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| 基于UKF的海底集矿车组合导航研究 | |
| 引用本文： | 朱洪前,胡豁生,桂卫华.基于UKF的海底集矿车组合导航研究[J].中国矿业大学学报,2010,39(2). |
| 作者姓名： | 朱洪前 胡豁生 桂卫华 |
| 作者单位： | 1. 中南大学信息科学与工程学院,湖南,长沙,410083;中南林业科技大学物流学院,湖南,长沙,410004 2. 中南大学信息科学与工程学院,湖南,长沙,410083;艾塞克斯大学计算机科学与电子工程学院,艾塞克斯,柯彻斯特,CO4 3SQ 3. 中南大学信息科学与工程学院,湖南,长沙,410083 |
| 基金项目： | 国务院大洋专项科技攻关项目，国家自然科学基金 |
| 摘 要： | 针对扩展卡尔曼滤波(EKF)在海底集矿车组合导航系统应用时存在着计算复杂、线性化误差大等问题,基于附加打滑参数的履带车运动学模型,将无色卡尔曼滤波(UKF)用于集矿车长基线声学导航(LBL)与推算导航(DR)的组合导航系统中.考虑到测量数据时延,组合导航系统融合LBL与DR信息,得到海底集矿车位置估计.研究结果表明:采用EKF方法,测量数据时延0,0.5,2s时,东向定位精度为0.14,0.32,0.48m,北向定位精度为0.13,0.28,0.44m;采用UKF方法,测量数据时延0,0.5,2s时,东向定位精度为0.10,0.26,0.37m,北向定位精度为0.09,0.24,0.34m.测量数据时延越短,EKF,UKF的位置估计效果都会越好.但与EKF方法相比,UKF方法能够明显减少组合导航系统的线性化误差,提高海底集矿车导航系统的精度与稳定性. |
| 关 键 词： | 海底集矿车 非线性 卡尔曼滤波 组合导航 |
Unscented Kalman Filter Based Integrated Navigation of a Deep-Sea Mining Vehicle |
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| ZHU Hong-qian,HU Huo-sheng,GUI Wei-hua.Unscented Kalman Filter Based Integrated Navigation of a Deep-Sea Mining Vehicle[J].Journal of China University of Mining & Technology,2010,39(2). | |
| Authors: | ZHU Hong-qian HU Huo-sheng GUI Wei-hua |
| Affiliation: | ZHU Hong-qian1,2,HU Huo-sheng1,3,GUI Wei-hua1(1. School of Information Science & Engineering,Central South University,Changsha,Hunan 410083,China,2. School of Logistics,Central South University of Foresty , Technology,Hunan 410004,3. School of Computer Science & Electronic Engineering,University of Essex,Colchester,Essex CO4 3SQ,U.K.) |
| Abstract: | Since there are some problems for an extended Kalman filter (EKF) to be deployed in an integrated deep-sea navigation system,including model errors caused by linearization and its complicated computation,the unscented Kalman filter (UKF) was introduced for the position estimation of a deep-sea mining vehicle based on a kinematic model in presence of sliding parameters. Taking into account the influence of measurement delays,the proposed navigation system fused both long-base line (LBL) data and the dead rec... |
| Keywords: | deep-sea mining vehicle nonlinear Kalman filter integrated navigation |
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