NAME

       filter_kalman  -  Unidimensional  Kalman filter, also known as linear quadratic estimation
       (LQE)

SYNOPSIS

       loadrt filter_kalman [count=N|names=name1[,name2...]]

DESCRIPTION

       Useful for reducing input signal noise (e.g. from the voltage or temperature sensor).

       More information can be found at https://en.wikipedia.org/wiki/Kalman_filter.

       Adjusting Qr and Qk covariances:

       Default values of Rk and Qk are given for informational purpose only. The  nature  of  the
       filter requires the parameters to be individually computed.

       One  of  the  possible  and  quite  practical method (probably far from being the best) of
       estimating the Rk covariance is to  collect  the  raw  data  from  the  sensor  by  either
       asserting  the  debug  pin  or  using halscope and then compute the covariance using cov()
       function   from   Octave   package.   Ready   to   use   script   can    be    found    at
       https://github.com/dwrobel/TrivialKalmanFilter/blob/master/examples/DS18B20Test/covariance.m.

       Adjusting Qk covariance mostly depends on the required response time of the filter.  There
       is  a  relationship  between  Qk  and  response  time  of the filter that the lower the Qk
       covariance is the slower the response of the filter is.

       Common practice is also to conservatively set Rk and Qk slightly larger then computed ones
       to get robustness.

FUNCTIONS

       filter-kalman.N (requires a floating-point thread)
              Update xk-out based on zk input.

PINS

       filter-kalman.N.debug bit in (default: FALSE)
              When asserted, prints out measured and estimated values.

       filter-kalman.N.passthrough bit in (default: FALSE)
              When asserted, copies measured value into estimated value.

       filter-kalman.N.reset bit in (default: FALSE)
              When  asserted,  resets  filter  to its initial state and returns 0 as an estimated
              value (reset pin has higher priority than passthrough pin).

       filter-kalman.N.zk float in
              Measured value.

       filter-kalman.N.xk-out float out
              Estimated value.

PARAMETERS

       filter-kalman.N.Rk float rw (default: 1.17549e-38)
              Estimation of the noise covariances (process).

       filter-kalman.N.Qk float rw (default: 1.17549e-38)
              Estimation of the noise covariances (observation).

AUTHOR

       Dmian Wrobel <dwrobel@ertelnet.rybnik.pl>

LICENSE

       GPL-2.0-or-later