in particular in an embodiment with a mobile terminal 29) and/or to connect to a mobile network ( typically UMTS/LTE/5G) for long distance communication. As a variant (not shown), the communication system 26 is for example a wired connection (typically USB) to transfer data from the storage module 28 to another storage module, typically from the mobile terminal 29.

For example, the communication system 26 is configured to send the position calculated by the dead reckoning navigation system 22 to the mobile terminal 29 for display of the position by the mobile terminal 29 in a navigation software interface.

In the examples described above, the processing units 32, 52 of the dead reckoning navigation system 22 and the relative positioning system 24 are integrated into the housing 16. Alternatively (not shown), at least part of these processing units 32, 52 is remote, for example in the mobile terminal 29, in the infrastructure 18 and/or in a remote server (not shown). In other words, at least part of the steps of calculating the position of the dead reckoning navigation system 22 by the dead reckoning navigation system 22 or by the relative positioning system 24 is carried out by the mobile terminal 29 , the infrastructure 18 and/or a remote server. The communication system 26 is then configured to send the data from the motion sensor 30 and/or the sensor 50 to the mobile terminal 29, the infrastructure 18 and/or the remote server. Advantageously, the communication system 26 is also configured to receive from the mobile terminal 29, the infrastructure 18 and/or the remote server the position of the dead reckoning navigation system 22 calculated by the dead reckoning navigation system 22 or by the relative positioning system 24.

Returning to Figures 1 and 2, the infrastructure 18 comprises, as described above, a plurality of beacons 54 arranged at the access points 19 to the predefined space 14. These beacons 54 are typically grouped within portals arranged at the access points 19, such as the portal 60 shown in Figure 2. Each portal 60 includes a minimum of three beacons 54 so as to allow the positioning of pedestrians 12 crossing the access point 19 by multi-lateration.

Infrastructure 18 is for example a permanent fixed infrastructure. This is particularly the case when the predefined space 14 is an industrial site and the location system 10 is intended to follow the movement of technicians on said site. Alternatively, architecture 18 is a temporary fixed infrastructure. This is for example the case when the predefined space 14 is an intervention site, particularly in the event of a fire: the infrastructure 18 is then brought and installed at one of the access points of the intervention site before the arrival of the firefighters. As a further variation, infrastructure 18 is a mobile infrastructure. It is typically carried on board a vehicle (not shown) used for transporting pedestrians 12 whose movement we wish to follow up to the predefined space 14. This vehicle is then itself equipped with a monitoring system. location and orientation making it possible to calculate the position of the infrastructure 18 in the predetermined benchmark. This is for example the case when the predefined space 14 is an intervention site, particularly in the event of a hostage taking.

A method 100 implemented by the location system 10, more particularly by the processing units 32, 52, will now be described, with reference to Figures 4 to 6.

As visible in Figure 4, the method 100 begins with a first step 102 of starting the dead reckoning location system 22. This first step 102 is typically implemented while the pedestrian 12 carrying the box 16 is still out of sight. the predefined space 14. Typically, step 102 is initiated by pressing, by the pedestrian 12, on a button (not shown) of the box 16. The relative positioning system 24 typically starts concomitantly with step 102.

After its startup, the dead reckoning location system 22 provides a position of the pedestrian 12 in an arbitrary fixed reference frame. This position v(t) is affected

from a random error. For simplification, this random error is here assimilated to a. , , . , , . Gaussian centered variance variable By

further simplification, we hypothesize below that there is no spatial correlation between the directions of the plane, that is to say that the terms ( ) and

are harmed. Still for simplification, we consider in the following that the terms are equal, so that the variance can be written

reflects an uncertainty on the position v(t) and is the identity matrix of dimension 2. If this uncertainty σ _v (t) is a priori variable over time, the amplitude of this variation is generally quite small. It is therefore considered, here and in the following, a constant uncertainty σ _v .

The dead reckoning location system 22 also provides a heading for the pedestrian 12

in said arbitrary fixed benchmark. This arbitrary fixed reference is a two-dimensional horizontal reference which typically consists of a rotation of the predetermined fixed reference by an angle 0 around the vertical axis and a translation of a horizontal vector Δ. The arbitrary fixed reference thus shares a common axis with the predetermined fixed reference, constituted by the vertical axis. It is chosen arbitrarily by the dead reckoning location system 22 depending on its orientation at start-up.

