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environment with known indicators.\n\n\n```r\nclutterKF(nobs, ssw, ssv, yy, ii)\n```\n\n## Arguments\n\n- `nobs`: the number of observations.\n- `ssw`: the standard deviation in the state equation.\n- `ssv`: the standard deviation for the observation noise.\n- `yy`: the data.\n- `ii`: the indicators.\n\n## Returns\n\nThe function returns a list with the following components: - **xhat**: the fitted location.\n\n- **shat**: the fitted speed.\n\n\n\n## Examples\n\n```r\nnobs <- 100; pd <- 0.95; ssw <- 0.1; ssv <- 0.5;\nxx0 <- 0; ss0 <- 0.1; nyy <- 50;\nyrange <- c(-80,80); xdim <- 2; ydim <- nyy;\nsimu <- simuTargetClutter(nobs,pd,ssw,ssv,xx0,ss0,nyy,yrange)\noutKF <- clutterKF(nobs,ssw,ssv,simu$yy,simu$ii)\n```\n\n## References\n\nTsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. 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