bearing tracking 中文意思是什麼
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Tracking performance is bad to anti - jamming and unstable in cartesian coordinate using ekf because of the bearing - only problem existing in the ir sensor
由於紅外傳感器只能獲得角測量信息，在直角坐標系下子跟蹤系統不穩定，抗干擾能力差。 -
The own ship maneuvering trajectory equations and optimal trajectory of bearing - only systems locating and tracking
純方位系統定位與跟蹤的本載體最優軌線方程及其最優軌線 -
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。 -
Bearing - only tracking ( bot ) is a typical question pertaining to target motion analysis ( tma )
無源唯方位跟蹤（ bearing - onlytracking ）技術是目標運動分析（ tma ）中一類典型問題。 -
Observability of maneuvering target passive tracking with bearing and doppler measurements
基於方位角和多普勒的機動目標無源定位跟蹤可觀測條件 -
Estimates of bearing and elevation and the standard deviations of the measurements, which are monopulse processing ' s results in ecm, are given. the measurements of simulation is the basis of processing tracking algorithm
通過建立相控陣雷達的模擬模型，給出了ecm存在時單脈沖測角的目標的測量角度和誤差方差。觀測模型的建立為目標演算法的進行奠定了基礎。 -
On robust state estimation algorithm for bearing - only tracking
魯棒跟蹤演算法研究 -
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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