target tracking filter 中文意思是什麼
target tracking filter
解釋
目標跟蹤濾光器-
The specific research methods are listed : 1. matched filter taking the max ouput snr as the best rule correlates nonstop divided signal and divided echo to detect low snr target signal. then all one dimension divided correlation outs and done fft in portrait to leach interferential signal such as static or low rate mussy meaves, many pathway echo and so on and to take target ' s time difference and doppler frequency that combine parameters that target ' s direction taken from antenna and so on to implement target ' s orientation and tracking
具體研究方法如下： 1 、採用以輸出信噪比最大為準則的最佳匹配濾波器來對分段的參考和目標信號作相關處理來檢測低信噪比目標信號，然後對一維分段相關輸出組作縱向傅立葉變換來濾除靜態或低速的雜波、多徑回波等干擾信號，並提取目標的時差和多普勒頻率，再結合由天線獲得的目標方向等參數，就可以實現目標的定位和跟蹤。 -
The extended kalman filter ( ekf ) and converted measurement kalman filter ( cmkf ) have been widely used in radar target tracking
在非線性量測的情況下， ekf和cmkf得到了廣泛的應用。 -
In the fourth part, the tracking filter for low - altitude radar target is studied
第四部分考慮了低空目標的雷達跟蹤濾波技術。 -
Here, the author put the emphasis on target trajectory smoothing, filter, prediction technique based on a parameterized model in multisensor target tracking system
作者在文中重點討論了用於多傳感器目標跟蹤系統的多項式最小二乘平滑、濾波和外推技術。 -
It consists of the coordinates setup and transform of the phased array radar, some filter parameters " design for low - altitude target, evim technique used in the low - altitude radar target tracking, the strategy for low - altitude radar target tracking, etc
包括相控陣雷達坐標系的建立與轉換；低空目標跟蹤有關濾波參數的考慮； imm技術在低空目標濾波中的應用；相控陣雷達的低空目標跟蹤策略等。 -
The method combining digital filter and ship - dynamic compensation is used to realize the precise motion - target tracking on the condition of ship - motion which causes the target relative motion and the results coming from real system test prove the effectiveness
針對甲板運動所造成的目標的相對運動和牽連運動，採用數字濾波與動態補償相結合的方案，實現了艦船搖擺情況下跟蹤雷達對運動目標的精確跟蹤，並經實踐驗證后裝備于某型跟蹤雷達。 -
Maneuver target tracking based on importance resampling particle filter
基於重要性重采樣粒子濾波器的機動目標跟蹤方法 -
Based on the framework of particle filter, this paper proposed and implemented different tracking algorithms for single mouse target and multi mice targets separately, which are as follows : we combined the weighted color histogram, which is considered as observation model, into the framework of particle filter and realized the tracking of single mouse target
本文在粒子濾波框架基礎上，分別就單個鼠類目標和多個鼠類目標的情況，提出和實現了不同的跟蹤演算法。具體內容如下:提出將加權的顏色直方圖作為觀察模型融入粒子濾波器演算法框架，實現了對單個鼠類目標的跟蹤。 -
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。 -
This paper studies and discusses comprehensively the applications of data processing techniques in track while scan radar. it begins with studies of filter theory and multitarget tracking theory, and continues to make deep discussion of such topics in the multitarget tracking environment as target movement models, adaptive - filtering and prediction, dynamic data association algorithms, and measured data. for radar using purpose, the data algorithms for nnf and the adaptive a - p filtering and prediction based on " cv " model are studied emphatically
論文對邊掃描邊跟蹤雷達中數據處理技術的應用作了全面的研究與討論，深入研究了符合實際的濾波理論與多目標跟蹤理論；對目標運動模型、自適應卡爾曼濾波與預測技術、各類數據關聯演算法、量測數據的處理等多目標跟蹤所涉及的主要內容進行了討論；根據實際雷達跟蹤要求，對nnf數據關聯演算法和基於「 cv 」運動模型的自適應濾波與預測演算法等作了重點研究。 -
With the development of modern science and engineering technology, the two theory systems in target tracking filter domain are formed, which are classic wiener filter using frequency domain and modern kalman filter using state space
隨著現代科學技術和工程技術的發展，目標跟蹤理論形成了經典的維納濾波（頻域法）和近代卡爾曼濾波（狀態空間法）的兩大理論體系。 -
Multi - bearings and one - range filter for bearings - only target locating and tracking
用多方位一距離濾波法解純方位定位與跟蹤問題 -