The relative positioning system 24 provides a horizontal position of the pedestrian 12 in the predetermined fixed reference. This position u(t) is

affected by a random error. For simplification, this random error is here assimilated to . , , . , , . a centered Gaussian variable with variance By

further simplification, we hypothesize below that there is no spatial correlation between the directions of the plane, that is to say that the terms

and have harmed. Still for simplification, we consider in the following that the terms

are equal, so that the variance r _u can be written

x I ₂ , where σ _u (t) reflects an uncertainty on the position u(t) and is the identity matrix of dimension 2. If

this uncertainty σ _u (t) is a priori variable over time, the amplitude of this variation is generally quite small. It is therefore considered, here and in the following, a constant uncertainty σ _u .

Step 102 is followed by a step 104 of determining the possibility, for the relative positioning system 24, of evaluating the position of the dead reckoning navigation system 22 in the predetermined fixed reference. If the determination is positive, that is to say typically if the box 16 is within range of the beacons 54 of the infrastructure 18, step 104 is followed by a step 106 of resetting the navigation system to the estimates 22 in position and a step 107 of resetting the navigation system to dead reckoning 22 in heading. If the determination is negative, that is to say typically if the box 16 is out of range of the beacons 54 of the infrastructure 18, step 104 is repeated after a time delay.

During the position registration step 106, the dead reckoning navigation system 22 estimates the position v(to) of the pedestrian 12 in the arbitrary fixed reference at a time to while the relative positioning system 24 evaluates the position of the pedestrian u(to) in the marker fixed predetermined at said instant t ₀ and communicates this evaluated position u(to) to the dead reckoning navigation system 22. The dead reckoning navigation system 22 then determines a resetting parameter in position <5 constituted by the difference between the positions evaluated u(to) and estimated

. The dead reckoning navigation system 22 then adjusts the estimated position by applying said position adjustment parameter

With reference to Figure 5, the heading adjustment 107 begins with the movement 110 of the pedestrian 12 following a movement trajectory during a movement interval while the box 16 is within range of the beacons 54 of the infrastructure 18.

During this movement 110, the heading adjustment 107 comprises, for a plurality of evaluation instants i _k included in the movement interval, an evaluation 112 of the position u(i _k ) of the pedestrian 12 by the positioning system relative 24 in the fixed reference predetermined at said evaluation instant i _k . This evaluation 112 is followed by the reception 114 of this evaluated position u(i _k ) by the dead reckoning navigation system 22.

In parallel, the heading adjustment 107 also includes, for a plurality of estimation instants t _k included in the movement interval, an estimation 116 of the position v(i _k ) of the pedestrian 12 by the navigation system at estimates it 22 in the arbitrary fixed reference at said estimation instant T _k .

The reception 114 and estimation 116 steps are followed by a step 118 of matching the positions evaluated u(i _k ) and estimated v(i _k ) by the dead reckoning navigation system 22. Indeed, the registration step 107 is based on the exploitation of evaluated positions synchronous with estimated positions. However, these two types of positions come from different origins, the evaluation times i _k generally differ from the estimation times T _k . A correspondence is therefore necessary between the evaluated positions u(i _k ) and estimated v(t _k ). This matching aims to associate and synchronize the evaluated positions u(i _k ) and estimated v(t _k ), in order to be able to have, for each of a plurality of determination instants t _k , a position pair evaluated u(t _k ) and estimated position v(t _k ) at said instant of determination t _k . This correspondence therefore consists of deducing from the set {u(i _k )} _k of the evaluated positions u(i _k ) at the evaluation instants i _k and from the set {vti _k )} _k of the estimated positions v (i _k ) at estimation times t _k : a set {u(t _k )} _k of evaluated positions u(t _k ) at determination times t _k , and a set {v(t _k )} _k of positions estimated v(t _k ) at the determination instants t _k . To this end, the matching comprises for example the interpolation of at least one set or subset among: the set {u(ik)}k of evaluated positions u(ik) at evaluation times i _k , and the set {v(T _k )} _k of estimated positions v(i _k ) at estimation times _Tk .

This interpolation preferably uses time splines. Preferably, the splines used for the interpolation are differentiable at least twice. The spline representation makes it possible in particular to force the continuity of the trajectory. The spline representation also makes it possible to optimize the various parameters involved, in particular the temporal synchronization parameters, using a method based on the gradient of a criterion to be minimized. Alternatively, the interpolation uses another approach, such as for example a discrete representation of the trajectory traveled by the pedestrian 12.

