動態噪聲特性未知系統的多模型自適應卡爾曼濾波

Multiple model adaptive Kalman filter for the system without the knowledge of process noise

摘要: 針對常規自適應卡爾曼濾波器存在過渡過程差的問題,基于一個給定的指標切換函數,采用多個基于不同動態噪聲協方差矩陣的卡爾曼濾波器和一個常規自適應卡爾曼濾波器共同組成多模型自適應卡爾曼濾波器.與常規自適應卡爾曼濾波器相比,多模型自適應卡爾曼濾波器可以在保持原有自適應濾波器性能的基礎上極大地改善瞬態響應.

Abstract: To solve the bad transient response of a conventional adaptive Kalman filter, multiple Kalman filters based on different noise covariances and a conventional adaptive Kalman filter (AKF) were used to form a multiple model adaptive Kalman filter (MMAKF) by using a switching index function. Compared with a conventional AKF, the MMAKF could improve the transient response greatly without losing the characteristic of the conventional AKF.