Based on multisensor target tracking system, the research of this thesis focuses on target location technique, target trajectory smoothing, filter, prediction based on a parameterized model, target tracking with nonlinear measurement, outlier detection and distributed systematic error estimate based on real - time data fusion and so on
論文以多傳感器目標跟蹤系統為背景，針對目標定位測速技術、基於參數建模技術的目標航跡平滑、濾波和外推、非線性測量系統的目標跟蹤、基於實時數據融合模型的野值剔除和分散式系統誤差估計等方面進行了深入研究。 -
In this article, converted measurement kalman filter ( cmkf ) is inferred in 3 - dimensional space. a target tracking application is simulated to compare the converted measurement kf and extended kalman filter ( ekf ). the result is that cmkf has a higher accuracy than ekf
本文在三維空間中推導了轉換坐標卡爾曼濾波演算法，用此演算法進行了雷達目標跟蹤模擬，和用推廣的卡爾曼濾波演算法進行的模擬結果進行了比較，得出轉換坐標卡爾曼濾波演算法比推廣的卡爾曼濾波演算法精度高的結論 -
The last, taking into account of the nonlinear transformation from sphere frame to cartesian frame, maneuvering target tracking is simulated by using current statistical model and converted measurement kalman filter ( cmkf ) without linearization bias in the statistical condition. the paper presents the converted measurement covariance that determines when to use the current measurements vs. the predicted state, and the simulation results are satisfied
最後，針對球坐標系與直角坐標系之間的變換是非線性變換的特點，哈爾濱工程大學博士學位論文運用統計條件下不存在線性化誤差的轉換測量卡爾曼濾波演算法，結合「當前」機動模型對機動目標進行了模擬研究。 -
Concerning the problem of low accuracy and speed of filter in bearings - only target tracking, the algorithm of underwater bearings - only passive target motion analysis is improved from ekf to maekf
摘要針對純方位被動目標跟蹤中擴展卡爾曼濾波器容易發散，從而導致濾波精度差而且收斂速度慢的問題，文中將水下純方位被動目標運動分析中的擴展卡爾曼濾波演算法改進為衰減記憶卡爾曼濾波演算法。 -
With the rapid development of modern computer science and information technology, and with the marvelous renovation of image identification, mtt comes out into the open and is of great practical value in the field of military defence, medical research, traffic monitoring, astronomical prediction, intelligent supervision etc. particle filter, as a nonlinear filtering based on bayesian estimate, has an advantage in the field of nonlinear moving target tracking
隨著現代計算機和信息技術的飛速發展及圖形識別演算法的革命性改進，多目標的實時追蹤技術脫穎而出，在軍事國防、交通監視、天文預測、智能監控等領域有著非常重要的實用價值。粒子濾波作為一種基於貝葉斯估計的非線性濾波演算法，在處理非線性運動目標跟蹤問題方面有獨到的優勢。 -
The new filter algorithm obtained is easily realized in the tws system, which can be applied to maneuver target tracking. then the third and the forth chapter discussed tracks association and tracks quality management. at last i simulated the tracking algorithm
同時在前人的研究的基礎上給出了，航跡質量的估計方法，提出了工程實用性強、通用性好、又可分析的多參數計分累計的可分析試航跡質量管理鏈。 -
In the fifth part we describe the procedure of amalgamating target and put emphasis on the research of target tracking method, by building up the moving status of target we can solve the problem of occultation. - - filter is adopted to predict next position of target so we can reduce the range of seeking matched target
在跟蹤過程中，著重針對多個運動目標遮掩的情況，設計了基於運動狀態的識別和跟蹤方法，並利用常系數的kalman濾波器對運動目標的位置進行預測，解決了目標遮擋情況下的識別和跟蹤問題。 -
The nonlinear problem is inevitable in bearing - only target tracking problem. here the monte carlo based nonlinear filters are compared with the classical extended kalman filter ( ekf ) in this field : the unscented kalman filter ( ukf ), the particle filter ( pf ) and the unscented particle filter ( upf ). furthermore, a multi - sensor passive tracking algorithm, through combining the ukf and probability data association ( pda ), is provided for bearing - only target tracking in dense clutters
本文將典型的montecarlo非線性濾波器? unscentedkalmanfilter （ ukf ） 、 particlefilter （ pf ）和unscentedparticlefilter （ upf ）應用於被動定位跟蹤，並在二維空間目標跟蹤模擬中與經典的擴展卡爾曼濾波演算法（ ekf ）進行了對比；本文將ukf演算法與概率數據關聯演算法（ pda ）相結合，給出了適用於雜波環境下多站被動式跟蹤的ukfpda演算法。
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