kalman filter algorithm 中文意思是什麼
kalman filter algorithm
解釋
卡門濾波法-
Because it is impossible to adjust the air bearing absolutely balance, the difference between mass center and rotation center must lead to a notable gravity disturbance torque. in the process of identification, modeling and identification of gravity disturbance torque is considered, and an extended kalman filter is educed for identifying air bearing inertia matrix and gravity disturbance torque, and then the algorithm is validated
由於氣浮臺平衡調試方法和手段的限制，實驗過程中氣浮臺質心與轉動中心有一定的位置偏差，必將導致較大的重力干擾力矩，在辨識演算法的推導過程中，重點考慮了重力干擾力矩的建模和參數辨識問題，推導了氣浮臺的轉動慣量和重力干擾力矩辨識的擴展卡爾曼濾波演算法，並對演算法進行了數學模擬和全物理模擬驗證。 -
The human motion tracking section discusses the use of combined algorithm to prevent kalman filter from diverge, while to estimate the motion state of human in image sequence accurately. when people mutually occlude forming group and then split, the algorithm in this paper matches human based on their color feature, resolves the problem to match human before forming group and after group splitting, and achieves satisfied results
在單獨人體融合成人群然後人群再分裂成單獨人體的情況下，本文的演算法利用人體的顏色特徵進行人體之間的匹配，解決了融合成人群前的人體與人群分裂后的人體之間的對應問題，並在人體運動跟蹤中取得了滿意的效果。 -
In this paper, the main research works are as follows : 1 ) survey and analysis previous work in auv navigation and summarize : as the cumulate error, the dead - reckoning and inertial navigation systems ca n ' t be used without other modified system ; the acoustic navigation system is used only in small range, and is very expensive. 2 ) two important approaches in geophysical navigation techniques are summarized, one is terrain contour based navigation, this approach is investigated keystone today ; the other is image based navigation, due to no perfect image sensors and image seabed map, this approach has seldom been practised. 3 ) two important terrain contour based navigation algorithms has been applied to auv, one is match algorithm - based terrain contour match ( tercom ) ; the other is kalman filter - based sandia inertia terrain - aided navigation ( sitan )
主要研究內容包括：一、總結分析了當前水下導航的常用方法和不足之處，指出基於航位推算的導航方法，存在著最大的問題就是導航誤差的積累問題，如果沒有修正系統，這種方法很難滿足使用要求；其次指出基於聲學的導航方法，造價昂貴，導航范圍有限，難以滿足自主水下航行器大范圍導航的需求；二、總結了當前水下地形輔助導航的主要技術路線，一是基於地形高程的匹配方法，這是當前研究的重點；二是基於地形圖像的匹配方法，由於缺乏良好的圖像傳感器，和可用的海底圖像地圖，目前這種方法還有待研究發展；三、將兩種地形高程匹配的常用方法應用到自主水下航行器上：以相關演算法為前提的地形輪廓匹配（ tercom ）方法和以卡爾曼濾波為基礎的桑迪亞慣性地形輔助導航（ sitan ）方法，前者演算法簡單可靠，但是導航精度不高，後者雖然精度比較高，但存在著演算法較為復雜、有可能發散和出現奇異值等問題。 -
Combining kalman filter with fuzzy algorithm, the paper also develops a method for tracking moving targets at a long rang
此外，本文將kalman濾波與模糊演算法相結合提出了一種小目標跟蹤演算法。 -
Kalman filter is an optimal filter algorithm in the minimum - mean - square - error sense, meanwhile extended kalman filter is a sub - optimal filter algorithm, which derived from the linearization of nonlinear system using taylor expansion. while the non - linearity of the system is not extreme strong, ekf can achieve approximately optimal filter effect
Kf是最小均方意義下的最優濾波演算法， ekf則是利用一階泰勒展開將非線性系統線性化而得到的一種次優濾波演算法，在非線性不是特別嚴重的情況下， ekf有著近似最優的濾波效果。 -
