The field of the invention is the measurement of the position and orientation of a mobile body M, which moves in translation and rotation relative to a reference mark connected to a fixed or mobile structure P relative to an inertial reference frame type fixed reference mark. In particular, the invention concerns the determination of the position and orientation (P/O) of the helmet of a pilot in the reference mark of the aircraft, P/O from which the angular position of an external target is determined in said same mark by sight through a system including the helmet-mounted display of the pilot. In a known manner, the pilot superimposes on the external target the image of a collimated cross projected on the transparent visor thereof, and acquires the measurement taken by the device by pressing on a push-button.
More specifically, concerning the devices for determining the P/O called trackers of magnetic technology, the main problem of determining the position and orientation of a mobile body relative to a reference mark connected to a fixed or mobile structure having to be accurately determined comes from an electromagnetic environment significantly disturbed by radiated magnetic fields (EMI for Electromagnetic Interferences, ECI for Eddy Current Interferences or fields due to Eddy currents) and/or magnetic fields induced by ferromagnetic bodies (FMI for FerroMagnetic Interferences), environments such as the cockpits of aircraft and more specifically of helicopters, surgical operating rooms, etc. Thus, the accuracy is significantly degraded in the presence of said interferences. Therefore, the problem consists of finding the means to improve the performances despite the disturbances.
U.S. Pat. No. 7,640,106 is known in prior art describing an apparatus for determining the position of a selected object relative to a moving reference image, the apparatus including at least one reference frame transceiver assembly secured to the moving reference frame, at least one object transceiver assembly firmly attached to the selected object, an inertial measurement unit firmly attached to the selected object, an inertial navigation system secured to the moving reference image, and a tracking processor coupled with the object transceiver assembly, to the inertial measurement unit and to the inertial navigation system, the object transceiver assembly communicating with the reference frame transceiver assembly using magnetic fields, the inertial measurement unit producing IMU inertial measurements of motion of the selected object relative to an inertially fixed reference frame, the inertial navigation system producing INS inertial measurements of motion of the moving reference frame relative to the inertially fixed reference frame, the tracking processor receiving electromagnetic measurements resulting from the magnetic communication between the reference frame transceiver assembly and the object transceiver assembly, the tracking processor determining the position of the selected object relative to the moving reference frame by using the IMU inertial measurements and the INS inertial measurements to optimise the electromagnetic measurements.
Patent FR2807831 is also known in prior art describing a device for measuring the position and orientation of a mobile object relative to a fixed structure, in a disturbed magnetic environment, including:
Such a device includes means:
U.S. Pat. No. 5,646,525 describes another example of equipment for determining the position and orientation of a helmet worn by a crew member in a vehicle including a generator, associated with the vehicle, which produces a rotating magnetic and electric field of fixed strength, the orientation and frequency within at least a portion of the vehicle. The apparatus also includes a plurality of detectors each of which generates a signal proportional to at least one of the electric or magnetic fields at least one point associated with the helmet and calculation circuitry responsive to the signal for determining the coordinates of the at least one point relative to the generator and for determining the position and orientation of the helmet.
U.S. Pat. No. 6,400,139 also describes an example of apparatus for position/orientation tracking within a bounded volume. Said methods and said apparatus employ at least one fixed sensor, called a “witness sensor,” having a fixed position and orientation near or within the volume to account for electromagnetic distortion. One or more probe sensors are placed on an object having to be tracked within the volume, and the output of each witness sensor is used to compute the parameters of a non-real effective electromagnetic source. The parameters of the effective source are used as inputs for the computation of the position and orientation measured by each probe sensor, as if the object were in the non-distorted electromagnetic field produced by the effective source or sources. In addition to trackers for the helmet-mounted displays in aircraft, tank, and armoured-vehicle applications, the invention finds utility in any electromagnetic tracking system which might be subject to electromagnetic distortion or interference.
In general, the solutions of prior art do not teach solutions to compensate the disturbances not correlated with the transmitters (actual emitted fields).
U.S. Pat. No. 7,640,106 requires a first inertial sensor in the helmet and a second inertial sensor and an estimator (Kalman filter) for determining an orientation of an object. Said solution requires providing a sensor on the fixed platform. It aims to know the angular orientation of the helmet in the mark of the platform. Said angular orientation is determined through incorporation of the estimated relative velocity. Said relative velocity is obtained by measuring the difference between:
Said solution therefore requires a double inertial system, doubling the noise and the errors.
Furthermore, said solution does not take into account the strong electromagnetic disturbances observed in a real cell, for example, a helicopter or aeroplane cell.
Furthermore, said solution requires an estimation to be carried out of the angular velocity.
