채널 추정기를 위한 칼만필터의 파라미터 설정치 최적화에 대한 연구

• 영문명: A Study on Parameter Optimization of Kalman Filter for Channel Estimator
• 발행기관: 한국산업기술융합학회(구. 산업기술교육훈련학회)
• 저자명: 김선웅(Seon-Woong Kim)
• 간행물 정보: 『산업기술연구논문지』산업기술교육훈련논문지 제22권 1호, 29~34쪽, 전체 6쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2017.03.30

영문 초록

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.

목차

Ⅰ. 서 론

Ⅱ. 제안한 알고리즘의 구현 및 적용

Ⅲ. 제안한 알고리즘의 시뮬레이션

Ⅳ. 결 론

키워드

Kalman Filter(칼만필터) Measurement Noise Variance R(n)(관측잡음분산) State-Prediction Error Variance Q(n)(상태예측오차분산) Channel Estimation(채널추정)