Preferably, only the set of estimated positions {v(T _k )} _k is interpolated, the determination instants t _k being chosen as being equal to the evaluation instants i _k : t _k = i _k . The set {u(t _k )} _k of evaluated positions u(t _k ) at the determination instants t _k is therefore confused with the set {u(i _k )} _k of evaluated positions u(i _k ) at the instants of evaluation i _k . The reception 114 by the dead reckoning navigation system 22 of an evaluated position u(i _k ) at an evaluation instant i _k thus constitutes a step of obtaining, by the dead reckoning navigation system 22, of an evaluated position u(t _k ) of the pedestrian 12 at a determination time t _k .

Alternatively, only the set of evaluated positions {u(t _k )} _k is interpolated, the determination times t _k being chosen as being equal to the estimation times t _k : t _k = t _k . The matching 118 thus constitutes a step of obtaining, by the dead reckoning navigation system 22, an evaluated position u(t _k ) of the pedestrian 12 at a determination time t _k .

It should be noted that in the case where the evaluation instants i _k correspond to the evaluation instants T _k , the matching 118 is limited to associating the evaluated positions u(i _k ) and estimated v(i _k ) to the same instants i _k , T _k , which then become instants of determination t _k .

The matching 118 is followed by the addition 120 of the pair of positions u(t _k ), v(t _k ) thus matched in the buffer memory 49 then by cleaning 122 of the buffer memory 49. This cleaning 122 consists by deleting from the buffer memory 49 pairs of positions u(t _k ), v(t _k ) associated with determination instants t _k which are no longer in the movement interval, the movement interval being included here as a sliding time window, of predetermined duration, ending on the date of the most recent evaluation moment i _k or estimation t _k .

These steps 120, 122 are followed by a step 124 of deducing a heading adjustment parameter 0. This heading 0 adjustment parameter is here constituted by a parameter, in in particular an angle, of modification of orientation by rotation around an axis of the predetermined reference, here the vertical axis. Optionally, the heading adjustment 107 also includes, in parallel with step 124, other steps (not shown) of deducing other heading adjustment parameters, for example a parameter for correcting a bias in angular variation of path.

With reference to Figure 6, this step 124 comprises a first sub-step 130 of calculating a first candidate value 01 for the heading adjustment parameter 0 with all the points, that is to say all the pairs of positions u(t _k ), v(t _k ), contained in the buffer memory 49. This first candidate value 01 is calculated by minimization of a cost function comparing the positions u(t _k ) evaluated at the N determination times t _k corresponding to the pairs of positions u(t _k ), v(t _k ) included in the buffer memory 49 at the estimated positions v(t _k ) for said N determination instants t _k corrected by means of the heading adjustment parameter 0 and of the adjustment parameter in position Δ. This cost function is in particular representative of an average geometric difference between the evaluated positions {u _k } _k and the estimated positions {v _k } _k after application to the evaluated positions {u _k } _k of a geometric transformation comprising: a rotation around an axis of the predetermined reference frame, here the vertical axis, by an angle equal to the heading adjustment parameter 0, and a translation in a direction orthogonal to said axis by a vector equal to the position adjustment parameter A .

Thus, the cost function is for example equal to

Or :

{u _k } _k is the set of positions evaluated at the determination times; {v _k } _k is the set of positions estimated at the determination times; {t _k } _k is the set of determination instants;

N is the number of pairs of positions u(t _k ), v(t _k ) included in buffer memory 49;

0 is the heading adjustment parameter;

R(0) is the rotation matrix representative of the modification of the orientation by application of the heading adjustment parameter; And

A is the position adjustment parameter.

The first candidate value 01 is thus equal to atan

U ₁ (t _k ) is a first position coordinate, along a first axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination time t _k ;

-

is an average of the first position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants;

u ₂ (t _k ) is a second position coordinate, along a second axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination time t _k ;

-

is an average of the second position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants;

v ₁ (t _k ) is a first position coordinate, along a first axis of the arbitrary fixed reference frame, of the estimated position of the dead reckoning navigation system 22 at a determination time t _k ;

-

is an average of the first position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination times;

v ₂ (t _k ) is a second position coordinate, along a second axis of the arbitrary fixed reference frame, of the estimated position of the dead reckoning navigation system 22 at a determination time t _k ;

-

is an average of the second position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants; And

N is the number of pairs of positions u(t _k ), v(t _k ) included in buffer memory 49.

