For large errors introduced by nonlinear state - space model in passive locating and tracking problems , various suboptimal recursive filtering algorithms are aralyzed and summarized , such as the extended kalman filtering ( ekf ) , the modified gain extended kalman filtering ( mgekf ) , the second order filtering and the adaptive extended kalman filtering ( aekf ) 摘要針對被動定位跟蹤中狀態空間模型非線性程度較高所引發的濾波精度偏低的問題,分析和總結了已有的包括推廣卡爾曼濾波( ekf ) 、修正增益的推廣卡曼濾波( mgekf ) 、二階濾波、自適應推廣卡爾受濾波( aekf )等各種次優遞推濾波算法的特點。
2 . the real - time processing technique of strong ground motion data is studied in this paper . based on the research of kanamori etc . , the relation between the design parameters of recursive filter and its corresponding low frequency cut - off frequency is obtained and quantitative phase adjustment is analyzed 本文在kanamori等人研究工作的基礎上,發展了一套強震觀測數據的實時處理技術,分析了遞歸濾波器設計參數q與所對應的低頻截止頻率f _ c以及相位校正的定量關系。
In signal processing, a recursive filter is a type of filter which re-uses one or more of its outputs as an input. This feedback typically results in an unending impulse response (commonly referred to as infinite impulse response (IIR)), characterised by either exponentially growing, decaying, or sinusoidal signal output components.