×

Particle sampling method and sensor fusion and filtering method

  • US 7,379,844 B2
  • Filed: 02/15/2006
  • Issued: 05/27/2008
  • Est. Priority Date: 02/17/2005
  • Status: Expired due to Fees
First Claim
Patent Images

1. A particle sampling method for sampling particles in order to filter ambiguous data or information on at least one state variable of a system using the particles, characterized in thatsampling is carried out in consideration of the influence of the non-linearity of system dynamic model, observation model and/or other system constraints, on the probability distribution of state variables, and the particle sampling method comprises the steps of:

  • when the sampling performed on a constraint manifold in a hyper space of an arbitrary model equation at regular intervals, where a constraint manifold represents a system dynamic model and/or other system constraints defined in the hyper space of current and previous state variables, wherein the hyper space of an arbitrary model equation at regular intervals is defined as “

    Uniform Sampling on Constraint Manifold,”

    previously performing the sampling in the hyper space from numerous sample meeting an equation for the system model at regular intervals, and obtaining particles of a previous state variable and a current state variable;

    when an interval divided uniformly on an axis of the previous state variable is defined as a bucket, finding a weight of each particle of the current state variable estimated through a weight allocated by the particles of the previous state variable and prior probability information of the previous state variable and through a number of the particles existing in the bucket;

    finding a prior probability distribution of a current state estimated from the estimated weight of the sampled particles of the current state variable and from the estimated weight of each particle of the current state variable; and

    previously performing the sampling in the geometrical space from the numerous samples meeting an equation for the observation model at regular intervals, and obtaining the particles of the previous state variable and particles of an observation variable.

View all claims
  • 1 Assignment
Timeline View
Assignment View
    ×
    ×