The unscented kalman filter is used to estimate the probe position, velocity and un - model acceleration, which improves the orbit estimation accuracy and ensures the stability of navigation algorithm
數學模擬結果表明，提出的導航方法是可行的，能夠滿足月球探測器奔月與繞月軌道段導航精度的要求。 -
And in this foundation, unified the kalman filter to make the improvement to the carrier recover algorithm, enhanced the synchronous system performance
並在此基礎上，結合卡爾曼濾波器對載波同步演算法作了改進，提高同步系統性能。 -
La dead reckoning algorithm has been developed based on the doppler velocity log ( dvl ) and fiber optic gyrocompass. 2. since the basic kalman filter will become lapsed, strong tracking filter theory has been inducted, and a new strong adaptive kalman filter algorithm has been developed. further more an adjust gene has been imported, and gets a new arithmetic
針對傳統的卡爾曼濾波演算法中由於噪聲統計特性未知而容易引起的濾波發散的缺點，引入強跟蹤濾波理論，提出了帶次優漸消因子的擴展卡爾曼濾波演算法，並進一步對該演算法進行改善，加入了調整因子，使濾波演算法得到較好的改善。 -
Firstly, the inversion of the ground motion with the unknown parameters and limited measurements was studied by the sub - structural identification, and the least - square algorithm of unknown input was built. secondly, based on the estimated input, structural parameter down to the element level was identified in time domain by extended kalman filter algorithm. several cases of a 6 - story frame s
首先，使用子結構識別技術，研究了未知參數、觀測不完整條件下的地震動輸入反演問題，建立了未知輸入的最小二乘估計演算法；其次，在估計地震動輸入的基礎上，使用廣義kalman濾波器方法，識別全部單元結構參數。 -
Thirdly, the theory of single radar multi - target tracking ( kalman filter algorithm, dynamic target model, track ' s origination and expiration, the form of tracking - door and association algorithm ) is dicussed, which is turned the basis of multi - radar centralized - system ' s tracking algorithm
對單雷達的多目標跟蹤理論（卡爾曼濾波、機動目標模型、航跡起始與終結、跟蹤門的形成和互聯演算法）進行了系統的研究，以此作為點跡處理之後集中式多雷達系統跟蹤技術的基礎。 -
A weighted global iteration parametric kalman filter algorithm
一類加權全局迭代參數卡爾曼濾波演算法 -
In this dissertation, the research trends for the problem have been introduced ; the ‘ dim ’ and ‘ point ’ has been strictly defined in mathematics from machine vision and human vision ; the ideal clutter suppression system based on clutter predication and the realization and evaluation of evaluation index has been studied, in succession the clutter suppression technologies have been researched. firstly, the classic nonparametric algorithm has been analyzed in detail and systematically, for it ’ s weakness that it cannot remove the non - stationary clutter ideally, kalman filter algorithm for clutter suppression in 2d image signal has been built. secondly, fast adaptive kalman filter is presented based on fast wide - sense stationary areas partition algorithm : limited combination and division algorithm based on quarti - tree algorithm, new taxis filter route algorithm which can break through the limitation of the necessity of pixel neighborhood of 2d filter and laplace data model with two parameters which is perfectly suitable for the residual image of kalman clutter suppression
首先分析了經典的非參數法，對於四種具有代表性的核，從前述的三個性能評價方面做了分析和對比，指出了其速度快的優點和對非平穩圖像適應性差的弱點，針對非參數法的弱點，重點研究了對非平穩圖像適應良好的卡爾曼雜波抑制技術:建立了非平穩圖像的類自回歸模型，在此基礎上建立了二維卡爾曼濾波基礎的兩個方程:狀態方程和測量方程;建立了非平穩圖像準平穩區域快速劃分演算法:基於四叉樹法的有限分裂合併演算法;二維空間的基於k排序的濾波路線演算法，突破了空域濾波路線上區域相鄰的限制;在這些研究的基礎上實現了快速卡爾曼估計，實驗驗證了該方法相對逐點卡爾曼估計可以提高運算速度三倍左右;雜波抑制結果表明傳統的高斯性檢驗並不適合卡爾曼估計后的殘余圖像，由此建立了殘余圖像的雙參數拉普拉斯模型，實驗表明其可以完好的吻合殘余圖像的概率密度曲線。 -
