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

       Dmian Wrobel <dwrobel@ertelnet.rybnik.pl>

       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.

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

       GPL-2.0-or-later

LinuxCNC Documentation                             2025-08-07                                   FILTER_KALMAN(9)

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

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).

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.

loadrtfilter_kalman[count=N|names=name1[,name2...]]