The solution taught by the U.S. Pat. No. 6,400,139 on the interpolation of data coming from a plurality of sensors in view of creating a model of the fields sent by real sources, and modelling unknown or dummy sources to compensate the Eddy current disturbances. Said solution consists of installing a plurality of fixed witness sensors in the vicinity of the volume in which the mobile body moves, in order to construct a model of the field measured by said witness sensors. Said model is used for recomputing by interpolation the field measured by the sensor positioned on the mobile object. Same does not make it possible to compensate the disturbance fields of Eddy currents.
Nor does same make it possible to process the disturbances of radiated and non-correlated disturbances (EMI), but only the ECI type disturbances correlated with the emitted radiative field.
All of the solutions of prior art require the use of an additional inertial platform, to determine an additional mark in addition to the reference system provided by the inertial system of the aircraft; which complicates the implementation and the errors.
The aim of the invention concerns a system as stated by claim 1, aiming to remedy the disadvantages of prior art and to establish a method and produce a process for eliminating electromagnetic disturbances (ECI: Eddy currents, FMI: induced ferromagnetism) in real time without requiring the very expensive need to map the effective volume scanned by the sensor.
Another aim of the invention is to improve the signal-to-noise S/N ratio of the P/O detector for obtaining the required performances in environments significantly disturbed by EMI (for example, in aircraft and more specifically in helicopters: radiated fields created by on-board generators and on-board equipment). The signal-to-noise S/N ratio may be expressed as the ratio between the standard deviation of the signal Sc received by the sensor in “free space”, i.e. without any electromagnetic disturbance and the standard deviation of the noise B, the noise being the sum of all of the signals not coming directly from the transmitter (inductive field).
The purpose of the invention is to achieve an improvement of the S/N ratio in the order of 1000 for the most critical cases (helicopters).
A third aim of the invention is to compensate the latency of the output information through hybridisation with an inertial system.
By referring to
In the invention which will subsequently be described in more detail, the currents injected into the windings that create the inductions, are preferably simultaneous. The measured inductions are therefore the sum of the fields emitted at instant t and the fields present in the environment. Therefore, the aim of the invention is to distinguish in the measured field each component emitted by each transmission axis. Said recognition of the field emitted by one of the components constitutes demultiplexing of the inductions that can be functionally qualified by comparison with the inventions cited that either perform temporal demultiplexing (emission not simultaneous but sequenced over time) or frequential demultiplexing (detection of frequencies in the spectral range). When the fields are demultiplexed, it is considered that three independent emissions were received on three sensor axes.
As regards the hybrid system, the principle of the invention consists of using the attitude provided by the magnetic tracker means expressed in the fixed inertial frame to reset or initialise the computation of the attitude of the IMU gyrometric sensors obtained by incorporation into the inertial frame of a dynamic equation for predicting a quaternion. The attitude of the tracker means expressed in the inertial frame simply uses the attitude of the platform provided by the INS, in the form of three Euler angles or DCM matrix (direction cosine matrix of the platform) or of the quaternion computed from the Euler angles or DCM matrix. The dynamic prediction model, computed at high speed, is reset to time t−TL, TL being the latency time of the magnetic tracker means, at each arrival of the quaternion provided by the magnetic tracker means. The information necessary for computing the quaternion (in particular the angular velocities of the IMU of the mobile object) having been stored in memory over time TL, the quaternion prediction model is recomputed from t−TL up to the current time t by using the velocities stored in memory. Beyond t up to the next arrival of the magnetic tracker information, the quaternion is computed at the frequency for acquiring angular velocity measurements. The invention also comprises the real time correction of the triaxial angular velocity sensor by estimation of the errors of the sensor.
The present invention will be better understood upon reading the following description, concerning non-limiting examples of embodiments of the invention referring to the appended drawings where:
According to
The mobile body (M) is a helicopter pilot helmet, the cell of the helicopter forming the platform (P).
On the helmet (M) are attached an electromagnetic sensor (C-1) and an IMU inertial sensor (C-3-1); said two sensors are mechanically connected in a rigid manner to the helmet (M).
On the platform P are attached:
A computer (4-4) receives the signals from said various components and carries out the processes described below.
A first assembly E for transmitting magnetic induction(s), comprising a first transmitting sub-assembly E-1 of Ne, Ne being equal to at least two transmitting coils, the axes of symmetry of which, not parallel with one another, form a mark RE attached to the second object P.
