共查询到18条相似文献,搜索用时 171 毫秒
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分析了低成本压电振动陀螺误差及其影响因素,在实验的基础上得出采用温度补偿陀螺误差的可行性。建立了联合卡尔曼滤波方程融合GPS和INS信息,估计定位信息和陀螺误差。提出车载GPS/INS组合导航系统中陀螺零漂误差和标度因子误差的校正过程启动条件,当条件满足时,以估计的陀螺误差为输入,采用温度误差校正表学习算法对陀螺误差模型进行训练。用道路实验数据对提出的陀螺校正算法进行验证,结果表明该算法精度高、收敛快、可操作性好。 相似文献
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提出了一种DR/MM组合定位新方法.采用D-s证据理论在候选路段中选择最匹配的路段进行地图匹配,利用误差概率准则计算地图匹配观测噪声,使得沿道路纵向的地图匹配噪声可观测.在此基础上建立卡尔曼滤波方程,以DR定位与地图匹配的误差为观测值,估计DR定位误差.在地图匹配结果具有较高可信度时,估计的状态反馈修正DR方程.离线试验结果表明,提出的方法显著改善了DR定位精度. 相似文献
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针对车载全球定位系统(global positioning system)存在的定位精度较差、定位可靠性较低等问题,提出了一种车车通信环境下考虑定位信息不确定性的多车协同定位算法.该算法在所研究车辆均装有车载GPS和前置距离传感器的基础上,以定位信息不确定性为依据进行协同定位.对自适应卡尔曼滤波进行改进以确定车辆定位信息的不确定度,搭建车间相对位置模型求解2车相对位置关系,最后设计联邦卡尔曼滤波算法利用多车数据进行融合以实现定位效果的优化.通过数值仿真表明这一算法与自车组合导航相比有效提升了GPS定位精度和可靠性,两者分别平均提升了35.2%和42.6%,且在车联网渗透率较高以及GPS信号较差时,定位效果提升更为明显. 相似文献
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车辆定位技术有多种,无线定位是车辆定位技术中的一个重要分支。基于RSSI(接收信号强度指示)可以实现ZigBee的测距功能。由于RSSI存在测量误差,从而产生测距误差,经过误差传递进一步影响到定位精度。本文提出了基于两参考点的组合定位算法,并对不同参考点组合方式下的定位精度进行分析。仿真结果表明通过灵活配置参考点的数量,改变定位算法,组合方式可以明显改善平面区域内各点的定位精度。 相似文献
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针对传统矢量地图制作中存在的道路位置误差及当前矢量地图校正算法中存在的不足,提出了一种新的矢量地图校正算法.利用大量浮动车GPS数据的地理空间分布特征,构建了道路节点的自适应缓冲区,并对缓冲区内的有效GPS数据进行了筛选,然后通过对筛选后的GPS数据进行层次聚类分析处理,获得了更准确道路节点位置.通过对道路节点校正完成道路校正,运用该算法对重庆市某区域原始矢量地图中的道路进行了校正试验.结果表明:算法能够对存在位置误差的路段进行有效校正,且对于误差较大路段的校正效果更加明显,校正后矢量地图的平均位置误差显著降低. 相似文献
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根据低成本车辆GPS/DR组合定位系统传感器精度低和计算能力弱的特点,提出一种改进联合卡尔曼滤波(FKF)算法,并简化主滤波器信息融合算法,稍微降低融合精度,提高计算效率。试验结果表明,提出的改进联合滤波算法具有融合精度高、容错性好、计算量小、便于工程实现等优点。 相似文献
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In this research, a hybrid dead reckoning error correction scheme is developed based on extended Kalman filter (EKF) and map matching (MM) to improve the positioning accuracy for vehicle self-localization. The developed method aims at obtaining accurate positions when the GPS signals are occasionally unavailable or weakened. First, the heading data collected from an odometer and an optical fiber gyroscope are integrated by an EKF to reduce the random errors in dead reckoning. Then a modified topological MM algorithm is developed to reduce the systematic errors in dead reckoning. In this work, both cross-track errors and along-track errors are considered to improve positioning accuracy of MM. The errors are finally corrected using the results achieved from both the dead reckoning and the MM when the driving distance of a vehicle exceeds a predefined length or the vehicle turns in an intersection. Experiments have been conducted to evaluate the developed method and the results show that the maximum error and average error of dead reckoning can be respectively reduced to 15.4?m and 5.2?m during the experiment with total distance of 43?km. This positioning accuracy is even better than the accuracy of the low-cost GPSs which are usually at the order of 15–20?m (95%). The developed method is effective to achieve the positions of the vehicle when the GPS signals are occasionally unavailable or weakened. 相似文献
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基于GPRS的GPS/DR车辆组合导航的研究 总被引:4,自引:0,他引:4
分析用GPRS网络传输车辆定位信息及其他车辆信息的优点,论述GPS/DR组合导航的原理,描述车载移动终端硬件结构,并且给出一种实现方法。基于GPRS的GPS/DR组合导航将成为车辆导航的主流。 相似文献
