2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014最新文献_第4页

Indoor navigation using Smartphone technology: A future challenge or an actual possibility? 使用智能手机技术的室内导航:未来的挑战还是现实的可能性?

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851509

M. Piras, A. Lingua, P. Dabove, I. Aicardi

{"title":"Indoor navigation using Smartphone technology: A future challenge or an actual possibility?","authors":"M. Piras, A. Lingua, P. Dabove, I. Aicardi","doi":"10.1109/PLANS.2014.6851509","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851509","url":null,"abstract":"Today knowing where we are has become an important issue for people who interactively and dynamically live and work in urban cities. Each user has a very complete and complex set of technologies for positioning and navigating in his/her hands which are simple to use even if they are not good at positioning or in Geomatics. Accelerometers, gyroscopes, magnetometers, pressure sensors, GNSS receivers, digital cameras are all tools which can be used for defining a three-dimensional position and their integration could be the key point of this technology. Indoor positioning is the latest challenge to be used whenever GNSS positioning is not always available or null, even using high sensitivity sensors. An alternative solution must be found starting from determining the other available solutions in Smartphone devices. An example of indoor positioning could be obtained by using the Image Based Navigation (IBN) approach, where the coordinates of our device are defined using the photogrammetric principle. Several papers demonstrate that IBN can be an useful approach for positioning and how the device in Smartphones can work indoors. In this study, the authors attempt to combine the IBN method with the potentiality of Smartphone internal sensors, in order to verify their performance in indoor positioning.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115219581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Robust en-route and terminal navigation using topology and intensity returns from a forward-looking millimeter-wave radar 利用前向毫米波雷达的拓扑和强度反馈，实现稳健的航路和终端导航

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851366

Joseph T. Hansen, J. Cross, D. Jourdan

{"title":"Robust en-route and terminal navigation using topology and intensity returns from a forward-looking millimeter-wave radar","authors":"Joseph T. Hansen, J. Cross, D. Jourdan","doi":"10.1109/PLANS.2014.6851366","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851366","url":null,"abstract":"In this paper we present Sierra Nevada Corporation's (SNC) Generalized Information Fusion Filter (GIFF). GIFF is a robust, sensor-agnostic estimation framework designed to blend measurements from a variety of sensors to produce an optimal estimate of the navigation state. At the core of GIFF is a Rao-Blackwellized (or marginalized) Particle Filter (RB-PF) with specialized Auxiliary Sampling Importance Resampling (ASIR). This algorithm places no limitation on the number of sensors it can use or on the linearity and error characteristics of their measurements, as opposed to more rigid, traditional techniques like Kalman Filters. This enables GIFF to process data from sensors of various kinds directly (3D radar/LIDAR, 2D surveillance radar, EO/IR, radar-altimeter, GPS, IMU, etc.), with minimal pre-processing. In addition, the marginalized implementation enables a large number of states to be estimated in real-time. We illustrate GIFF flexibility and performance using actual sensor data collected on fixed- and rotary-wing platforms equipped with an imaging radar producing 3D points and 2D images, a radar-altimeter, and an IMU. En-route tests show near-optimal accuracy is achieved during a one-hour flight over Virginia with a simulated GPS outage. GIFF is also initialized with large position uncertainty (5km) and shown to converge after only 30 seconds of flight. GIFF performance during terminal operations (landing) is illustrated using data collected on approaches to the Reno Stead airport, showing an accuracy similar to GPS 60 seconds before touchdown.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115243534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study of MEMS-based inertial sensors operating in dynamic conditions 基于mems的动态惯性传感器研究

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851497

Y. Stebler, S. Guerrier, J. Skaloud, R. Molinari, Maria-Pia Victoria-Feser

引用次数: 5

Simulation of stress effects on mode-matched MEMS gyroscope bias and scale factor 应力对模式匹配MEMS陀螺仪偏置和标度因子影响的仿真

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851352

E. Tatar, T. Mukherjee, G. Fedder

引用次数: 17

IMU calibration and validation in a factory, remote on land and at sea IMU校准和验证在工厂，在遥远的陆地和海上

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851514

M. J. Jørgensen, Dario Paccagnan, N. K. Poulsen, M. Larsen

{"title":"IMU calibration and validation in a factory, remote on land and at sea","authors":"M. J. Jørgensen, Dario Paccagnan, N. K. Poulsen, M. Larsen","doi":"10.1109/PLANS.2014.6851514","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851514","url":null,"abstract":"This paper treats the IMU calibration and validation problem in three settings: Factory production line with the aid of a precision multi-axis turntable, in-the-field on land and at sea, both without specialist test equipment. The treatment is limited to the IMU calibration parameters of key relevance for gyro-compassing grade optical gyroscopes and force-rebalanced pendulous accelerometers: Scale factor, bias and sensor axes misalignments. Focus is on low-dynamic marine applications e.g., subsea construction and survey. Two different methods of calibration are investigated: Kalman smoothing using an Aided Inertial Navigation System (AINS) framework, augmenting the error state Kalman filter (ESKF) to include the full set of IMU calibration parameters and a least squares approach, where the calibration parameters are determined by minimizing the magnitude of the INS error differential equation output. A method of evaluating calibrations is introduced and discussed. The two calibration methods are evaluated for factory use and results compared to a legacy proprietary method as well as in-field calibration/verification on land and at sea. The calibration methods shows similar navigation performance as the proprietary method. This validates both methods for factory calibration. Furthermore it is shown that the AINS method can calibrate in-field on land and at sea without the use of a precision multi-axis turntable.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"276 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123414148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

