JP2008236270A5

JP2008236270A5 -

Info

Publication number: JP2008236270A5
Application number: JP2007071688A
Authority: JP
Filing date: 2007-03-19
Publication date: 2010-05-06
Anticipated expiration: 2027-03-19

Claims

A noise suppression device that estimates the desired information only from observation information in which noise is mixed in the desired information,
Obtaining means for obtaining the observation information;
Using only a Kalman filter and extracting the desired information by removing the noise from the acquired observation information, and
The Kalman filter is
It is configured not to use autoregressive model coefficients in the state equation of the state space model,
Noise suppression device.

  The extraction means includes
  A first correlation calculation unit that calculates a first correlation value matrix of an estimation error when the state quantity of the system at time n + 1 including the desired information is estimated from information up to time n with respect to observation information only at time n When,
  For observation information only at time n, using the first correlation value matrix of the estimation error calculated by the first correlation calculation unit, optimal estimation of the state quantity at that time by information up to time n + 1 A weighting coefficient matrix for defining the relationship between the value vector, the optimum estimated value vector of the state quantity at time n + 1 based on the information up to time n, and the estimated error vector of the observed quantity including the observation information is calculated. A weighting factor calculation unit;
  A first optimum estimated value calculating unit for calculating a first optimum estimated value vector of the state quantity at time n + 1 based on information up to time n with respect to observation information only at time n;
  For the observation information only at time n, using the weighting coefficient matrix calculated by the weighting coefficient calculation unit, calculate a second optimal estimated value vector of the state quantity at the time based on information up to time n + 1. A second optimum estimated value calculation unit;
  A second correlation calculation unit that calculates a second correlation value matrix of an estimation error when the state quantity at the time is estimated from information up to time n + 1 with respect to observation information only at time n;
,
  The noise suppression device according to claim 1, comprising:

  The first correlation calculation unit includes:
  Using a predetermined state transition matrix, an element value of covariance of a given drive source vector, and a second correlation value matrix of the estimation error given or previously calculated by the second correlation calculation unit, Calculate the first correlation value matrix of the estimation error,
  The weight coefficient calculation unit includes:
  Calculation of the weighting coefficient matrix using a first correlation value matrix of the estimation error calculated by the first correlation calculation unit, a given observation transition matrix, and a covariance scalar quantity of a given noise vector And
  The first optimal estimated value calculation unit includes:
  Using the state transition matrix and the second optimum estimated value vector of the state quantity given or previously calculated by the second optimum estimated value calculating unit, the first optimum estimated value vector of the state quantity Perform the calculation
  The second optimum estimated value calculation unit includes:
  The first optimal estimated value vector of the state quantity calculated by the first optimal estimated value calculating unit, the weighting coefficient matrix calculated by the weighting coefficient calculating unit, the observation transition matrix, and the observed amount only at time n + 1 To calculate a second optimal estimated value vector of the state quantity,
  The second correlation calculation unit includes:
  Using the weight coefficient matrix calculated by the weight coefficient calculation unit, the observation transition matrix, and the first correlation value matrix of the estimation error calculated by the first correlation calculation unit, the second estimation error is calculated. Calculate the correlation value matrix,
  The noise suppression device according to claim 2.

A noise suppression method for estimating the desired information only from observation information in which noise is mixed in the desired information,
An acquisition step of acquiring the observation information;
Using only a Kalman filter and extracting the desired information by removing the noise from the acquired observation information, and
The Kalman filter is
It is configured not to use autoregressive model coefficients in the state equation of the state space model,
Noise suppression method.

  The extraction step includes
  A first correlation calculation step of calculating a first correlation value matrix of an estimation error when the state quantity of the system at time n + 1 including the desired information is estimated from information up to time n with respect to observation information only at time n When,
  For the observation information only at time n, using the first correlation value matrix of the estimation error calculated in the first correlation calculation step, the optimum estimated value of the state quantity at that time by the information up to time n + 1 A weight for calculating a weight coefficient matrix for defining a relationship between a vector, an optimal estimated value vector of the state quantity at time n + 1 based on information up to time n, and an estimated error vector of the observed quantity including the observation information Coefficient calculation step;
  A first optimal estimated value calculating step of calculating a first optimal estimated value vector of the state quantity at time n + 1 based on information up to time n with respect to observation information only at time n;
  For the observation information only at time n, the second optimal estimated value vector of the state quantity at the time according to the information up to time n + 1 is calculated using the weight coefficient matrix calculated in the weight coefficient calculation step. 2 optimal estimated value calculation steps;
  A second correlation calculation step of calculating a second correlation value matrix of an estimation error when the state quantity at the time is estimated from information up to time n + 1 with respect to observation information only at time n;
,
  The noise suppression method according to claim 4, comprising:

