state space filtering 中文意思是什麼
state space filtering
解釋
狀態空間濾波-
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演算法的特點。 -
The twelve kinds of modes and equivalent circuits within one high frequency switching period are carefully analyses. by using the state - space averaging approach, the converter ' s averaging model is presented, the output characteristic curve and design criterion of key circuit parameters such as output voltage, filtering inductance, common conduction time, uni - polarity spwm waveform ' s duty cycle etc are given
詳細分析了這類變換器在一個高頻開關周期內的十二個工作模式及其等效電路。採用狀態空間平均法建立了變換器平均模型，獲得了輸出電壓、濾波電感電流、共同導通時間、單極性spwm波占空比等關鍵電路參數的設計準則和變換器的外特性曲線。 -
The deducing of the algorithms has very practical value in state estimation for systems under the complex environments. in the instance of complicated multi - channel system with multiplicative noise, the dissertation discusses the optimal estimation of state filtering and smoothing and the stochastic input signal with the technique of innovation and projection theorem of hilbert space. the main study of the dissertation is introduced as follows : 1 according to the practical requirement of complicated multi - channel system with multiplicative noise, the dissertation broadens rajasekaran filtering algorithm
本文針對復雜多通道帶乘性噪聲系統，應用新息的方法和hilbert空間的投影定理，對狀態最優濾波和平滑估計、隨機輸入信號的最優估計等理論與應用方面的問題，進行了進一步的探討，著重完成了以下工作：第一，根據復雜多通道乘性噪聲系統問題的實際需要，推廣了rajasekaran濾波演算法。 -
By augmenting the state vector, linearizing the nonlinear augmented state space model and adopting the equivalent measurement equation, the problem of strong tracking extended kalman filtering of nonlinear systems with additive combined colored noise can be converted into the problem of strong tracking kalman filtering of linear systems with correlated process and measurement noise
通過增廣狀態向量、線性化非線性的增廣狀態空間模型和採用等效量測方程，將加性復合有色噪聲干擾下非線性系統的強跟蹤濾波問題轉化為過程與量測噪聲相關情況下線性系統的強跟蹤卡爾曼濾波問題。 -
Compared with kalman filtering, the unknown definite disturbance with finite energy instead of white noise drives the state - space system in h filtering. compared with the time - variant filter and the first - order filter, h filter has preferable robustness
與kalman濾波相比， h _濾波採用未知的具有有限能量的確定性干擾代替白噪聲驅動狀態空間系統；與時變濾波器和一階濾波器相比， h _濾波器具有較強的魯棒性。 -
Recently, withthe rapid improvement of performance of digital processor, sequential monte carlo ( smc ) method has a wide range of application in engineering, especially in signal processing, statistics, and econometrics etc. the time varying systems can be stated in the form of a dynamic state space model. for linear models and gaussian noise, the kalman filter provides analytical expressions for posterior filtering
一般的時變系統都可以被看作是一動態狀態空間模型，對于線性高斯模型，卡爾曼濾波可以給出后驗密度函數的解析解；而對于非線性非高斯模型，我們則無法得到它的解析解，在這種情況下則可以使用序列蒙特卡羅方法來對其進行近似。 -
This paper presents and probes into several filtering schemes for the deep space explores attitude measurement system composed of star sensors and gyros. under the stellar - inertial modes, two attitude determination algorithms are designed which use the extended kalman filter. one of the algorithms is to linearized the state equation based on the optimal estimation
本文中以星敏感器和光纖陀螺為基本配置組成的深空探測器姿態測量系統為對象，針對星敏感器與光纖陀螺聯合定姿模式和基於星敏感器的定姿模式，對深空探測器的三軸姿態濾波技術方案進行了設計與研究。
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