채널 추정기를 위한 칼만필터의 파라미터 설정치 최적화에 대한 연구

A Study on Parameter Optimization of Kalman Filter for Channel Estimator

This paper deals with the initial value problem of Kalman filter in environment of time varying noise variance. Due to its rapid convergence rate and low steady state error properties, Kalman Filter is widely used as a fast acquisition algorithm in high speed channel estimation. But the wrong initial values of measurement noise variance R(0) and state prediction error variance Q(0) degrade the performance especially in time varying noise environment. In order to overcome this weakness there need to modify these variances to proper values expected with time elapse and we introduced a empirical study on an algorithm to realize that modification process. The simulation result shows the estimated measurement noise variance follows the abrupt change in variance of R(n) within 250 symbol times and the estimation error for R(n) converges very small amounts.