As a variant (not shown), the cost function includes a weighting of the different terms of the sum

for example according to the likelihood of said terms (typically terms associated with higher variances would be assigned a lower weight) or the geometric distance between the different terms (typically terms geometrically close to each other would be assigned a lower weight). lower weight). As a further variation, the geometric transformation is applied to the estimated positions {v _k } _k and not to the evaluated positions {u _k } _k : the terms of the sum is then written As another variant, the transformation

geometric also includes: a straightening of the trajectory, parameterized by a parameter b for correcting a bias in angular variation of the trajectory: the terms of the sum are then written

; and/or a homothety, parameterized by a scale factor h: the terms of the sum are then written

This sub-step 130 is followed by a sub-step 132 of evaluating a first precision value σ _θ1 associated with said first candidate value 01. This first precision value σ _θ1 is for example a function of the uncertainties σ _v , σ _u on the estimated positions {v _k } _k and the evaluated positions {u _k } _k . It is typically constituted by the standard deviation of the first candidate value 01 and is given by the following formula:

{u _k } _k is the set of positions evaluated at the determination times, {v _k } _k is the set of positions estimated at the determination times, {t _fc } _k is the set of determination times, is the variance of the random error affecting each coordinate of the position evaluated by the relative positioning system 24, is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22, is a first position coordinate, along a first axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , is a second position coordinate, along a second axis of the

predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , v ₁ (t _k ) is a first position coordinate, along a first axis of the arbitrary fixed reference, of the position estimated from the dead reckoning navigation system 22 at a determination instant t _k , v ₂ (t _k ) is a second position coordinate, along a second axis of the arbitrary fixed reference, of the estimated position of the navigation system at l 'estimates 22 at a moment of determination t _k , -

is the average of the first position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination times

-

is the average of the second position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination times

-

is the average of the first position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination times

-

is the average of the second position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants, and

Alternatively, the first precision value

is a function of an average difference observed between all of the evaluated positions and all of the estimated positions {v _k } _k

associated, corrected by means of the heading adjustment parameter 0 having the first candidate value 01. It is for example given by the following formula:

N is the number of pairs of positions u(t _k ), v(t _k ) included in the buffer memory 49, is the set of positions evaluated at the determination instants; is the set of positions estimated at the determination instants;

is the average of the evaluated position of the dead reckoning navigation system 22 over all the determination times

v is the average of the estimated position of the dead reckoning navigation system 22 over all the determination times

01 is the heading adjustment parameter assigned to the first candidate value 01, and

R(0i) is the rotation matrix representative of the modification of the orientation by application of the heading adjustment parameter.

Alternatively, the first precision value is a combination of a function of the uncertainties σ _v , σ _u on the estimated positions and the evaluated positions and

of a function of an average difference observed between all of the evaluated positions {u _k } _k and all of the associated estimated positions {v _k } _k , corrected by means of the heading adjustment parameter 0 having the first value candidate 0i.

In parallel with sub-steps 130, 132, deduction step 124 also includes a sub-step 134 for calculating a second candidate value θ2 for the heading adjustment parameter 0 without the oldest point contained in the buffer memory 49, that is to say with all the pairs of positions u(t _k ), v(t _k ) contained in the buffer memory 49 except the pair of positions u(ti), v(ti) associated with the oldest moment of determination. This second candidate value θ2 is calculated by minimization of a cost function comparing the positions u(t _k ) evaluated at the N-1 determination instants t _k corresponding to the pairs of positions u(t _k ), v(t _k ) the most recent included in the buffer memory 49 at the estimated positions v(t _k ) for said N-1 determination instants t _k corrected by means of the heading adjustment parameter 0 and the position adjustment parameter A. This cost function is in particular representative of an average geometric difference between the evaluated positions {u _k } _k and the estimated positions {v _k } _k after application to the evaluated positions {u _k } _k of a geometric transformation comprising: a rotation around a axis of the predetermined reference frame, here the vertical axis, by an angle equal to the heading adjustment parameter 0, and a translation in a direction orthogonal to said axis of a vector equal to the position adjustment parameter A.

Thus, the cost function is for example equal to

Or :

{u _k } _k is the set of positions evaluated at the determination times; {v _k } _k is the set of positions estimated at the determination times; is the set of moments of determination;

0 is the heading adjustment parameter;

R(0) is the rotation matrix representative of the modification of the orientation by application of the heading adjustment parameter; and A is the position adjustment parameter.