A first receiving assembly C-1, attached to said mobile object M and comprising Nc>=2 non-parallel receiving coils, forming a mark RC1, sensitive to the ambient magnetic field resulting from the vector sum of the fields emitted by said first transmitting assembly E and disturbing magnetic fields generated by electric currents existing in the environment and by ferromagnetic magnetisations, said second assembly forming a sensor C-1 secured to the first mobile object M and such that the product Nc*Ne>=6, the first mobile object M has a reference mark RM. The orientation of the mark RC1 relative to the mark RM is constant and noted by RC1/M the direction cosine matrix of the axes of C-1 in RM.
The Nc components of SC form the output of said first receiving assembly C-1.
A computing processor 4 for computing the position and orientation of the first mobile object, coupled with the first analogue/digital conversion (or ADC) means 4-1 for carrying out the acquisition, at discrete times tk=k*Te, of analogue signals Sc, Xu1 and Sb according to
In a preferred embodiment, Ne=Nc=3 will be taken.
The total field BTE, three-component vector (pseudo vector), existing at the centre of the sensor is the sum of the following inductions:
{right arrow over (B)}
TE
={right arrow over (B)}
EU
+{right arrow over (B)}
EMI
+{right arrow over (B)}
ECI
+{right arrow over (B)}
FMI
+{right arrow over (B)}
Γ [1]
with
{right arrow over (B)}
EU
={right arrow over (B)}
EU1
+{right arrow over (B)}
EU2
+{right arrow over (B)}
EU3 [2]
where
BEMI is the vector of the induction radiated in the environment, for example generated by the currents circulating in the electrical equipment, by the on-board generators, by the 50-60 Hz sector, etc. Same can be modelled by the sum of periodic fields Bsc not correlated with the BEUj and fields BR which are EMI signals the characteristics of which are presumed random because they cannot be represented by deterministic signals of known or estimated characteristics.
{right arrow over (B)}
RM(tk)={right arrow over (B)}SC+{right arrow over (B)}R [3]
BECI is the induction vector at the centre of the sensor, created by the Eddy currents in the conductors situated in the environment of the P/O system, same produced by the magnetic field emitted by the transmitting antenna at the location where the conductors are found.
BFMI is the induction vector at the centre of the sensor, created by the magnetisation of ferromagnetic materials situated in the environment of the P/O system.
BT is the induction of the earth's magnetic field.
It should be noted that, according to
One of the aims of the invention is to eliminate by filtering all of the inductions so as to only keep the measured vector the model of which is expressed by BCU=[Rc/e]t(BEu1+BEu2+BEu3) where BEU1, BEU2, BEU3 are the three-component vectors of the field emitted and received at the centre of the sensor (expressed in the mark of the transmitter) and RC/E is the rotation of the sensor mark relative to the mark of the transmitter. Demultiplexing of the transmission channels is carried out (recognition of the portion of the signals that comes from the transmission channel j=1 to 3) i.e. to determine the components Bc1 Bc2, Bc3 of the sensor C-1 coming from the emission of the axes 1, 2 and 3 of the transmitter E-1 in order to form the 3×3 matrix: [Bcu]=[Bc1|Bc2|Bc3]. The method for computing the rotation of the sensor is obtained in a known manner (U.S. Pat. No. 4,287,809 Egli): knowing Bcu, an estimation of BEU is deduced by using an induction model in free space (without disturbances): RCE=BCBEU−1.
From the matrix [Rc/e], the Euler angles or the quaternion QEM, which are two representations of the attitude of the object M, are taken in a known manner.
The static and dynamic accuracy performances are obviously increasing with the S/N ratio. The increase of the S/N ratio sought is obtained in two obvious and complementary manners: increase the power (or the amplitude) of the useful signal in particular in low frequency and jointly reduce the power of the noise by filtering.
A first aim of the invention is the assembly E which includes according to
The main object of said control is to cancel out the EMI magnetic fields present in the environment which are added to the exciter field proportional to n*Ij, where Ij is the current relative to the winding j, but also to linearise the coefficient μeff because it is known that the magnetisation of magnetic materials has a non-linear magnetisation curve with saturation for the strong excitations.
From
μeff is the effective permeability if in addition in the useful band: GF>>1
with μr_eff effective relative permeability
where BEC is the induction produced at the centre of the core and μr_eff the effective relative permeability. The signal-to-noise ratio in the coreless and control-less configuration is
With core for E-1 and control E-2, it is seen that the signal-to-noise ratio is
To keep the same signal-to-noise ratio whilst keeping the same order of magnitude for BE in output, it is therefore necessary that G·F≧μr_eff. Said relation defines the minimum gain of the control chain. The corrector network of the shifted proportional type KG(1+
It is observed that if G*F>>1, the amplitudes of the harmonics are divided by the gain of the direct chain G. That said, as will be highlighted in the paragraph dealing with the modelling and filtering, the fact of measuring Xuj and of using reference signals of the induction emitted in the model of signals received, makes the filtering device insensitive to harmonics, which is a fundamental advantage relative to existing systems for which the measurement of the current in E1.1, E1.2, E1.3 is no longer the image of the induction emitted following the appearance of harmonics.
