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DVL/RPM Based Velocity Filter Aiding in the Underwater Vehicle Integrated Inertial Navigation System
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作者 Tae Suk Yoo 《Journal of Sensor Technology》 2014年第3期154-164,共11页
The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Vel... The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment. 展开更多
关键词 IMU (inertial Measurement Unit) KALMAN FILTER VKF (Velocity KALMAN Filter)
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IMU/DGPS辅助车载CCD及激光扫描仪三维数据采集与建模 被引量:32
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作者 陈允芳 叶泽田 +2 位作者 谢彩香 石波 王贵宾 《测绘科学》 CSCD 北大核心 2006年第5期91-92,77,共3页
三维信息快速采集是真实场景建模与三维虚拟现实技术的关键。本文提出了一种基于激光扫描仪、线/面阵CCD相机及GPS与IMU等多种传感器融合的车载移动式数据快速采集系统。各传感器安置在车内稳定平台上并随车保持一致的运动姿态。通过对... 三维信息快速采集是真实场景建模与三维虚拟现实技术的关键。本文提出了一种基于激光扫描仪、线/面阵CCD相机及GPS与IMU等多种传感器融合的车载移动式数据快速采集系统。各传感器安置在车内稳定平台上并随车保持一致的运动姿态。通过对GPS和IMU数据进行卡尔曼(Kalman)滤波,可推测出整个系统及各传感器的位置和最佳姿态估计;从扫描仪点云数据可提取出街道场景中事物的三维几何信息;线阵CCD相机用于获取路面带状地物等线性特征;面阵CCD采集街道两侧面状纹理信息,从而快速获得城市目标的地理坐标和三维建模信息,由此可重建城市路面街道的三维真实场景。 展开更多
关键词 CCD IMU(inertial Measurement Unit) 点云 卡尔曼滤波 三维建模
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基于惯性测量单元的激光雷达点云融合方法 被引量:19
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作者 张艳国 李擎 《系统仿真学报》 CAS CSCD 北大核心 2018年第11期4334-4339,共6页
针对16线激光雷达环境感知过程中,点云数据稀疏,导致对目标检测和识别困难的问题,提出了一种基于惯性测量单元(InertialMeasurementUnit,IMU)的激光雷达点云融合方法。建立了激光点云数据的融合模型,有效利用历史点云数据与历史检测结果... 针对16线激光雷达环境感知过程中,点云数据稀疏,导致对目标检测和识别困难的问题,提出了一种基于惯性测量单元(InertialMeasurementUnit,IMU)的激光雷达点云融合方法。建立了激光点云数据的融合模型,有效利用历史点云数据与历史检测结果,获得较多的环境信息,提高了目标物的检测精度。利用16线激光雷达与自研的IMU传感器进行实验验证,结果表明能够实现激光雷达点云的融合,进一步提高激光雷达对目标物的检测能力,并且以较低的硬件成本,实现更加高级的环境感知能力,对无人驾驶等技术的研究具有实际应用价值。 展开更多
关键词 IMU(inertial MEASUREMENT Unit) 激光雷达 点云融合 目标物检测
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Review of special issue on high power facility and technical development at the NLHPLP 被引量:2
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作者 Jianqiang Zhu 《High Power Laser Science and Engineering》 SCIE CAS CSCD 2019年第1期90-91,共2页
Achieving ignition of ICF(inertial confinement fusion)has been the great dream that scientists all over the world pursue.As a grand challenge,this aim requires energetic and high quality lasers.High power laser facili... Achieving ignition of ICF(inertial confinement fusion)has been the great dream that scientists all over the world pursue.As a grand challenge,this aim requires energetic and high quality lasers.High power laser facilities,for this purpose,have therefore flourished over the past several decades.Meanwhile high power laser facilities,also essential for high-energy-density(HED)scientific research and astrophysics,drive rapid progress of material science,electronics,precision machinery and so on.Many countries have successfully established a succession of facilities to study ICF and HED physics,such as National Ignition Facility(NIF)[1]in the United States and the Laser Megajoule(LMJ)in France[2]. 展开更多
关键词 ICF(inertial CONFINEMENT fusion) high-energy-density(HED) Laser Megajoule(LMJ)
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一种LiDAR平面配准方法辅助的IMU室内定位算法 被引量:1
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作者 聂明炎 杨诚 《测绘地理信息》 CSCD 2021年第5期27-30,共4页
室内环境由于缺乏观测条件,无法使用全球导航卫星系统(global navigation satellite system,GNSS)进行定位,而单独惯性导航系统(inertial navigation system,INS)由于传感器的误差累积,定位结果快速偏移且无法受到限制。因此,针对室内... 室内环境由于缺乏观测条件,无法使用全球导航卫星系统(global navigation satellite system,GNSS)进行定位,而单独惯性导航系统(inertial navigation system,INS)由于传感器的误差累积,定位结果快速偏移且无法受到限制。因此,针对室内未知环境下移动背包的定位问题,提出激光雷达(light detection and ranging,LiDAR)与惯性测量单元(inertial measurement unit,IMU)的组合导航系统,使用LiDAR平面配准获得的载体速度作为扩展卡尔曼滤波器观测量,对IMU位姿推算的误差进行修正。结果表明,该方法可以有效控制惯性导航误差的漂移,从而提高室内定位精度。 展开更多
关键词 激光雷达(light detection and ranging LiDAR)平面配准 惯性测量单元(inertial measurement unit IMU) 扩展卡尔曼滤波器 室内定位
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