multiple target tracking 中文意思是什麼
multiple target tracking
解釋
多目標跟蹤-
Mulitisensor target tracking is the intersectional technique of multiple subjects. it has gained popularity over past decades with the advent of vigorous sponsorship in many areas
近年來，隨著傳感器技術、計算機技術、通信技術和信息處理技術的發展，特別是軍事上的迫切需求，多傳感器目標跟蹤技術的研究內容日益深入和廣泛。 -
Influence of tracking gate upon multiple target tracking system
跟蹤門對多目標跟蹤系統性能的影響 -
In this paper, there are presented that a single stationary station single target passive bearings - only tracking and data association algorithm and a simplified single stationary station multiple target passive bearing - only tracking and data association algorithm, then a single stationary station multiple target tracking problem can be regarded as a single stationary station single target tracking problem. 3. based on least square method, this paper presents the line - of - sight location method of multiple stationary station single target
針對實際無源探測網路中存在同一探測區域內只布置了一個無源聲音探測傳感器站的情況，給出了一種單靜止站單目標無源純方位定位與跟蹤的演算法，提出了一種簡單的單靜止站多目標無源純方位定位與跟蹤的演算法，從而將單靜止站多目標問題轉化為單靜止站單目標問題。 -
Multiple target tracking system concludes data association algorithm and data filtering algorithm
多目標跟蹤系統包含了數據互連演算法和數據濾波演算法。 -
Interacting multiple model algorithm in target tracking
激光器與軌道的相對位置對動態加熱的影響 -
The fuzzy probabilistic data association of multiple targets tracking is presented in this paper, which define a target ? uzzy set on the measurement set at time k and then use fuzzy least mean square error method to estimate target states
給出了一種多目標跟蹤的模糊概率數據關聯方法，該方法在k時刻的回波集上定義一個目標模糊集，表示回波與目標之間的模糊關系。然後基於目標模糊集，利用模糊最小均方誤差估計方法對目標狀態作出估計。 -
In the last chapter, interacting multiple mode ( imm ) algorithm is provided as a candidate solution for tracking of a target with occurrence of maneuvers
由於雷達站在不同時間段里可能採用不同的機動方式，這就產生了目標運動狀態切換的問題。 -
4. finally, a peak extraction method is proposed for further improving the separability between the local peak cell and its neighbors in multiple target tracking. the simulation of multiple track initiation shows its feasibility and effectiveness
給出了一種峰值提取演算法，並在航跡起始中，將採用該演算法與不採用該演算法的航跡起始結果進行了比較，驗證了該演算法的可行性和有效性。 -
The methods of data association and tracking beginning and ending to single and multiple targets tracking in the multi - echo environment is listed. at the end of the thesis, a method is introduced, which is that based on the most closed principle, without the chosen echo, the current forecasting values added yawp based upon the former state values is considered as the target state estimated value. the value is an input of observation equation, the output of the observation equation is considered a chosen echo. and the method is validated in the simulation results
針對多目標跟蹤問題，首先對多目標跟蹤的原理和跟蹤門的形成方法進行了概述，並對多回波環境下單目標跟蹤和多目標跟蹤的常用的數據關聯方法和跟蹤起始、跟蹤終結方法進行了介紹，在本文的後半部分，對多目標的運動狀態進行了模擬研究，提出了一種目標狀態估計方法，該種方法的思想是當前時刻如果目標跟蹤門內沒有所期望的候選回波，首先計算出目標在前一時刻的運動狀態下對當前時刻的預測值，並將該值疊加上系統噪聲作為量測方程輸入值，然後將觀測值作為候選回波對目標進行狀態估計。 -
Considering the time delay of sound transfer, a least square line - of - sight location method is presented in this paper. 4. filtration matrix is developed to make the problem of multiple target tracking in net can be regarded as a problem of multisensor - multitarget tracking in a same region
利用最小二乘理論，研究了多靜止站單目標無源純方位定位方法，給出了多靜止站單目標的視線交叉定位演算法，同時針對聲音傳播的延時特性，提出了處理具有延時特性的最小二乘迭代視線交叉定位演算法。 -
The degrees of membership obtained from fuzzy clustering are considered as the probabilities of association events, which are later used as the weighted numbers to obtain the innovation of each target. the full - rate tracking of target using multi - rate interacting multiple models is realized. the maneuvering target tracking algorithms are analyzed, which conclude the current statistical model adaptive kalman filtering and interacting multiple models algorithms
新演算法借鑒了概率數據關聯演算法的思想，把模糊均值聚類后得到的隸屬度值視為相應關聯事件的概率，並將其作為加權系數對目標有效回波的新息量進行加權得到該目標的總新息量。 -
4. we review variable structure multiple model ( vs - mm ) ground target tracking method, and analyze the algorithm systematically
進一步研究了變結構多模型濾波器對地跟蹤問題，並對其進行了理論分析和模擬。 -
For a target to multiple measurements, we consider the case of small target tracking by using an imaging sensor
對一個目標對應多個量測的情景，考慮了利用成像傳感器對小目標的跟蹤情況。 -
By processing the observed data sequences of target position using the fuzzy imm approach based on current statistics model, the proposed method integrates multiple filtering and predicted values of target state from different trackers using the adaptive weighting fusion approach based on total least - squares error rule, which improves the precision and robustness of tracking system
該方法在對各跟蹤器輸出的目標位置測量值序列採用基於「當前」統計模型的模糊交互多模方法進行處理的基礎上，採用基於總均方誤差最小規則的自適應加權融合方法對目標狀態的多個濾波與預測值進行綜合處理，較大程度上提高了系統的跟蹤精度與穩定性。 -
Applications of multiple - model smoothing algorithms for maneuvering target tracking are studied via simulation, some important conclusions are obtained. based on model - set sequential likelihood ratio, an enhanced agimm, in which model - set adaptation is implemented by jointly utilizing model posterior probability and predication probability, is proposed, simulation results indicate that improvements of both dynamic and steady state tracking performance are achieved with the enhanced algorithm
模擬研究了多模型平滑演算法在機動目標跟蹤中的應用；利用模型集合序貫似然比檢驗，提出了一種綜合利用模型后驗概率和預測概率實現模型集合自適應的綜合格自適應多模型演算法，模擬實驗表明演算法有效改善了動態跟蹤精度和穩態跟蹤性能。 -
In this paper, we describe the study background, meaning and methods of passive acoustic detective network, summarize the basic theories and methods of target tracking and data association, analyze some tipical data association algorithms include the nearest neighbor algorithm ( nn ), probabilistic data association filtering ( pdaf ), joint probabilistic data association filtering ( jpdaf ), multiple hypothesis tracking ( mht ), and multidimensional s - d assignment algorithm. 2. in detective network, sometimes a surveillance region have only single sensor
從整體上描述了無源聲音探測網路的研究背景、意義、基本框架和研究方法，概述了目標跟蹤與數據關聯的基本理論與方法，重點分析了幾種典型的數據關聯方法，包括最近鄰方法、概率數據關聯濾波器（ pdaf ） 、聯合概率數據關聯濾波器（ jpdaf ） 、多假設跟蹤（ mht ）以及多維s - d分配演算法。
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