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A map-matching algorithm is an integral part of every navigation system and reconciles raw and inaccurate positional data (usually from a global positioning system [GPS]) with digital road network data. Since both performance (speed) and accuracy are equally important in real-time map-matching, an accurate and efficient map-matching algorithm is presented in this article. The proposed algorithm has three steps: initialization, same-segment, and next-segment. Distance between the GPS point and road segments, difference between the heading of the GPS point and direction of road segments, and difference between the direction of consecutive GPS points and direction of road segments are used to identify the best segment among candidates near intersections. In contrast to constant weights applied in existing algorithms, the weight of each criterion in this algorithm is dynamic. The weights of criteria are calculated for each GPS point based on its: (a) positional accuracy, (b) speed, and (c) traveled distance from previous GPS point. The algorithm considers a confidence level on the assigned segment to each GPS point, which is calculated based on the density and complexity of roads around the GPS point. The evaluation results indicate 95.34% correct segment identification and 92.19% correct segment assignment. The most important feature of our algorithm is that the high correct segment identification percentage achieved in urban areas is through a simple and efficient weight-based method that does not depend on any additional data or positioning sensors other than digital road network and GPS. 相似文献
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B. J. Yoon J. Y. Lee J. H. Kim C. S. Han 《International Journal of Automotive Technology》2011,12(1):111-118
A navigation algorithm is indispensable for Unmanned Ground Vehicles (UGVs). During driving, UGVs follow a global path. In
this study, we propose a navigation algorithm using Real Time Kinematic (RTK)-Differential Global Positioning System (DGPS)
units and encoders to complement global path planning. Sometimes GPS systems lose their signals and receive inaccurate position
data due to many factors, such as edifice and barrier obstructions. This paper shows that GPS deviations can be solved using
a Dead Reckoning (DR) navigation method with encoders and that position errors can be decreased through the use of RTK-DGPS
units. In addition to this method, we will introduce a new waypoint update algorithm and a steering algorithm using RTK-DGPS
units. 相似文献
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为了解决智能车动态组合定位过程中,因动力学模型与实际模型之间存在偏差导致滤波精度下降的问题,针对智能车全球导航卫星系统(GNSS)/惯性测量单元(IMU)组合定位系统,结合非线性预测滤波(NPF)和自适应滤波的优点,提出了一种考虑动力学模型系统误差实时估计和补偿的自适应非线性预测滤波(ANPF)算法。首先,根据NPF算法原理,通过最小化预测观测残差与系统误差的加权平方和,估计动力学模型系统误差;其次,结合自适应滤波原理,利用状态预测残差向量构造自适应因子,设计了一种自适应扩展卡尔曼滤波(AEKF)算法,用于估计系统状态向量,并通过自适应因子抑制动力学模型系统误差和线性化误差对系统状态估计精度的影响,克服NPF对系统状态估计精度有限的缺陷;再次,对动力学模型系统误差的估计误差和由动力学模型系统误差引起的系统噪声的等效协方差阵进行了分析和推导,以补偿动力学模型系统误差对系统状态估计的影响;最后,通过车载GNSS/IMU组合定位系统试验,从算法精度、鲁棒性和实时性方面对提出的算法和其他滤波算法的性能进行了验证和对比分析。研究结果表明:提出的自适应算法继承了NPF算法简易性和高实时性的优点,同时克服了NPF算法估计精度有限的缺陷,具有较好的滤波解算精度,水平定位精度小于1.0 m,算法单次平均执行时间约为0.013 9 ms,在精度和实时性的平衡方面显著优于其他滤波方法。 相似文献