As said previously, one of the aspects of the invention consists of producing a core in order to obtain an effective relative permeability μr_eff of a few hundreds of units. The existence of cores of ferrite or of shims made of ferromagnetic alloy exists in a number of applications. Said latter used for example in transformers, must be laminated to reduce the Eddy currents which counter the magnetisation and cause losses. Ferrite, much more conductive than ferromagnetic alloys, makes it possible to use cores with uniform density of said matter obtained by sintering. In general, the cores are spherical or cubic (or even parallelepiped) according to
From the preceding relations, a formula of the induction is deduced, for the ellipsoids of which the magnetisation is uniform,
In general, μR·δ>>1, therefore
Using the preceding example of the elongated bar, this gives
Said relation is only approximate, the value of μr is in general lower because the magnetisation is not uniform. Experimentally, the exponent is between one and two. But an increase in the induction in the order of μΓ is indeed observed in the volume of the material, but also on the outside.
Therefore, the invention consists of an arrangement of permeable bars of L/D ratio chosen so that the gain in induction μr-eff=α·μr is higher than ten. The coefficient α, lower than the unit, takes into account a plurality of factors, in particular:
According to the invention, to optimise the coefficient a, very thin bars of permeable material are used, for example, wires of Mu-metal, permalloy or Vitrovac electrically isolated in advance, stored according to
Thus, according to the at least two non-parallel transmission axes, the bars are grouped (
A device consisting of producing three concentric spherical coils instead of the concentric cubic coils in
Another aspect of the invention concerns the control at zero of the quasi-static magnetisation produced by quasi static disturbances, such as for example, the earth's magnetic field. To avoid the saturation of the bars of blocks 7-3 or 7-4 in the presence of a continuous or quasi-continuous magnetisation, the symmetry of the currents circulating in the coils is detected.
A—The On-Board Processor 4:
The computing processor is coupled with the three measurement assemblies C-1, C-2, C-3 previously described in order to firstly produce at discrete times tk=k*Te the acquisition of signals on one hand by analogue/digital conversion of the second receiving assembly C-1 as well as of the third sub-assembly E.3.1 of said first transmitting assembly E, on the other hand by digital serial links of said third assembly for acquiring angular velocities C.3.1 at the frequency FEG as well as the angles of attitude of said second object M relative to the absolute fixed mark delivered by C.3.2, secondly generate and produce digital/analogue conversions by the block E.4 for providing the setpoints of the control of predetermined currents in the first transmitting assembly E, thirdly, to produce the computations of a first position/orientation from a complete model of the measured inductions the variables of which are developed from the signals acquired and some parameters of which identified by optimum filtering represent the terms proportional to a dipolar or multipolar field model of which the position and orientation of the block C-1 are extracted. The block 4.3, receives, for example, from a conventional digital serial link which communicates with the inertial system of the platform, the information dated relative to the specific clock of 4 is constituted. If necessary, this makes it possible to temporally reset the attitudes of the platform. Said block also receives the serial type digital information of the MEMS inertial sensor C-3.1.
B—Method for Extracting the Noise Reference:
If the equation [1] is used,
{right arrow over (B)}
TE
={right arrow over (B)}
EU
+{right arrow over (B)}
EMI
+{right arrow over (B)}
ECI
+{right arrow over (B)}
FMI
+{right arrow over (B)}
Γ [7]
the useful signal {right arrow over (B)}EU is linearly dependent on the signals emitted by the transmitter block E. According to
Consequently, it will be considered that the additive noise {right arrow over (B)}FMI measured in Nb points of the environment, by definition not correlated with the fields emitted estimated Xu has been noted
{right arrow over (B)}
RM(tk)={right arrow over (B)}SC+{right arrow over (B)}R [8]
The signal BRM(tk) is shown in
In some environments, such as for example aeroplanes, the noise BEMI is lower than in helicopter environments and in particular the noise BR is very low. In said type of environment, the noise may have to be extracted instead of being measured. The definition of the block 4.4 therefore enables a method for extracting the reference noise BRM(tk) in two different manners:
the frequencies ωk
As another example, two periods TOFF can be considered according to
The independent variables XC(tk)=cos(ωk
B
F
={circumflex over (B)}
EC(ic,tk)+{circumflex over (B)}RM(ic,tk) [10]
where XC(j,ki
[10] is written:
It is noted that XC(j,ki
The indexes Kic are relative to the delays of the independent variables of the model and range from 0 to Nic, said latter index Nic being defined strictly necessary in order to minimise the residual error. The offset terms of Kic form a transversal filter. BRM is written in the form of a development of complex variables:
The equations [11] and [12] which are linear relative to the parameters to be estimated.
