北斗导航系统在精细农业系统中的应用

GPS,RS,GIS(简称3S)技术是实现精细农业的关键技术.GPS导航系统是无源系统,只能完成位置信息的采集,需要搭载通信模块才能回传位置数据.在新型精细农业系统中,利用北斗导航系统代替GPS导航系统,搭建基于北斗导航系统的精细农业系统模型,可以实现数据采集和信息回传两项功能,不仅简化系统复杂度、降低建设成本,而且具备安全性和自主可控性.     

北斗卫星导航系统在陆军武器中的应用

北斗卫星导航系统已进入大规模应用阶段。本文首先介绍了卫星导航系统的定位和定向的原理,在此基础上以车载平台作为重点,详细介绍了北斗卫星导航系统在陆军武器系统中的应用。     

北斗卫星导航系统在民用领域中的典型应用

北斗卫星导航系统是中国自主研发的导航系统,它具有中国的自主产权,不但具备定位导航功能,还具备通信功能.目前为止,北斗卫星导航系统被广泛应用于各行业当中,大到军事勘察,小到出行导航.随着北斗二号卫星系统的建设,北斗卫星导航系统功能增强,应用范围扩大,北斗卫星导航系统在导航定位中的作用越来越突出.本文主要研究北斗卫星导航系统的定位原理,分析其在个人位置服务领域中的应用.     

修正Kalman滤波在北斗授时中的应用

北斗卫星导航系统中北斗单向授时用户的授时精度与其上行时延值变化较大有直接关系。经过分析发现,在出现连续较大的野值情况下,线性Kalman滤波算法不能正确估计上行时延值,从而影响北斗用户正常使用。因此,对算法进行了相应修改并提出了基于修正的卡尔曼滤波算法,完成上行时延值的估计方法,同时对该算法进行了仿真,实验结果表明了该算法的正确性。     

车载GPS/北斗/DR组合导航系统研究

针对移动车辆的定位与导航问题,研究了GPS/北斗/DR组合导航算法.文中采用坐标系变换及增加状态变量法对不同卫星星座进行了时空统一,并在此基础上研究了GPS/北斗卫星组合导航算法;为了克服卫星定位存在的不连续性问题,提出了GPS/北斗卫星导航系统与低成本的航位推算系统组合导航方案,设计了GPS/北斗/DR组合导航滤波器...     

北斗卫星导航系统在TD-SCDMA系统中的应用

1北斗卫星导航系统的功能 1.1北斗卫星导航系统功能概述 北斗卫星导航系统,是中国自行研制开发的区域性有源三维卫星定位与通信系统（CNSS）,是除美国的GPS、俄罗斯的GLONASS之后第3个成熟的卫星导航系统。该系统由3颗（两颗工作卫星、一颗备用卫星）北斗定位卫星（北斗一号）、地面控制中心为主的地面部分、北斗用户终端3部分组成。     

北斗卫星导航系统应用的分析

导航定位系统对于国防安全和国家建设均具有重要的战略意义,我国自主研发的北斗导航定位系统已进入了逐步应用的阶段,本文首先对导航定位、授时原理以及该系统的组成进行了介绍,结合实际,分析了典型的应用体系的架构,重点讨论了现有几大应用领域的现状和不足之处,阐述了未来发展的一个方面。     

北斗卫星导航系统URE与定位精度分析

北斗卫星导航系统已具有区域无源导航能力,为了研究当前可用星座情况下的系统定位精度,首先分析用户等效测距误差(UERE)结合精度因子(DOP)值的精度评估方法计算模型,然后利用上述方法采用实际数据对比分析了北斗卫星导航系统和GPS系统一段时间内的静态定位精度。通过分析得出,在该段时间内北斗系统定位精度在水平方向上误差优于5 m,在高程方向上误差优于15 m。     

