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首页> 外文会议>Proceedings of the 22nd international technical meeting of the Satellite Division of the Institute of Navigation (ION GNSS 2009) >Multi-sensor Bayesian Estimation Interior Positioning for Stationary and Mobile Structures
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Multi-sensor Bayesian Estimation Interior Positioning for Stationary and Mobile Structures

机译：固定和移动结构的多传感器贝叶斯估计内部定位

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Indoor positioning has been a burgeoning technology which has been researched and,to date,sparsely implemented using a variety of sensors.This paper addresses theoretical and practical considerations of a continuous outboard inboard positioning system with emphasis on its future implementation aboard Navy or commercial ships.The need for positioning systems aboard platforms,such as aircraft carriers,to reduce on-board manning,for damage control and maintenance,as well as for general personnel and high value asset tracking,is a Naval research initiative.The paper evaluates,via analysis and demon stration,the utility of very low cost MEMS(gyroscopes and accelerometers) sensors,along with GPS,to augment the WiFi.This unique combination of sensors,which has been implemented in hardware and modeled in software,is used to explore the tradeoffs among positioning accuracy, availability and complexity. rnThe first test site for the experimental validation of the prototype system hardware and software was chosen as the George Washington University Ashburn campus in Northern Virginia.This site was chosen based on its extensive WiFi capability as well as it having certain areas with topological and WiFi transmission characteristics resembling that of a ship.A description of the WiFi network’s access points,received signal strength maps,and overall topology is included.The generation of detailed apriori WiFi RSS maps along with the overall test methodology employed,necessary to demonstrate a horizontal performance accuracy goal of two meters and deck level vertical discrimination,are described.As a consequence of the non-linearities involved in the RSS maps and topological constraints,as well as the non- Gaussian nature of some of the noise sources,emphasis has been placed on a novel implementation of a regularized particle filter. rnThis paper considers navigation in both an absolute and relative sense.For most applications,absolute and relative solutions can be straightforwardly related to each other.A complication,however,arises when a user on a mobile platform employs inertial sensors as auxiliary sensors. These sensors inherently measure acceleration and angular rate with respect to inertial space and thus are subject to the total motion of the user.When the total motion of the user includes both a relative motion with respect to the mobile vehicle and a vehicle motion with respect to inertial space,then algorithms must attempt to separate the user′s relative motion with respect to the mobile platform.This topic is analytically addressed in a preliminary fashion and will be the subject of further research.The paper concludes with the plans and schedule for a second prototype demonstration aboard a US Navy ship in the Fall of 2009.
机译：室内定位已经成为一种新兴的技术，迄今为止，已经使用各种传感器对其进行了研究和稀疏实现。本文讨论了连续舷外舷内定位系统的理论和实践考虑，重点是其在海军或商用舰船上的未来应用。为了减少机载人员，减少损害的控制和维护以及一般人员和高价值资产的跟踪，需要在航空母舰等平台上定位系统是海军的一项研究计划。和演示，非常低成本的MEMS（陀螺仪和加速度计）传感器与GPS一起使用，以增强WiFi。这种传感器的独特组合已在硬件中实现，并在软件中建模，用于探索折衷方案。定位精度，可用性和复杂性之间的关系。 rn第一个用于原型系统硬件和软件实验验证的测试站点被选为北弗吉尼亚州的乔治华盛顿大学Ashburn校区，该站点是基于其强大的WiFi功能以及具有拓扑和WiFi传输功能的某些区域而选择的特性类似于船。包括对WiFi网络的访问点，接收到的信号强度图和整体拓扑的描述。详细的先验WiFi RSS图的生成以及所采用的整体测试方法，证明了水平性能的准确性由于RSS图涉及非线性和拓扑约束以及某些噪声源的非高斯性质，因此着重说明了两米的目标和甲板高度的垂直判别。正则粒子过滤器的新颖实现。 rn本文从绝对和相对的角度考虑导航。对于大多数应用，绝对和相对的解决方案可以直接相互关联。但是，当移动平台上的用户将惯性传感器用作辅助传感器时，就会出现复杂情况。这些传感器固有地测量相对于惯性空间的加速度和角速度，因此服从用户的总运动。当用户的总运动既包括相对于移动车辆的相对运动，又包括相对于移动车辆的车辆运动。惯性空间，然后算法必须尝试分离用户相对于移动平台的相对运动。本主题以初步的方式进行了分析研究，将成为进一步研究的主题。 2009年秋天，第二艘原型机在美国海军舰艇上进行了演示。

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