If a model was produced for Xsc(tk) of the same type as [11] i.e. a development sum of the type [12] for each variable Xsc(tkksc·Tc), this would remain within the field of the invention. The same would apply if the complex parameters ĈSC(ic,ksc) were no longer constant but depended on the time in the form of a polynomial of the time
For said temporal model, the values of the terms Cio((icksc)·kio are computed by developing same in [12]. Any type of different temporal model no longer comprising of temporal polynomial but of sums of functions of the time of exponential type ea·t or eibt (complex periodic function i2=−l) remains within the field of the invention.
The parameters of said model are determined by a conventional method of least squares (MSE) or an equivalent recursive method (LMS, RLS). The estimation of the parameters relative to the variables Xuj may be refined by subtracting the term {circumflex over (B)}SC(ic,tk) estimated at the signal Ŝc(ic,tk). The new estimation makes it possible to estimate the correlated terms with better accuracy after one or two iterations. The reference noise {circumflex over (B)}RM is in this case the signal {circumflex over (B)}SC′ estimated in the preceding iteration.
The measurements of the additive noise BEMI are identified by the output signals Sb of the block C-2 in diagram 4. In a particular embodiment, in order to facilitate the drafting, Nb=1 will be taken and it will be considered that the measurement of a single component is sufficient. The measurement of {circumflex over (B)}RM(tk) according to a particular direction will be noted to be considered as a signal very strongly correlated with BEMI. In the ideal situation, the measured noise reference BRM contains no signal correlated to Xuj, j=l to 3. In practice, it is very difficult to arrange sensors C-2 at locations such that no component correlated with XU exists, including and in particular the signals BECI and BFMI. Therefore, the signal for measuring the noise Sb consisting of the same components as the signal Sc must be considered. Therefore, the same problem arises as in i), i.e. that the various components of the signal Sb must be identified that are written as follows:
B
C2
=B
RU
+B
RM [13-a]
with BRU=Bu+BPCU [13-b]
where BU is linearly dependent on XUj(tk), BPCU is linearly dependent on XUj(t−k·Te)
and BRM=BSC+BR [14]
is the term not correlated with XUj.
BRM is not negligible as in i) and this consists of extracting from [13-a] the portion BRM. As in the case i), all of the terms of the model must be identified to prevent biasing the estimation of the parameters of the model. However, the random signal BR is in general weaker than Bsc and Bcu, and the identification may be performed over longer times insofar as the sensors of C-2 are immobile. It can also be considered that, since the transmitter and the sensor(s) of the block C-2 are fixed on the same structure, the identification of the parameters of the model [14] may be carried out once for all or indeed at the start of use of the system during an initialisation phase of sufficient duration in order to enable very good accuracy in the estimation of the parameters following filtering of the terms of [14] which are not correlated with [14]. Said identification is exactly the same as that described in [10], [11], [12]. The parameters of [14] are therefore stored in memory for the computation of {circumflex over (B)}CU. The principle of extraction of BRM consists of writing:
{circumflex over (B)}
RM
=B
C2
−{circumflex over (B)}
RU [16-a]
where BRU are the estimates of the signals correlated with Xuj.
After the identification of the model of the type:
All of the terms of the signals correlated with Xuj are extracted therefrom to form the signal {circumflex over (B)}RU:
{circumflex over (B)}RM′ of [16-a] is therefore the estimate of the noise not correlated with the emitted fields.
It is therefore noted that when there is emission of signals by E-1, in the two embodiments i) and ii) previously described, the same model should be identified on the measurements Sc (coming from the block C-1) or Sb (coming from the block C-2).
The model of the signal to be identified within the framework of said second embodiment of the invention for which a measurement of the EMI noise is taken and of which only the BRM noise is extracted, is therefore produced.
The model of Bc is developed which is the field measured by the sensor C-1:
{right arrow over (B)}
C
=R
c/i
1({right arrow over (B)}U/E+{right arrow over (B)}CU/E+{right arrow over ({circumflex over (B)})}RM/E) [17]
In the index U/E, E indicates that the vector is expressed in the mark of the transmitter (said index is sometimes omitted by simplifications knowing that the context indicates in which mark the fields are expressed), U indicates that this is the portion of the field linearly dependent on the fields emitted by the transmitter XU. The index CU indicates that {right arrow over (B)}CU/E={right arrow over (B)}ECI+{right arrow over (B)}FMI represents the vector of the disturbances correlated with the vector XU. {right arrow over (B)}CU/E could be modelled by the convolution of {right arrow over (B)}U/E by the impulse response of the complex filter existing between the two magnitudes. {right arrow over ({circumflex over (B)})}RM/E has the same meaning as in [13] and [15], it is the noise present in the environment not correlated with the emitted fields.