The second candidate value θ2 is thus equal to atan2

-

is an average of the first position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants except the oldest;

-

is an average of the second position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants except the oldest;

-

is an average of the first position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants except the oldest;

-

is an average of the second position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants except the oldest; And

for example according to the likelihood of said terms (typically terms associated with higher variances would be assigned a lower weight) or the geometric distance between the different terms (typically terms geometrically close to each other would be assigned a lower weight). lower weight). As a further variation, the geometric transformation is applied to the estimated positions {v _k } _k and not to the evaluated positions {u _k } _k : the terms of the sum is then written

Still as a variant, the geometric transformation also includes: a straightening of the trajectory, parameterized by a parameter b for correcting a bias in angular variation of the trajectory: the terms of the sum are then written

and/or a homothety, parameterized by a scale factor h: the terms of the sum are then written

This sub-step 134 is followed by a sub-step 136 of evaluating a second precision value σ _θ2 associated with said second candidate value θ2. This second precision value σ _θ2 is for example a function of the uncertainties σ _v , σ _u on the estimated positions {v _k } _k the evaluated positions {u _k } _k . It is typically constituted by the standard deviation of the second candidate value θ2 and is given by the following formula:

^{<T02 0U} '

{u _k } _k is the set of positions evaluated at the determination times, {v _k } _k is the set of positions estimated at the determination times, {t _k } _k is the set of determination times, is the covariance of the random error affecting each coordinate of the position evaluated by the relative positioning system 24, is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22,

is a first position coordinate, along a first axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , u ₂ (t _k ) is a second position coordinate, along a second axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , v ₁ (t _k ) is a first position coordinate, along a first axis of the fixed reference arbitrary, of the estimated position of the dead reckoning navigation system 22 at a determination instant t _k , v ₂ (t _k ) is a second position coordinate, along a second axis of the arbitrary fixed reference, of the estimated position of the dead reckoning navigation system 22 at a determination time t _k , -

is the average of the first position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants with the exception of the oldest {t _k ] _k=2 ,

-

is the average of the second position coordinate of the evaluated position of the dead reckoning navigation system 22 over all the determination instants with the exception of the oldest {t _k ] _k=2 ,

-

is the average of the first position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants with the exception of the oldest {t _k ] _k=2 ,

-

is the average of the second position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants with the exception of the oldest {t _k ] _k=2 , and

Alternatively, the second precision value σ _θ2 is a function of an average difference observed between all of the evaluated positions {u _k } _k and all of the associated estimated positions {v _k } _k , corrected by means of the parameter of adjustment to heading 0 having the second candidate value θ2. It is for example given by the following formula:

N is the number of pairs of positions u(t _k ), v(t _k ) included in buffer memory 49,

{u _k } _k is the set of positions evaluated at the determination times; {v _k } _k is the set of positions estimated at the determination times; ü is the average of the evaluated position of the dead reckoning navigation system 22 over all the determination instants except the oldest

v is the average of the estimated position of the dead reckoning navigation system 22 over all the determination times except the oldest

θ2 is the heading adjustment parameter assigned to the second candidate value θ2, and

R(θ2) is the rotation matrix representative of the modification of the orientation by application of the heading adjustment parameter. Alternatively, the first precision value σ _θ2 is a combination of a function of the uncertainties σ _v , σ _u on the estimated positions {v _k } _k and the evaluated positions {u _k } _k and a function of a average difference observed between all of the evaluated positions {u _k } _k and all of the associated estimated positions {v _k } _k , corrected by means of the heading adjustment parameter 0 having the first candidate value θ2.

Substeps 132 and 136 are followed by a substep 140 of comparing the first precision value σ _θ1 with the second precision value σ _θ2 .

If the first precision value σ _θ1 reflects better precision than the second value σ _θ2 , that is to say here if σ _θ1 < σ _θ2 , then step 140 is followed by a step 142 of selecting the first candidate value 01 as selected candidate value.

If, on the other hand, the precision value reflecting the best precision is constituted by the second precision value σ _θ2 , that is to say here if σ _θ1 >σ _θ2 , then step 140 is followed by a step 144 of deletion of the oldest point from buffer memory 49, that is to say of the pair of positions u(ti), v(ti) associated with the oldest determination instant ti. The remaining determination moments are then renumbered in and the steps

130 to 140 are repeated.

This maximizes the precision of the registration parameter 0.

