Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium最新文献_第7页

Collaborative image navigation simulation and analysis for UAVs in GPS challenged conditions GPS挑战条件下无人机协同图像导航仿真与分析

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236949

B. Schnaufer, P. Hwang, J. Nadke, G. McGraw, D. Venable

{"title":"Collaborative image navigation simulation and analysis for UAVs in GPS challenged conditions","authors":"B. Schnaufer, P. Hwang, J. Nadke, G. McGraw, D. Venable","doi":"10.1109/PLANS.2012.6236949","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236949","url":null,"abstract":"Accurate and robust position, navigation, and time (PNT) data is a key-enabler for multi-platform collaborative sensing for a diverse array of military operations. The AFRL Collaborative Robust Integrated Sensor Positioning (CRISP) program has investigated techniques that leverage shared sensor data to enhance the availability of reliable PNT information for all platforms in a network, particularly those that experience GPS outages, utilizing electro-optical (EO) payload data in conjunction with GPS and inertial data. Rockwell Collins has developed an architecture for enabling continuous navigation capabilities for airborne platforms having disparate sensing capabilities in GPS challenged and denied conditions. In this study program the Rockwell Collins architecture was evaluated via a high-fidelity simulation environment. Navigation performance results for our solution were produced and presented by exercising our simulation with an AFRL-provided dataset. The performance results have shown that our collaborative image navigation architecture and implementation supports extended, GPS-level navigation accuracy in GPS Denied conditions.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128217827","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

High-Q and wide dynamic range inertial MEMS for north-finding and tracking applications 用于寻北和跟踪应用的高q宽动态范围惯性MEMS

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236888

A. Trusov, I. Prikhodko, S. Zotov, A. Shkel

{"title":"High-Q and wide dynamic range inertial MEMS for north-finding and tracking applications","authors":"A. Trusov, I. Prikhodko, S. Zotov, A. Shkel","doi":"10.1109/PLANS.2012.6236888","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236888","url":null,"abstract":"We report high-Q and wide dynamic range MEMS gyroscopes and accelerometers for development of an IMU capable of north finding and tracking. The vacuum sealed SOI gyroscope utilizes symmetric quadruple mass architecture with measured quality factors of 1.2 million and proven sub-°/hr Allan deviation of bias. The true north detection was accomplished in conventional amplitude modulated (AM) rate mode and showed 3 milliradian measurement uncertainty. The north (azimuth) tracking necessitates a wide dynamic range, for which the same QMG transducer is switched to a frequency modulated (FM) modality. The test results for FM operation experimentally demonstrated a wide linear input rate range of 18,000 °/s and inherent self-calibration against temperature changes. Vertical alignment is possible using resonant accelerometers with a projected bias error of 5 μg and self-calibration against temperature variations, enabled by differential frequency measurements. We believe the developed low dissipation inertial MEMS with interchangeable AM/FM modalities may enable wide dynamic range IMUs for north-finding and inertial guidance applications previously limited to optical and quartz systems.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133677240","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: 15

A framework for inertial sensor calibration using complex stochastic error models 基于复杂随机误差模型的惯性传感器标定框架

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236827

Y. Stebler, S. Guerrier, Jan Skalud, Maria-Pia Victoria-Feser

{"title":"A framework for inertial sensor calibration using complex stochastic error models","authors":"Y. Stebler, S. Guerrier, Jan Skalud, Maria-Pia Victoria-Feser","doi":"10.1109/PLANS.2012.6236827","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236827","url":null,"abstract":"Modeling and estimation of gyroscope and accelerometer errors is generally a very challenging task, especially for low-cost inertial MEMS sensors whose systematic errors have complex spectral structures. Consequently, identifying correct error-state parameters in a INS/GNSS Kalman filter/smoother becomes difficult when several processes are superimposed. In such situations, the classical identification approach via Allan Variance (AV) analyses fails due to the difficulty of separating the error-processes in the spectral domain. For this purpose we propose applying a recently developed estimation method, called the Generalized Method of Wavelet Moments (GMWM), that is excepted from such inconveniences. This method uses indirect inference on the parameters using the wavelet variances associated to the observed process. In this article, the GMWM estimator is applied in the context of modeling the behavior of low-cost inertial sensors. Its capability to estimate the parameters of models such as mixtures of GM processes for which no other estimation method succeeds is first demonstrated through simulation studies. The GMWM estimator is also applied on signals issued from a MEMS-based inertial measurement unit, using sums of GM processes as stochastic models. Finally, the benefits of using such models is highlighted by analyzing the quality of the determined trajectory provided by the INS/GNSS Kalman filter, in which artificial GNSS gaps were introduced. During these epochs, inertial navigation operates in coasting mode while GNSS-supported trajectory acts as a reference. As the overall performance of inertial navigation is strongly dependent on the errors corrupting its observations, the benefits of using the more appropriate error models (with respect to simpler ones estimated using classical AV graphical identification technique) are demonstrated by a significant improvement in the trajectory accuracy.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434318","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: 29

A novel quasi open loop frequency estimator for GNSS signal tracking 一种用于GNSS信号跟踪的准开环频率估计器