High-precision globally-referenced position and attitude via a fusion of visual SLAM, carrier-phase-based GPS, and inertial measurements 通过融合视觉SLAM、基于载波相位的GPS和惯性测量，实现高精度的全球参考位置和姿态

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851506

Daniel P. Shepard, T. Humphreys

{"title":"High-precision globally-referenced position and attitude via a fusion of visual SLAM, carrier-phase-based GPS, and inertial measurements","authors":"Daniel P. Shepard, T. Humphreys","doi":"10.1109/PLANS.2014.6851506","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851506","url":null,"abstract":"A novel navigation system for obtaining high-precision globally-referenced position and attitude is presented and analyzed. The system is centered on a bundle-adjustment-based visual simultaneous localization and mapping (SLAM) algorithm which incorporates carrier-phase differential GPS (CDGPS) position measurements into the bundle adjustment in addition to measurements of point features identified in a subset of the camera images, referred to as keyframes. To track the motion of the camera in real-time, a navigation filter is employed which utilizes the point feature measurements from all non-keyframes, the point feature positions estimated by bundle adjustment, and inertial measurements. Simulations have shown that the system obtains centimeter-level or better absolute positioning accuracy and sub-degree-level absolute attitude accuracy in open outdoor areas. Moreover, the position and attitude solution only drifts slightly with the distance traveled when the system transitions to a GPS-denied environment (e.g., when the navigation system is carried indoors). A novel technique for initializing the globally-referenced bundle adjustment algorithm is also presented which solves the problem of relating the coordinate systems for position estimates based on two disparate sensors while accounting for the distance between the sensors. Simulation results are presented for the globally-referenced bundle adjustment algorithm which demonstrate its performance in the challenging scenario of walking through a hallway where GPS signals are unavailable.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124736934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 33

The design process for navigation Kalman filters: Striving for performance and quality 导航卡尔曼滤波器的设计过程:追求性能和质量

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851439

Z. Berman

{"title":"The design process for navigation Kalman filters: Striving for performance and quality","authors":"Z. Berman","doi":"10.1109/PLANS.2014.6851439","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851439","url":null,"abstract":"A methodology for the design of navigation Kalman filters is discussed. The goal is to design a Kalman filter that can support sensor integration during its extensive life span with well-controlled performance. The idea is to relate the Kalman filter design with systematic performance evaluation. Using dual model and truth covariance analysis (TCA) approaches, a complete framework for modeling, evaluating and designing an arbitrary integration scheme based on inertial sensors is described. One important achievement is the separation of system-level decisions such as sensor selection or measurement policy from Kalman filter design. The second achievement is the effective procedure for Kalman filter design based on two, almost completely automated steps: state selection and reduced-order Kalman filter tuning. The last, but by no means least important accomplishment is the presentation of an integrated framework, with appropriate parameterization and interfaces, to support all design phases and to allow reuse, with minimal modification, for different projects. The methodology is illustrated with a case-study analysis of a low-cost vehicle INS/GPS system.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123549677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Correction combination of compact network RTK considering tropospheric delay variation over height 考虑对流层时延随高度变化的紧凑网络RTK校正组合

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851362

Junesol Song, C. Kee, Byungwoon Park, Heungwon Park, Seungwoo Seo

引用次数: 5

Implementation of identification system for IMUs based on Kalman Filtering 基于卡尔曼滤波的imu识别系统的实现

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851381

D. Unsal, M. Doğan

{"title":"Implementation of identification system for IMUs based on Kalman Filtering","authors":"D. Unsal, M. Doğan","doi":"10.1109/PLANS.2014.6851381","DOIUrl":"https://doi.org/10.1109/PLANS.2014.6851381","url":null,"abstract":"Modeling and simulation studies are used to measure the desired performance prior to the hardware implementation of inertial navigation systems. Inertial measurement units are the main components of the inertial navigation systems. Therefore, IMUs should be modeled within the scope of modeling and simulation studies of inertial navigation systems. Several time and frequency domain analysis are implemented in these simulation studies. In addition to deterministic and stochastic error parameters, frequency and delay characteristics of the sensors required for inertial sensor identification. Hence, transfer functions of accelerometer and gyroscope channels are required. Generally, transfer functions of COTS IMUs, accelerometers and gyroscopes are not provided to end-users. Therefore, identification of sensor transfer functions becomes a problem. In order to identify sensor transfer function several methods have been examined. This study explains the how the transfer functions of inertial sensors are defined by using system identification with Kalman Filter. System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system. System identification consists of data record, generating of model set and determining of the best model steps and lots of several methods can be used in these steps. In the scope of this study Kalman Filter is used to generate candidate transfer function set in the generating of model set step of the system identification. Transfer function identification process will be completed by selecting the best model from the model set. Thereby, effects of frequency and delay characteristics on the system performance can be observed. An IMU can be modeled in frequency domain with transfer function by using the methodology which is explained in this study.","PeriodicalId":371808,"journal":{"name":"2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125410222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Robust motion mode recognition for portable navigation independent on device usage 独立于设备使用的便携式导航鲁棒运动模式识别

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014 Pub Date : 2014-05-05 DOI: 10.1109/PLANS.2014.6851370

Mostafa Elhoushi, J. Georgy, M. Korenberg, A. Noureldin

引用次数: 16