Substep 142 is optionally followed by a set of substeps 150 to 154 aimed at validating the new adjustment parameter 0 from a residual calculation.

Substep 142 is then followed by a substep 150 of calculating an expected registration residue r ^exp . This registration residual is intended to reflect the expected average difference between all of the evaluated positions {u _k } _k and all of the associated estimated positions {v _k } _k , corrected using the heading 0 registration parameter. It is given by the following formula:

N is the number of pairs of positions u(t _k ), v(t _k ) included in the buffer memory 49, is the covariance of the random error affecting each coordinate of the position evaluated by the relative positioning system 24, is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22,

- is the covariance of the registration parameter 0, equal to the square of the standard deviation σ _θ1 , discussed above, of the selected candidate value 01, U ₁ (t _k ) is a first position coordinate, along a first axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , u ₂ (t _k ) is a second position coordinate, along a second axis of the predetermined fixed reference, of the evaluated position of the dead reckoning navigation system 22 at a determination instant t _k , v ₁ (t _k ) is a first position coordinate, according to a first axis of the arbitrary fixed reference, of the estimated position of the dead reckoning navigation system 22 at a determination instant t _k , v ₂ (t _k ) is a second position coordinate, along a second axis of the arbitrary fixed reference , from the estimated position of the dead reckoning navigation system 22 at a determination time t _k ,

-

is the average of the first position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination instants and

-

is the average of the second position coordinate of the estimated position of the dead reckoning navigation system 22 over all the determination times

Sub-step 150 is followed by a sub-step 152 of calculating an observed registration residue r° ^bs . This adjustment residual is intended to reflect the average difference observed between all of the evaluated positions {u _k } _k and all of the associated estimated positions {v _k } _k , corrected using the assigned heading 0 adjustment parameter. of the selected candidate value 01. It is given by the following formula:

{u _k } _k is the set of positions evaluated at the determination times; {v _k } _k is the set of positions estimated at the determination times; ü is the average of the evaluated position of the dead reckoning navigation system 22 over all the determination times

0 is the heading adjustment parameter, and

R(0) is the rotation matrix representative of the modification of the orientation by application of the heading adjustment parameter.

Sub-step 152 is followed by a sub-step 154 of comparing the observed registration residue r° ^bs with the expected registration residue r ^exp , increased by a predetermined threshold <5.

If the observed registration residual r ^obs is strictly greater than the sum of the expected registration residue r ^exp with the threshold <5, that is to say if the inequality is

verified, then sub-step 154 is followed by a sub-step 156 of rejecting the selected candidate value. The adjustment parameter 0 then retains its previous value.

If the observed registration residue r° ^bs is less than or equal to the sum of the expected registration residue r ^exp with the threshold <5, that is to say if the inequality is verified,

then sub-step 154 is followed by a sub-step 158 of comparing the precision value σ _θn associated with the selected candidate value with a precision value σ _θ0 associated with a current value of the registration parameter 0. Note that, taking into account the candidate value selection algorithm, precision value σ _θn associated with the selected candidate value is equal to the first precision value σ _θ1 described above.

More precisely, substep 158 comprises the comparison of the precision value σ _θn associated with the selected candidate value with the precision value σ _θo associated with the current value of the adjustment parameter 0 increased by a proportional time drift value to the time elapsed between the determination of the selected candidate value and the determination of the current value of the heading adjustment parameter 0. This time drift value is typically equal to (t _n - t ₀ ) xb, where: t _n is a instant representative of the determination instants {t _k }k taken into consideration for determining the selected candidate value, t ₀ is an instant representative of the determination instants {t _k }k taken into consideration for determining the current value of the parameter heading adjustment 0, and b is a predefined constant representing a typical bias value of the gyrometer 40.

Each of the instants t ₀ , t _n is for example constituted by the average of the determination instants {t _k }k taken into consideration for the determination of the candidate value selected, respectively for the determination of the current value of the heading adjustment parameter 0. Alternatively, each of the instants t ₀ , t _n is for example constituted by the most recent determination instant t _k taken into consideration for the determination of the selected candidate value, respectively for determining the current value of the heading adjustment parameter 0.

In the case where substep 158 is implemented for the first time since the start of the dead reckoning navigation system 22, the precision value σ _θ0 associated with the current value of the adjustment parameter 0 is preferably infinite .