BT is overlooked which is presumed to be filtered by a conventional digital filter known by the person skilled in the art. The three models are developed linearly relative to the parameters to be identified for example by a conventional square error minimisation method. When the coefficients are determined, the nine terms (3 terms due to each transmission channel for each component of the triaxial sensor C-1) are extracted relative to XU(tk) components of the matrix noted A which will be better defined subsequently. The fundamental interest of said complete modelling of the signals received by the sensor C-1 lies in the fact that the 9 parameters of A are even less biased if the independent variables of the model more accurately represent the physical phenomena.
The following three models of [17] are developed: Model {right arrow over (B)}U/E, Model {right arrow over (B)}CU/E, Model {right arrow over (B)}RMI/E:
Model {right arrow over (B)}U/E:
Consequently, it is considered that the sensor C-1 has been corrected of the errors thereof according to known methods: the functions of gain correction, misalignment, etc., are applied. Presuming that the distance between the sensor C-1 and transmitter is at least three times the largest dimension of the transmitter, it is therefore written in a known manner that the model is of dipolar type and is written
Dc/E is the distance between the centre OC of the sensor C-1 and the centre of the transmitter Oe:
O
E
{right arrow over (O)}
C
D
C/E
·{right arrow over (u)}, [19-bis]
DC/E is variable as a function of time, like the rotation RC/E(t:={right arrow over (u)}: unit vector of OE{right arrow over (O)}C expressed in the reference mark of the transmitter RE which is mechanically defined in a known manner by the person skilled in the art relatively to the mark of the platform Rp according to
P is the transfer matrix between the mark of the transmitter and the mark ({right arrow over (u)},{right arrow over (v)},{right arrow over (w)}) with {right arrow over (w)}={right arrow over (u)}M̂{right arrow over (u)} and {right arrow over (v)}={right arrow over (w)}̂{right arrow over (u)} and known as the radial mark, where {right arrow over (u)}M is the unit vector of a transmission axis. It is also shown that for example:
are the dipolar moments of the transmitting coils the amplitude of which change substantially over time according to the functions fj(t), f2(t), f3(t) imposed by the currents circulating in the coils.
m1 m2, m3 are the multiplicative terms of amplitudes of the magnetic moments that depend on the units chosen, the gains of the current amplifiers E-2, αi,βi,γi the direction coefficients (cosines) of the collinear unit vectors of the magnetic moments (axes of revolution) of the coils, f1(t), f2(t), f3(t) represent the variations of the standardised measurements proportional to the magnetic inductions emitted over time by each transmitting coil. The measurements of said emitted inductions are taken by the sensors E-3 secured to the transmitter E in
The functions {right arrow over (X)}U=[XU1,XU2,XU3]t thus digitalised, proportional to the functions f1(t), f2(t), f3(t) are therefore the images of the fields emitted by the 3 coils: by re-writing [18], if {right arrow over (x)}p is the vector {right arrow over (OEOC)}
B
C(t)=[Rc/e(t)]tB({right arrow over (x)}p)[M1XU1(t)+M2XU2(t)+M3XU3(t)]
B({right arrow over (x)}p)=[P][H][P)]t [23]
Or again if it is noted
A=[R
c/e(t)]tB({right arrow over (x)}p) [23-bis]
This gives three equations to each three unknowns, i.e. 9 terms to be identified. Measuring the three components of Bc, when there are no disturbances BCU and BRM of [17], the nine terms of {right arrow over (X)}U=[XU1,XU2,XU3]t are identified using a conventional least square method (MSE) or an equivalent recursive method (LMS, RLS).
Therefore, the matrix W is obtained which can be applied in the form of:
The two matrices, CE and KE (gains and misalignments) relative to the transmitting block E-1, are identified in the factory, therefore the matrix A sought is easily obtained.
[A]=W[CEKE]−1 [27]
Knowing A, the position {right arrow over (x)}p of the centre of the sensor in the transmitter mark and the rotation RC/E (or direction cosines of the axes of the sensor in the transmitter mark) are obtained according to the methods of prior art. Through the identification of the matrix
A consisting of the coefficients of the functions {right arrow over (X)}CU=[XU1,XU2,XU3]t, the demultiplexing of the transmitting channels was thus carried out by identification of a model, and not by temporal demultiplexing (emissions not simultaneous), or by frequential demultiplexing (U.S. Pat. No. 6,754,609 Lescourret, U.S. Pat. No. 6,172,499 ASHE, etc.) or any other demultiplexing.