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236836

M. Tahir, L. Presti, M. Fantino

引用次数: 7

E-textile microstrip patch antennas for GPS GPS用电子纺织微带贴片天线

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236866

P. Elliot, E. Rosario, B. Rama Rao, R. Davis, N. M. Marcus

{"title":"E-textile microstrip patch antennas for GPS","authors":"P. Elliot, E. Rosario, B. Rama Rao, R. Davis, N. M. Marcus","doi":"10.1109/PLANS.2012.6236866","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236866","url":null,"abstract":"Body-worn microstrip patch antennas made from e-textile (Electro-Textile) materials were designed, built, and tested for the 1575 MHz (L1) and 1227 MHz (L2) Global Positioning System (GPS) frequencies. E-textiles, including fabrics and foam sheets, are flexible, lightweight, wearable, conformal, and the materials are low cost compared to conventional antenna materials. A variety of materials were tested to determine suitability for e-textile antennas. Gain was measured and found to be a few dB lower than for patch antennas built with conventional copper-clad materials, largely due to higher ohmic losses in the conductive fabrics. Gain was also measured on a human body “phantom” which is a plastic shell filled with fluids formulated to replicate the electromagnetic properties of the body. Use of wearable antennas removes the antenna from the receiver which reduces the size and weight of the receiver, and also allows larger antennas to be used. This effort also helps prepare for possible future applications of multiple wearable antennas such as interference mitigation, anti-spoof, indoor position detection, multiple-input-multiple-output (MIMO) communications, and body-worn antennas for health monitoring or covert communications.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125591564","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: 15

A near-far effect canceller for GPS high sensitivity receiver GPS高灵敏度接收机的近远效应消除器

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236900

Bidong Lu, J. Zhong, Minjian Zhao, Liyan Li

引用次数: 5

Filter-based calibration for an IMU and multi-camera system 基于滤波器的IMU和多相机系统标定

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236950

K. Brink, A. Soloviev

引用次数: 12

Study on the use of Microsoft Kinect for robotics applications 微软Kinect在机器人应用中的应用研究

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236985

Riyad A. El-laithy, Jidong Huang, M. Yeh

{"title":"Study on the use of Microsoft Kinect for robotics applications","authors":"Riyad A. El-laithy, Jidong Huang, M. Yeh","doi":"10.1109/PLANS.2012.6236985","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236985","url":null,"abstract":"The Microsoft X-Box Kinect Sensor is a revolutionary new depth camera that is used in the gaming industry to capture motions of people and players efficiently using the technology of an RGB camera and infrared camera to differentiate depth. In the Microsoft X-Box, Kinect was used to sense 3D perception of human's motions. It can also be used for robotic applications, precisely for indoor navigation through the process of reverse engineering. Certain software packages were made available and are open source from “LibFreenect” for Linux machines, Microsoft's Kinect SDK using the Kinect namespace on Visual Studio 2010 Express (C++, C# or Visual Basic), and Google's released “Robotic Operating System (ROS)”. In order to claim that this sensor is capable of taking on such a task, we must be able to investigate thoroughly all factors that contribute to this and at the same time we must be able to understand its limitations to be applied and integrated properly with certain types of robots for accomplishing our purpose of achieving successful indoor navigation using proper algorithms. In this paper, the results from testing the Kinect sensor on an autonomous ground vehicle was given.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594715","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: 206

An analysis of observability-constrained Kalman Filtering for vision-aided navigation 视觉辅助导航的可观测约束卡尔曼滤波分析

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236980

C. Taylor

{"title":"An analysis of observability-constrained Kalman Filtering for vision-aided navigation","authors":"C. Taylor","doi":"10.1109/PLANS.2012.6236980","DOIUrl":"https://doi.org/10.1109/PLANS.2012.6236980","url":null,"abstract":"Significant improvements in the accuracy of navigation state estimation have been previously demonstrated through the fusion of inertial measurement unit (IMU) and visual sensor data in both GPS-denied and GPS-enabled scenarios. Despite this improved navigation state accuracy, several significant hurdles remain before widespread acceptance of vision-aided navigation can be achieved. One significant bottleneck is the lack of accurate information about the performance of the vision-aided navigation algorithms. Many vision-aided navigation algorithms are implemented using some form of the Kalman Filter, thereby returning a covariance estimate that should correspond with the accuracy of the current navigation estimate. Unfortunately, a well known problem with the Kalman Filter is that its covariance estimates are inconsistent, i.e. the Kalman Filter estimates of uncertainty are significantly smaller than the true uncertainty achieved by the Kalman Filter. Recently a set of papers has introduced the concept of “observability-constrained” Kalman filtering that helps solve the consistency problem. In this paper, we apply the observability-constrained Kalman Filter to a vision-aided navigation problem and analyze its results. Significantly more accurate state and uncertainty estimates are achieved using the observability-constrained Kalman Filter. Unfortunately, the it is still not consistent, so a comparison with a batch, bundle adjustment approach is also performed to verify the possibility of consistent uncertainty estimation.","PeriodicalId":282304,"journal":{"name":"Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121353558","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: 14

The IMRE Kalman filter — A new Kalman filter extension for nonlinear applications IMRE卡尔曼滤波器-一种新的非线性应用的卡尔曼滤波器扩展

Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium Pub Date : 2012-04-23 DOI: 10.1109/PLANS.2012.6236912

A. Draganov, L. Haas, M. Harlacher

引用次数: 3