Sub-step 158 is followed by a sub-step 160 of determining a future value of the adjustment parameter 0 as a function of the result of the comparison 158. This future value is typically a function of the candidate value and the current value .

For example, if the precision value σ _θn associated with the selected candidate value is greater than or equal to the precision value σ _θ0 associated with the current value increased by the temporal drift value, that is to say if the following inequality is verified: σ _θn >

, then the future value is equal to the current value, and if on the other hand the precision value σ _θn associated with the selected candidate value is strictly less than the precision value σ _θ0 associated with the current value increased by the temporal drift value , that is, if the following inequality is verified: σ _θn < σ _θ0 + (t _n - t ₀ ) xb, then the future value is equal to the selected candidate value.

Alternatively, the future value is equal to a combination of the selected candidate value and the current value depending on the ratio between the precision value σ _θn associated with the selected candidate value and the precision value σ _θ0 associated with the increased current value of the temporal drift value, typically by application of a Kalman filter or a Bayesian fusion. For example the future value is equal to

0 _n is the selected candidate value, σ _θn is the precision value associated with said selected candidate value, 0o is the current value of the heading adjustment parameter 0, and σ _θo is the precision value associated with said current value.

This sub-step 160 concludes step 124 of deducing the heading adjustment parameter 0.

Returning to Figure 5, step 124 is followed by a step 126 of adjusting the evaluated heading. During this step 126, the dead reckoning navigation system 22 adjusts the estimated heading by applying the heading adjustment parameter

This step 126 concludes the heading adjustment step 107.

Returning to Figure A, the steps of resetting in position 106 and resetting in heading 107 are followed by a step 109 of calculating a position of the pedestrian 12 by the dead reckoning navigation system 22. During this step 109, the dead reckoning navigation system 22 applies the heading and position adjustment parameters to determine the position of the pedestrian 12 in the predetermined benchmark. This position is determined by the following formula:

where: is a position of the pedestrian 12 in the predetermined landmark calculated by the dead reckoning navigation system 22, v(t) is the position of the pedestrian 12 in the arbitrary landmark estimated by the dead reckoning navigation system 22, θ is the heading adjustment parameter,

R(θ) ^T is the rotation matrix representative of the modification of the orientation by application of the inverse of the heading adjustment parameter, and Δ is the position adjustment parameter.

The method 100 then loops to step 109 so as to allow continuous updating of the calculated position x(t).

In parallel, the method 100 returns to step 104, so as to allow continuous updating of the adjustment parameters in heading 0 and in position A each time pedestrian 12 passes near the beacons 54.

Thanks to the example of implementation described above, it is thus possible to precisely follow, in a simple and economical manner, the movement of people inside a building. This objective is in fact achieved thanks to the particularly light infrastructure 18 which simply needs to be deployed and the particularly simple location boxes 16 with which the people to be tracked only need to be equipped. The motion sensors 30 equipping these boxes 16 do not need to be very precise since the dead reckoning navigation system can be reset regularly each time a person passes near the infrastructure 18.

In particular, the use of UWB technology for the relative positioning system 24 is particularly advantageous because it allows, thanks to the low level of error of UWB localization, to obtain very precise registration for a small range of movement. It therefore makes it possible to significantly reduce infrastructure requirements. It is also completely transparent for the pedestrian 12, who does not have to perform any special task to ensure the alignment of his location box 16.