MODEL {right arrow over (B)}CU/E:
As already seen, {right arrow over (B)}CU/E, may be considered as the output of a linear filter the input of which are the inductive fields emitted by El, and the output is the measurement by the sensor C-1. It is therefore still possible to consider that the output at instant tk is a linear combination of the inputs at instants tk−kl·Te. If it is noted: {right arrow over (X)}CU(tk−k1Te)=[XU1(tk=k1Te),XU2(tk−k1Te),XU3(tk−k1Te)]t, for each component ic (ic=l to 3) of the sensor C-1, the following model is formed:
In general, in the environments of cockpits, there are practically no ferromagnetic materials, the FMI effects are therefore low in particular for the high frequencies and in addition vary substantially in 1/(DP/E3DC/P3) where DP/E is the transmitter-disturber distance and DC/p the disturber-sensor C-1 distance. When it is possible to ignore same, the ECI disturbers are the only disturbers of which the model can be written as a function of the shifts of the emitted fields:
MODEL {right arrow over (B)}RM/E:
The reference noise is extracted from the signals Sb is {circumflex over ({right arrow over (B)})}RM={right arrow over (B)}C2−{circumflex over ({right arrow over (B)})}CU. If the variable is called XBR(tk)−{circumflex over ({right arrow over (B)})}RM(tk), and to take into account the transfer functions between sensors, the model of the ambient noise for each component ic of the sensor C-1: BEMI(ic,tk), may be applied in the form of a function of the variables XBR(tk−kbTe):
Complete Model:
The complete model [17] is written for each component of
The number of coefficients and the number of variables are in the number of Ne*Max/ic(N(ic)).
The nine terms of Acu(ic,j,0) are the terms of the model in free space, i.e. without disturbers.
Once all of the coefficients are estimated using a conventional least squares method (MSE) or an equivalent recursive method (LMS, RLS, KALMAN, etc.) at each transmission cycle Tobs, the terms Acu(ic,j,0) relative to the variables XUj(tk) form a 3×3 matrix identical to W of [26] and which are the coefficients of the model in free space, since same only represent the inductive fields. As indicated above the first position and orientation are deduced therefrom at instants tk from the magnetic detector insensitive to disturbances. The insensitivity to disturbances arises from the fact that the invention implements a complete model of useful signals and measured and estimated noises, a model for which the coefficients are not biased due to the completeness of the model.
The P/OEM information according to
C—Inertial and Magnetic Hybridisation
One of the aims of the invention is presented hereafter which consists of compensating the latency of a position/orientation tracker system. The example described concerns a magnetic system but would be applied to any system for detecting the orientation of a mobile body.
When the signal-to-noise ratio input from the magnetic detection system is not sufficient, either that noise exists that is not taken into account by the model or that noise is added on the sensor C-1, one method consists of increasing the number of points to further average the noise. Therefore, the latency is increased, which is relatively harmful for the piloting of aircraft. One aspect of the invention is to associate with the magnetic detection an inertial system the excellent short-term properties of which are known, i.e. a very short response time, but having long-term shifts, in particular due to bias and bias shifts. The magnetic tracker means has an excellent long-term stability but a response time related to the signal-to-noise ratio which may be insufficient in some conditions. The principle of the invention consists of associating, also called hybridising, the magnetic system and the inertial system, when the platform has an inertial unit providing the attitude of the platform at any instant within a fixed inertial reference frame.
The rotation thus computed from the initial attitude of the gyrometric sensors C-3-1 at time ti is expressed within the fixed inertial reference frame shown by the mark Ri in
The information from the IM tracker means is available at the output of 4-4 and constitutes the first orientation known as Rot (tn=n·Tobs). Said rotation is RC/EEM(tn), i.e. the rotation of the axes of the mark RM connected to the mobile object M according to
The direction cosines of the gyrometers are deduced therefrom in the inertial frame at time ti=tn by the formula:
R
g/i
EM(tn)={circumflex over (R)}P/i(tn)·RM/PEM(tn)·Rg/m [32]
where Rg/m is the constant matrix defining the direction cosines of the gyrometers in the mobile mark M. The quaternion Q(tn) is deduced from Rg/iEM(tn).