  The first correlation calculation step includes:
  The estimation is performed using a predetermined state transition matrix, a covariance element value of a given drive source vector, and a second correlation value matrix of the estimation error given or previously calculated in the second correlation calculation step. Calculate the first correlation value matrix of error,
  The weighting factor calculating step includes
  The weighting coefficient matrix is calculated using the first correlation value matrix of the estimation error calculated in the first correlation calculation step, the given observation transition matrix, and the scalar quantity of the covariance of the given noise vector. Done
  The first optimum estimated value calculating step includes:
  Calculation of the first optimum estimated value vector of the state quantity using the state transition matrix and the second optimum estimated value vector of the state quantity given or previously calculated in the second optimum estimated value calculating step And
  The second optimum estimated value calculating step includes:
  The first optimal estimated value vector of the state quantity calculated in the first optimal estimated value calculating step, the weighting coefficient matrix calculated in the weighting coefficient calculating step, the observation transition matrix, and the observed amount only at time n + 1 are used. Calculating a second optimal estimated value vector of the state quantity,
  The second correlation calculation step includes:
  A second correlation value of the estimation error using the weighting coefficient matrix calculated in the weighting coefficient calculation step, the observation transition matrix, and a first correlation value matrix of the estimation error calculated in the first correlation calculation step. Calculate the matrix,
  The noise suppression method according to claim 5.

A noise suppression program for estimating the desired information only from observation information in which noise is mixed in the desired information,
On the computer,
An acquisition step of acquiring the observation information;
An extraction step for extracting the desired information by removing the noise from the obtained observation information using only the Kalman filter, and the Kalman filter is configured not to use the coefficient of the autoregressive model in the state equation of the state space model Being
The noise suppression program in order to run.

  The extraction step includes
  A first correlation calculation step of calculating a first correlation value matrix of an estimation error when the state quantity of the system at time n + 1 including the desired information is estimated from information up to time n with respect to observation information only at time n When,
  For the observation information only at time n, using the first correlation value matrix of the estimation error calculated in the first correlation calculation step, the optimum estimated value of the state quantity at that time by the information up to time n + 1 A weight for calculating a weight coefficient matrix for defining a relationship between a vector, an optimal estimated value vector of the state quantity at time n + 1 based on information up to time n, and an estimated error vector of the observed quantity including the observation information Coefficient calculation step;
  A first optimal estimated value calculating step of calculating a first optimal estimated value vector of the state quantity at time n + 1 based on information up to time n with respect to observation information only at time n;
  For the observation information only at time n, the second optimal estimated value vector of the state quantity at the time according to the information up to time n + 1 is calculated using the weight coefficient matrix calculated in the weight coefficient calculation step. 2 optimal estimated value calculation steps;
  A second correlation calculation step of calculating a second correlation value matrix of an estimation error when the state quantity at the time is estimated from information up to time n + 1 with respect to observation information only at time n;
,
  The noise suppression program according to claim 7.

  The first correlation calculation step includes:
  The estimation is performed using a predetermined state transition matrix, a covariance element value of a given drive source vector, and a second correlation value matrix of the estimation error given or previously calculated in the second correlation calculation step. Calculate the first correlation value matrix of error,
  The weighting factor calculating step includes
  The weighting coefficient matrix is calculated using the first correlation value matrix of the estimation error calculated in the first correlation calculation step, the given observation transition matrix, and the scalar quantity of the covariance of the given noise vector. Done
  The first optimum estimated value calculating step includes:
  Calculation of the first optimum estimated value vector of the state quantity using the state transition matrix and the second optimum estimated value vector of the state quantity given or previously calculated in the second optimum estimated value calculating step And
  The second optimum estimated value calculating step includes:
  Using the first optimal estimated value vector of the state quantity calculated in the first optimal estimated value calculating step, the weighting coefficient matrix calculated in the weighting coefficient calculating step, the observation transition matrix, and the observed amount only at time n + 1. Calculating a second optimal estimated value vector of the state quantity,
  The second correlation calculation step includes:
  A second correlation value of the estimation error using the weighting coefficient matrix calculated in the weighting coefficient calculation step, the observation transition matrix, and a first correlation value matrix of the estimation error calculated in the first correlation calculation step. Calculate the matrix,
  The noise suppression program according to claim 8.