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强跟踪滤波在动基座传递对准中的应用
引用本文:彭赛锋,吴峻,程向红. 强跟踪滤波在动基座传递对准中的应用[J]. 舰船电子工程, 2011, 31(4): 69-72,84
作者姓名:彭赛锋  吴峻  程向红
作者单位:东南大学仪器科学与工程学院,南京,210096
基金项目:“十一五”总装备部预研项目(编号:51309050402)资助
摘    要:在保证捷联惯性导航系统(SINS)动基座传递对准具有一定精度的前提下,为了缩短传递对准的时间,对强跟踪滤波(STF)在动基座传递对准中的应用进行了研究。通过在一步预测方差P(k+1|k)中引入渐消因子λ(k+1),以此减弱老数据对当前滤波值的影响。同时,对渐消因子λ(k+1)的计算做出修正,使得状态估计更加平滑。最后,在匀速拐弯的机动方式下进行了仿真,结果表明强跟踪滤波在对准精度与速度上比Kalman滤波有更好的表现。

关 键 词:捷联惯性导航系统  动基座  传递对准  强跟踪滤波  Kalman滤波

Application of Strong Tracking Filter in Moving Base Transfer Alignment
Peng Saifeng,Wu Jun,Cheng Xianghong. Application of Strong Tracking Filter in Moving Base Transfer Alignment[J]. Ship Electronic Engineering, 2011, 31(4): 69-72,84
Authors:Peng Saifeng  Wu Jun  Cheng Xianghong
Affiliation:Peng Saifeng Wu Jun Cheng Xianghong (School of Instrument Science and Engineering,Southeast University,Nanjing 210096)
Abstract:On the premise of assuring certain precision and shortening alignment time,strong tracking filter(STF) applied in transfer alignment of strapdown inertial navigation systems(SINS) on moving base is approached in this paper.To reduce the impact of old data on current filter values,the STF algorithm adjusts the one step prediction error covariance matrix P(k+1|k) by modifying the introduced fading factor λ(k+1) and makes the state estimation smoother.Simulation results show that the STF could obtain higher alignment rapidity and accuracy than Kalman Filter.
Keywords:SINS  moving base  transfer alignment  STF  Kalman filter  
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