The quaternion Q(tkg=tn−kgTg) obtained by digital incorporation of the equation of the type {dot over (Q)}=F(ω)Q or in the incorporated form thereof:
With the initial condition:
{dot over (Q)}(tn)={circumflex over (Q)}i(tn) [33-b]
It will be seen that said initial conditions is the value of the state predicted by the model at tn to which is added a fraction of the error between estimated measurement and real measurement.
Where {right arrow over ({circumflex over (ω)})}={right arrow over (ω)}m−{right arrow over (δ{circumflex over (ω)})}, [33-d]
calculated from the values provided by the gyrometers and corrected of the errors of the gyrometers {right arrow over (δ{circumflex over (ω)})} estimated by an optimal estimator of the Kalman type (extended: EKF or “unscented”: UKF) or sub-optimal (“Recursive least squares” of the type LMS, RLS, etc.) according to a model of errors of the type
{right arrow over (δ{circumflex over (ω)})}={right arrow over (b)}ω+ΔK·{right arrow over ({circumflex over (ω)})} [34]
where ωb is a random bias and K the matrix of gain, misalignment and coupling errors between channels.
The propagation of gyrometric errors is carried out by a dynamic model of the terms of {right arrow over (δ{circumflex over (ω)})}, same incorporated as is known to be carried out with a KALMAN filter. By calling dQ the error between the value QiEM(tn) computed by the magnetic tracker means at time tn and Q(tn) incorporated from t to tn, the propagation state vector of the errors is for example of the type
Y=dQ+v measures [39-b]
v, Vg, Vk are superimposed additive Gaussian noises centred according to the characteristics of the fluctuations of the terms {right arrow over (b)}ω and K of [38-a and 38-b] and the error provided by the magnetic detection system.
Equations [35] to [38] may be digitally incorporated in various manners or be applied in the form of recurrent matrix equations. At each instant tn, the parameters of {right arrow over (δω)} are reset using formulas known by the person skilled in the art depending on the filter chosen, for example the KALMAN filter.
In this hypothesis, the resetting formula is of the type:
X(tn+)=X(tn−)+Kn(Y−Ŷ) [41]
If the KALMAN filter (of the standard or extended (EKF) or unscented (UKF) type is used, Kn is obtained using well-known formulas (prediction and resetting of the covariance matrix). If Kη=1, the prediction model is not trusted: resetting consists of initialising the incorporation with {circumflex over (Q)}iEM(tn). If Kn=0, the measures are not trusted which are not taken into account. Adjustment of the gain does not form part of the invention, in particular because it depends a great deal on experimental conditions (noise, quality of the sensors, etc.).
The compensation of the latency is performed in the following manner: After the resetting of the filter according to [41] at the instant tn+the equations [35] to [38] are incorporated over a time tkg−Tobs/2 up to tkg (the current time), by using the raw angular velocities stored in memory over said time interval, and corrected according to [33-d]. The initial value of Q is the value reset at A new value of tn+. A new value of {dot over (Q)}(tkg) is obtained. Then, from tkg to
at each new acquisition of {right arrow over (ω)}m, {dot over (Q)}(tkg) is computed according to the same formulas [35] to [38] up to the new resetting value Q(tn+1) date of the arrival of the new orientation of the tracker system (first orientation). Thus, the compensation has been carried out.
The direction cosine matrix Rg/i(tkg) is computed defining the attitude of the gyrometers in the fixed mark and computed from the quaternion {dot over (Q)}(tkg)=[q0 q1 q2 q3]t of [33] using the following formula:
The matrix defining the direction cosines of the mark of the mobile object M relative to the reference mark (mark of the platform RP) is then computed using the expression
R
m/p(tkg)=Rp/it(tkg)Rg/i(tkg)Rg/mt [43]
The second orientation may be defined by the Euler angles extracted from the matrix Rm/p(tkg) using formulas known by the person skilled in the art.
said method makes it possible, on one hand, to provide at very high speed (in the order of 10 times faster) the estimation of the second orientation, which minimises the delay between the provision of the information computed and the use thereof by the system which carries out the acquisition thereof at any periodicity and in a manner not synchronised with tn, and on the other hand, the compensation of the latency by the computation of the trajectory of (tkg−Tobs/2) at tkg thanks to the storing in memory and correction of the gyrometric speeds of (tkg−Tobs/2) at tkg.
The applications of the invention are mainly those for which significant accuracy is necessary for the position and orientation of a body relative to another body taken for reference in the presence of strong electromagnetic disturbances. The position and orientation of the helmet of civilian and military aircraft pilots without using magnetic maps is a first application. Numerous applications in surgery, in simulators, capture of movements and video games, etc., are possible.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1302566 | Nov 2013 | FR | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/FR2014/052843 | 11/6/2014 | WO | 00 |