Invariant particle filtering
    1.
    发明授权

    公开(公告)号:US10379224B2

    公开(公告)日:2019-08-13

    申请号:US15324255

    申请日:2015-07-09

    IPC分类号: G01S19/37 G01S19/49

    摘要: A method for estimating the state of a moving system, using a particle filter. The method implements on one reference particle an estimation of the state and includes a first set of variables and a second set of variables. A random mutation, by the particle filter, of the first set of variables is performed followed by parameterization of an extended Kalman filter using the mutated first set of variables. The Kalman filter produces a new particle using the second set of variables and data measured by at least one sensor. The second set of variables includes at least the variables: orientation, speed and position of the moving system. The Kalman filter is configured assuming that the pair of variables orientation and position has a property of invariance upon a rotation or translation and their orientation and speed has a property of invariance on application of a rotation or translation.

    METHOD FOR TRACKING THE NAVIGATION OF A MOBILE CARRIER WITH AN EXTENDED KALMAN FILTER

    公开(公告)号:US20180095159A1

    公开(公告)日:2018-04-05

    申请号:US15563262

    申请日:2016-04-01

    摘要: The invention proposes a method for tracking the navigation of a mobile carrier, in which an extended Kalman filter estimates, over successive iterations, a navigation state of the carrier, one iteration of the filter comprising steps of: propagating a previous navigation state of the carrier into a propagated state according to a kinematic model and/or measurements acquired by at least one inertial sensor, updating the propagated state according to measurements acquired by at least one navigation sensor, in which, for at least one navigation variable of the carrier contained in the propagated state, the updating comprises sub-steps of: calculating a linear correction term from an innovation representative of a difference between the measurements acquired by the navigation sensor and the propagated state, calculating an exponential of the linear correction in terms of a Lie group, calculating a first correction term expressed in a reference frame that is fixed relative to the carrier, the first correction term depending on said exponential, calculating a second correction term expressed in an inertial reference frame in which the carrier is mobile, by changing the reference frame applied to the first correction term, and adding the second correction term to the value of the variable contained in the propagated state, the state containing the result of this addition being used as the output state of the iteration.

    INVARIANT PARTICLE FILTERING
    5.
    发明申请

    公开(公告)号:US20170160399A1

    公开(公告)日:2017-06-08

    申请号:US15324255

    申请日:2015-07-09

    IPC分类号: G01S19/37 G01S19/49

    CPC分类号: G01S19/37 G01S19/49

    摘要: A method is provided for estimating the state of a moving system, the method using a particle filter and comprising the following steps implemented on one reference particle among a plurality of previously calculated particles, the reference particle providing an estimation of the state and comprising a first set of variables and a second set of variables: random mutation (101), by the particle filter, of the first set of variables into a mutated first set of variables; parameterization (102) of an extended Kalman filter using the mutated first set of variables; and implementation (103) of the parameterized extended Kalman filter to produce a new particle by way of the second set of variables and data measured by at least one sensor, the method being characterized in that the extended Kalman filter is an invariant extended Kalman filter, and in that the second set of variables comprises at least the variables: orientation, speed and position of the moving system, the invariant extended Kalman filter being configured assuming that: the pair of variables orientation and position has a property of invariance on application of a rotation or translation to said pair, and that the pair of variables orientation and speed has a properly of invariance on application of a rotation or translation to said pair.