Claims

Claims Attitude resetting method (107) for resetting an attitude provided by a dead reckoning navigation system (22), the attitude resetting method (107) comprising the following steps: estimation (116), by the dead reckoning navigation system (22), for each of a plurality of determination instants included in a movement interval during which the dead reckoning navigation system (22) moves along a movement trajectory, d 'an estimated position of the dead reckoning navigation system (22) in an arbitrary fixed reference at said instant of determination, obtaining (114), for each instant of determination, an evaluated position of the dead reckoning navigation system ( 22) said instant of determination in a predetermined fixed reference frame, said evaluated position having been evaluated by a relative positioning system (24), and deduction (124) of at least one attitude adjustment parameter by minimization of a function cost comparing the evaluated positions to the estimated positions corrected using the or each adjustment parameter. Attitude adjustment method (107) according to claim 1, in which the dead reckoning navigation system (22) is carried by a pedestrian (12), the dead reckoning navigation system system (22) being preferably attached to a foot or ankle of the pedestrian (12). Attitude adjustment method (107) according to claim 1 or 2, wherein the dead reckoning navigation system (22) comprises a motion sensor (30) for measuring a movement of the dead reckoning navigation system ( 22) and a processing unit (32) for deducing from the measured movement an attitude and a position of the dead reckoning navigation system (22). Attitude registration method (107) according to any one of the preceding claims, in which the relative positioning system (24) is chosen from: a multi-angulation system, a multi-lateration system, a system map matching system and a visual positioning system, the relative positioning system (24) preferably comprising an ultra-wideband telemetry device. Attitude resetting method (107) according to any one of the preceding claims, in which the arbitrary fixed reference and the predetermined fixed reference share a common axis, an attitude resetting parameter being constituted by a parameter, preferably a angle, modification of orientation by rotation around said common axis. Attitude adjustment method (107) according to any one of the preceding claims, in which the cost function is representative of an average geometric difference between the evaluated positions and the estimated positions after application to the evaluated or estimated positions of a geometric transformation including rotation and, preferably, translation. Attitude resetting method (107) according to any one of the preceding claims, in which the step of deducing the resetting parameter comprises the calculation (130) of a candidate value for the resetting parameter, the evaluation ( 132) of a precision value of said candidate value, comparing (158) said precision value with a previous precision value associated with a previous registration parameter, and determining (160) the registration parameter as a function of the result of the comparison (158), the registration parameter depending on the candidate value and the previous registration parameter. Attitude adjustment method (107) according to claim 7, in which the precision value is a function of uncertainties in the estimated positions and the evaluated positions and/or an average geometric difference between the evaluated positions and the estimated positions after application of the candidate value of the registration parameter. Attitude resetting method (107) according to any one of the preceding claims, in which the deduction (124) of the resetting parameter comprises the following sub-steps: a) calculation (130) of a first candidate value for the adjustment parameter by minimization of a cost function comparing the positions evaluated for N instants of determination at the positions estimated for said N instants of determination corrected by means of the adjustment parameter, b) calculation (132) of a first precision value associated with said first candidate value, c) calculation (134) d 'a second candidate value for the adjustment parameter by minimization of a cost function comparing the positions evaluated for N-1 determination instants, corresponding to said N determination instants minus the oldest determination instant, to the positions estimated for said N-1 determination instants corrected by means of the or each adjustment parameter, d) calculation (136) of a second precision value associated with said second candidate value, e) comparison (1 0) of the first and second values precision, and f) selecting (142) the first candidate value when the first precision value reflects the best precision. : Attitude registration method (107) according to claim 9 in which, when the precision value reflecting the best precision is constituted by the second precision value, the deduction (124) of the registration parameter comprises the additional sub-steps following: deletion (144) of the evaluated position and the estimated position for the oldest determination moment, and repetition of substeps a) to e) with a number N reduced by 1. Method (100) for locating an object (12) in a predefined space (14), the object (12) carrying a dead reckoning navigation system (22), the method (100) comprising the following steps: starting (102) of the dead reckoning navigation system (22), attitude adjustment (107) of the dead reckoning navigation system (22) using a relative positioning system (24) comprising an infrastructure (18) installed at an access point (19) to the predefined space (14), so as to obtain an attitude adjustment parameter, said attitude adjustment (107) implementing a method of attitude resetting according to any one of the preceding claims, position resetting (106) of the dead reckoning navigation system (22) using a relative positioning system (24) comprising an infrastructure (18) installed at said access point (19) to the predefined space (14), so as to obtain a position adjustment parameter, and calculation (109), by the dead reckoning navigation system (22), at means of the attitude adjustment parameter and the position adjustment parameter, of a calculated position of the dead reckoning navigation system (22) in the predetermined reference frame. Location method (100) according to claim 11, in which the infrastructure (18) is on board a vehicle itself equipped with a location and orientation system making it possible to calculate the position of the infrastructure (18) in the predetermined mark. Dead reckoning navigation system (22) comprising a motion sensor (30) for measuring a movement of the dead reckoning navigation system (22) and a processing unit (32) for deducing an attitude and an attitude from the measured movement. position of the dead reckoning navigation system (22) in a fixed reference frame, the processing unit being configured to implement an attitude adjustment method (107) according to any one of claims 1 to 10 to realign said attitude. Computer program product comprising code instructions for executing an attitude registration method (107) according to any one of claims 1 to 10 when said program is executed by a processor. Storage means readable by computer equipment on which is recorded a computer program product comprising code instructions for the execution of an attitude adjustment method (107) according to any one of claims 1 to 10.