Granted Patent B2

US 12,631,455 · App. 17/796,937 · Granted May 19, 2026

Inventors: Paul Chauchat (Moissy-Cramayel, FR); Axel Barrau (Moissy-Cramayel, FR); Silvère Bonnabel (Noumea, NC)

Assignees: SAFRAN; LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS—A.R.M.I.N.E.S.

G01C21/165

Abstract

Claims (64)

1 . A computer implemented method of navigation assistance for a mobile carrier including an inertial navigation unit including at least one inertial sensor, wherein, the following steps are implemented by an estimation unit of the inertial navigation unit, over a determined observation window:

acquiring a kinetic model and/or of measurements by at least one inertial sensor ( 12 ), a navigation state comprises at least position, speed, acceleration, orientation of the mobile carrier;

parameterizing a non-linear system configured to estimate a navigation state of the mobile carrier over a given time interval at an iteration n as a function of the kinetic model and/or of measurements acquired, the non-linear system estimates a trajectory of the mobile carrier;

linearizing said non-linear system for expressing the navigation state at the iteration n as a function of the state at an iteration n−1 and of a correction to this navigation state, said system being initialized by a first a priori state;

determining a first correction of a navigation state at the iteration n, by combining a Kalman filtering of the non-linear system to a stochastic cloning of the non-linear system,;

wherein the stochastic cloning consists in duplicating the past states of the non-linear system to future states of the non-linear system;

estimating a second correction of the navigation state at the iteration n by an iterative information filter running backwards and stochastic cloning;

determining a third correction by fusion of the first and second corrections; and

outputting the third correction which is used to control the correcting of the navigation state at the iteration n as a function of the third correction, said corrected state being used at an iteration n+1 as being the navigation state for this iteration n+1, the corrected navigation state including the correction of at least the orientation and the position or the orientation and the speed of the mobile carrier, and thus controlling the correction of the trajectory of the mobile carrier.

2 . The computer implemented method as claimed claim 1 , wherein

the step of determining the first correction is done over successive timesteps, one timestep comprising steps of:

propagation of a preceding navigation state of the carrier into a propagated state as a function of a kinetic model and/or of measurements acquired by the at least one inertial sensor,

updating of the propagated state as a function of measurements acquired by the at least one additional sensor,

the step of estimating the second correction is done over successive timesteps, and includes, for a timestep the steps of:

back-propagating a correction of a posterior navigation state of the carrier into a correction of the back-propagated state as a function of a kinetic model and/or of measurements acquired by the at least one inertial sensor,

updating of the correction of a back-propagated state as a function of measurements acquired by the at least one additional sensor.

3 . The computer implemented method as claimed in claim 2 , wherein,

for estimating the first correction, the first correction of the navigation state propagated by the Kalman filter includes a clone of a correction of the navigation state earlier than the correction of the propagated navigation state, if correction of an earlier navigation state is involved in a relative measurement of a state correction later than a correction of the propagated navigation state; and wherein

for estimating the second correction, the second correction of the navigation state back-propagated by the information filter running backwards includes a clone of a navigation state correction later than a correction of the back-propagated navigation state, if correction of a later navigation state is involved in a relative measurement of a state correction earlier than a correction of the propagated navigation state.

4 . The computer implemented method as claimed in claim 1 , wherein the non-linear system configured to estimate the navigation state is expressed as follows:

X

⋆

=

arg

⁢

min

X

⁢

∑

k



ψ

k

(

X

)



P

k

2

,

where ψ k are cost functions associated with the measurements of each inertial sensor, P k the covariance matrix associated with the k-th measurement, that is an uncertainty that is associated therewith, the notation



e



P

k

2

=

e

T

⁢

P

k

-

1

⁢

e

represents a Euclidian norm, e, weighted by an inverse of the matrix P k .

5 . An inertial navigation unit of a mobile carrier comprising:

an interface for receiving inertial measurements acquired by at least one inertial sensor,

an interface for receiving additional measurements acquired by at least one additional sensor,

an estimation unit as claimed in claim 1 for estimating the navigation state of the unit on the basis of measurements acquired by the interface for receiving inertial measurements and the interface for receiving additional measurements.

6 . A non-transitory computer program product comprising code instructions which, when executed by a processor, cause the processor to perform the method according to claim 1 .

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (58)