In this paper, a aero - engine performance tracking filter is designed by kalman filter algorithm. the filter estimate the ecdp ( engine component deviation parameters ) which reflect the deterioration of engine and the variation between engines. the estimate parameters are used to tune the embedded model to make the model consistent with the engine which respect
本文利用卡爾曼濾波原理設計了發動機性能跟蹤濾波器，對反映發動機性能退化和不同發動機之間性能差異的部件性能偏離參數（ ecdp ， enginecomponentdeviationparameters ）進行估計，用估計值修正機載模型，通過修正後的模型計算發動機性能參數的變化。 -
In order to acquire 3d spatial position and motion parameters of moving target, the limitation of second focus method to get the depth of target is analyzed according to perspective projection model of target centroid. then, the constraint for obtaining 3d position and motion parameters of moving target centroid from monocular image sequence is presented and proved in this paper. with this constraint, a nonlinear extended kalman filter algorithm for estimating 3d spatial position and motion parameters of moving target centroid from monocular image sequence is proposed
進一步，為獲取目標的空間位置和運動參數等三維信息，在目標和成像系統都運動的情況下，根據目標質心的透視投影成像模型，首先分析了二次成像法獲取目標深度信息的缺陷；然後給出了由單目序列圖像獲取目標質心的空間位置和運動參數的條件，並提出利用多幀單目序列圖像和應用非線性擴展卡爾曼濾波演算法來估計目標質心的空間位置和運動參數；最後對提出的估計方法進行了多組模擬驗證，證明該方法可行有效。 -
On the other hand, extended kalman filter algorithm ( ekl ) comes into being by the way of improving kalman filter
另外對常規kalman濾波演算法進行改進，提出推廣kalman濾波演算法。 -
Generally speaking, the algorithm of terrain contour matching is adapted to be used in cruise missiles which made fight path prior for that this algorithm is not a real - time system for it makes use of historical terrain data. while kalman filter algorithm is a real - time, rapid calculation system. which is appropriate for pilot or pilotless aircraft
得出，地形輪廓匹配演算法使用歷史地形數據，實時性差，比較適合事先規劃好航跡的導彈使用：卡爾曼濾波的方法有較好的實時性，計算速度快，很適合有人無人駕駛飛機的機動飛行要求；小波分層只是對地形信息做了高低頻分解，其本質還是相似性度量演算法，但它有效的降低了匹配演算法的計算量。 -
Vehicle reference speed determination using adaptive kalman filter algorithm
基於自適應卡爾曼濾波演算法確定汽車參考車速 -
The satisfied experimental results prove that extended kalman filter algorithm can real time estimate rotor speed and flux very accurately, and based on which the speed sensorless drive system has good static and dynamic performance
證明擴展卡爾曼濾波演算法對磁鏈和轉速的實時估計是非常準確的，由此構成的無速度傳感器系統具有良好的靜、動態性能。 -
Meanwhile we research - ? filter, kalman filter and extend kalman filter. based on the requirement of gbr simulation system, we adopt extend kalman filter algorithm of ballistic missile model
對當前常用的濾波演算法- ?濾波器、 kalman濾波器以及推廣kalman演算法進行了研究，並結合本模擬系統的特點，選擇了使用彈道導彈模型的推廣kalman濾波演算法。 -
Use the traditional kalman filter algorithm and optimal linear fusion theory to export the centralized and the decentralized algorithm, then, analyze the strongpoint and the defect of various structures. 2
在經典kalman濾波估計理論的基礎上，利用最優線性融合理論，分別給出了集中式kalman濾波及各種分散式kalman濾波的演算法，並分析了各種演算法的優缺點。
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