Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1992.07a
- /
- Pages.305-307
- /
- 1992
Identification of Noise Covariance by using Innovation Correlation Test
이노베이션 상관관계 테스트를 이용한 잡음인식
Abstract
This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics
Keywords
- Square Root Kalman Filter;
- Linear Quadratic Control;
- Extended Recursive Least Squares;
- Auto Regressive Moving-average Model;
- Correlation test;
- Model Reference control