北斗导航系统应用在我国社会经济发展中的作用

各位来宾．我主要是跟大家沟通一下情况．提一点建议。 关于北斗这一件事情．去年我在会议上也做过介绍。对北斗系统的构成．以及相关的东西，我就不讲了，我主要是讲两个问题.[第一段]     

北斗定向在车载雷达中的应用

北斗二代卫星导航系统(BDS Ⅱ)是我国自主研发、开放兼容、技术先进、由区域逐渐向全球覆盖的导航系统。目标是提供全天候、全天时定位和导航服务。文中介绍的车载炮位侦查与校射雷达配置北斗接收系统进行双频快速定向。在多径信号分析建模的基础上,北斗定位定向仪在扼流圈天线设计、信号处理等方面采取适宜的多径抑制措施。其中,改进窄相关器对同相多径信号起到了较好的抑制效果。测试结果表明:北斗系统具有稳定可靠的定向精度,满足雷达方位标定需求。     

An unscented Kalman filter based navigation algorithm for autonomous underwater vehicles

Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions involving one or more AUVs. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present a comparison between the Extended Kalman Filter (EKF) approach, classically used in the field of underwater robotics and an Unscented Kalman Filter (UKF). The comparison results to be significant as the two strategies of filtering are based on the same process and sensors models. The UKF-based approach, here adapted to the AUV case, demonstrates to be a good trade-off between estimation accuracy and computational load. UKF has not yet been extensively used in practical underwater applications, even if it turns out to be quite promising. The proposed results rely on the data acquired during a sea mission performed by one of the two Typhoon class vehicles involved in the NATO CommsNet13 experiment (held in September 2013). As ground truth for performance evaluation and comparison, performed offline, position measurements obtained through Ultra-Short BaseLine (USBL) fixes are used. The result analysis leads to identify both the strategies as effective for the purpose of being included in the control loop of an AUV. The UKF approach demonstrates higher performance encouraging its implementation as a more suitable navigation algorithm even if, up to now, it is still not used much in this field.     

无迹卡尔曼滤波器在直升机导航系统中的应用

提出一种针对直升机导航过程中风场干扰问题的航迹建模方法。该方法基于CV运动模型,用非线性状态方程准确描述了飞机的定高飞行过程。在该模型的基础上,根据UKF算法设计无迹卡尔曼滤波器,对包含风场噪声的航迹进行处理,用以提高航迹的估计精度。仿真结果表明,航迹估计结果精度较高,滤波效果显著,克服了由于扩展卡尔曼滤波类方法截断误差等因素导致精度下降的不足。此外,该滤波器计算速度快且易实现,具有较好的工程应用参考价值。     

Point-based rigid-body registration using an unscented Kalman filter

We present and validate a novel registration algorithm mapping two data sets, generated from a rigid object, in the presence of Gaussian noise. The proposed method is based on the Unscented Kalman Filter (UKF) algorithm that is generally employed for analyzing nonlinear systems corrupted by additive Gaussian noise. First, we employ our proposed registration algorithm to fit two randomly generated data sets in the presence of isotropic Gaussian noise, when the corresponding points between the two data sets are assumed to be known. Then, we extend the registration method to the case where the data (with known correspondences) is stimulated by anisotropic Gaussian noise. The new registration method not only reliably converges to the correct registration solution, but it also estimates the variance, as a confidence measure, for each of the estimated registration transformation parameters. Furthermore, we employ the proposed registration algorithm for rigid-body, point-based registration where corresponding points between two registering data sets are unknown. The algorithm is tested on point data sets which are garnered from a pelvic cadaver and a scaphoid bone phantom by means of computed tomography (CT) and tracked free-hand ultrasound imaging. The collected 3-D points in the ultrasound frame are registered to the 3-D meshes in the CT frame by using the proposed and the standard Iterative Closest Points (ICP) registration algorithms. Experimental results demonstrate that our proposed method significantly outperforms the ICP registration algorithm in the presence of additive Gaussian noise. It is also shown that the proposed registration algorithm is more robust than the ICP registration algorithm in terms of outliers in data sets and initial misalignment between the two data sets.     

