隨機觀測誤差 的英文怎麼說
中文拼音 [suíjīguāncèwùchā]
隨機觀測誤差
英文
random observational errors- 隨 : Ⅰ動詞1 （跟; 跟隨） follow 2 （順從） comply with; adapt to 3 （任憑; 由著） let （sb do as he li...
- 機 : machineengine
- 觀 : 觀名詞1. （道教的廟宇） taoist temple2. （姓氏） a surname
- 測 : 動詞1. （測量） survey; fathom; measure 2. （測度; 推測） conjecture; infer
- 誤 : Ⅰ名詞（錯誤） mistake; error Ⅱ動詞1 （弄錯） mistake; misunderstand 2 （耽誤） miss 3 （使受損害...
- 差 : 差Ⅰ名詞1 （不相同; 不相合） difference; dissimilarity 2 （差錯） mistake 3 [數學] （差數） differ...
- 隨機 : random stochasticrandom
- 觀測 : observe; observation; viewing
- 誤差 : error
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The influence of observational error on statistical inference is discussed and the method to diminish the impact of stochastic error is given
摘要討論了觀測誤差對某些統計推斷的影響，給出了減小隨機誤差影響的方法。By analyzing the inter - satellite measurement net of walker constellation at some time in geometry and numeric, the correction of system error and random error caused by the change of orbit elements using different type of estimation of inter - satellite measurement net was provided quantitatively
並通過對walker星座某一時刻的星間觀測網進行幾何分析和數值分析，定量給出了利用不同類型的星間觀測網對軌道根數變化引起的系統誤差和隨機誤差的修正情況。One dimension river flow roughness parameter inverse analysis kalman filter is introduced into the model to solve stochastic error in observed data. applying kalman filter automatism revising system, dynamic roughness course is obtained. using dynamic roughness course the model result precision is improved, it is more consistent with observed data
對於一維河道糙率參數反分析，針對觀測資料存在的隨機誤差，引進卡爾曼濾波器的自動校正系統，求解出河道糙率變化的動態過程，使用動態糙率計算，明顯改善模型的模擬精度，使模擬過程和觀測過程很好吻合。Kalman filtering is widely used for data processing in kinematic gps positioning, while the practical application of kalman filtering requires the dynamic model ( functional model ) and the stochastic model to be reliable and accurate, yet it is difficult to maintain regular motion of the object in actual kinematic positioning, thus model biases are usually generated
摘要動態定位的數據處理中廣泛應用卡爾曼濾波，而卡爾曼濾波的應用要求動態模型（函數模型）和隨機模型可靠和切合實際，但實際測量定位中難以保證觀測對象的規則運動，因而容易出現模型誤差。Simulations show that this method is effective. observability analysis and error analysis are also given. in chapter three, ambiguity elimination for phase difference measurement data is discussed
本章還針對該無源定位問題進行了可觀測性分析和單次定位隨機誤差分析，給出了分析結果。分享友人