Depth from motion and optical blur with an unscented Kalman filter

Space-variantly blurred images of a scene contain valuable depth information. In this paper, our objective is to recover the 3-D structure of a scene from motion blur/optical defocus. In the proposed approach, the difference of blur between two observations is used as a cue for recovering depth, within a recursive state estimation framework. For motion blur, we use an unblurred-blurred image pair. Since the relationship between the observation and the scale factor of the point spread function associated with the depth at a point is nonlinear, we propose and develop a formulation of unscented Kalman filter for depth estimation. There are no restrictions on the shape of the blur kernel. Furthermore, within the same formulation, we address a special and challenging scenario of depth from defocus with translational jitter. The effectiveness of our approach is evaluated on synthetic as well as real data, and its performance is also compared with contemporary techniques.     

基于平方根无迹卡尔曼滤波的数字预失真算法

射频功率放大器工作在近饱和点时产生的非线性效应是制约其性能提升的主要因素.提出了一种基于非线性无迹卡尔曼滤波的数字预失真算法,可有效克服此非线性效应的影响.针对预失真算法的状态方程为线性的特点,优化了无迹卡尔曼滤波算法以提高运算效率.仿真结果表明,所提算法性能优于传统的基于最小均方的数字预失真算法.     

卡尔曼滤波在iBeacon室内定位系统中的应用

为了抑制iBeacon信号在传播过程中由于人员扰动、多径效应等引起的噪声,以及移动定位过程中定位结果的不稳定,在iBeacon室内定位系统中引入了卡尔曼滤波算法分别对采集到的iBeacon信号与移动定位结果进行处理.首先通过卡尔曼滤波对采集的信号进行处理,降低了信号噪声,提高了信号的质量,其次应用卡尔曼滤波对移动定位结果进行二次处理,提高了移动定位结果的稳定性与精度.实验结果表明,在办公室环境下采用卡尔曼滤波进行处理后可将1 m以内的定位精度提高到80%以上.     

惯性/地磁组合导航系统自适应卡尔曼滤波算法研究

针对惯性/地磁组合导航中遇到的滤波的发散问题,采用自适应卡尔曼滤波估计导航系统的误差.该算法通过实时估计和修正系统噪声以及观测噪声的统计特性达到降低模型误差、抑制滤波发散的目的.在Matlab环境下的仿真证实了该方案可以防止滤波器发散,缩小滤波误差,提高滤波精度.     

In vitro identification of four-element windkessel models based on iterated unscented Kalman filter

Mock circulatory loops (MCLs) have been widely used to test left ventricular assist devices. The hydraulic properties of the mock systemic arterial system are usually described by two alternative four-element windkessel (W4) models. Compared with three-element windkessel model, their parameters, especially the inertial term, are much more difficult to estimate. In this paper, an estimator based on the iterated unscented Kalman filter (IUKF) algorithm is proposed to identify model parameters. Identifiability of these parameters for different measurements is described. Performance of the estimator for different model structures is first evaluated using numerical simulation data contaminated with artificial noise. An MCL is developed to test the proposed algorithm. Parameter estimates for different models are compared with the calculated values derived from the mechanical and hydraulic properties of the MCL to validate model structures. In conclusion, the W4 model with an inertance and an aortic characteristic resistance arranged in series is proposed to represent the mock systemic arterial system. Once model structure is appropriately selected, IUKF can provide reasonable estimation accuracy in a limited time and may be helpful for future clinical applications.     

一种改进的地图匹配技术在车载导航系统中的应用

本文在研究地图匹配算法的基础之上,提出了一种改进的地图匹配算法,利用该算法绝大多数(>96%)定位数据都能相对准确地匹配到道路上,匹配后的定位精度得到提高;匹配算法实现了实时,能够满足实际需要(1次/s);在GPS受到一定程度的遮挡时系统能够正常识别并且匹配.