GPS/INS uses low-cost MEMS IMU

Brown, Alison

doi:10.1109/maes.2005.1514768

Cited by 49 publications

(19 citation statements)

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“…While they were used in the beginning mainly as sensors and actuators, they are nowadays designed to be used in many other engineering applications [1]. To cite few, they are being used as pressure sensors [2,3], accelerometers [4,5], microphones in cellphones [6], micro-mirrors in plasma TVs [7], GPS [8] and many other useful applications. Moreover, they are still being continuously explored by scientists and researchers, and these developments will hopefully lead to more useful features and become even more important in life.…”

Section: Introductionmentioning

confidence: 99%

Structural Behavior of a Multi-Layer Based Microbeam Actuator

2016

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Abstract:In this paper, the structural behavior of a micro-electromechanical system (MEMS) composed of two electrically coupled parallel clamped-clamped microbeams is investigated. An Euler Bernoulli beam model is considered along with the nonlinear electric actuating force to get the equation of motion governing the structural behavior of the actuator. A reduced-order modeling (ROM) based on the Galerkin expansion technique, while assuming linear undamped mode shapes of a straight fixed-fixed beam as the basis functions, is assumed as a discretization technique of the equations of motion in this investigation. The results showed that the double-microbeam MEMS actuator configuration requires a lower actuation voltage and a lower switching time as compared to the single microbeam actuator. Then, the effects of both microbeams air gap depths were investigated. Finally, the eigenvalue problem was investigated to get the variation of the fundamental natural frequencies of the coupled parallel microbeams with the applied actuating DC load.

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Section: Introductionmentioning

confidence: 99%

Structural Behavior of a Multi-Layer Based Microbeam Actuator

2016

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“…However, such INU configuration still fail to work as a standalone device for navigation applications due to its resided stochastic noise (El-Diasty and Spiros, 2008;Sheimy et al, 2008;Lim et al, 2012a). A conventional approach to solve this issue is to fuse the Global Positioning System (GPS) data with the INU measurement using Kalman filter, where such configuration is commonly known as GPS-aided INS (Alison, 2005;David et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Implementation of Anfis for GPS-Aided Ins Uav Motion Sensing at Short Term GPS Outage

Lim¹,

Lim²,

Koo³

2014

Journal of Computer Science

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The recent improvement in Micro-Electro-Mechanical System (MEMS) technology has enabled the evolvement of Inertial Navigation Unit (INU) to be built on top of a low cost, small size Integrated Circuit (IC) chip. Due to the nature of the MEMS INU, its outputs are normally corrupted by the resided stochastic noise. A common practice to regulate its measurements into usable motion data is by fusing the Global Positioning System (GPS) measurement data with the MEMS INU measurement data through Kalman filter for position, velocity and orientation estimations. Such integrated system is known as GPS-aided Inertial Navigation System (INS). Note that the robustness of the GPS-aided INS relies heavily on the availability of the GPS signals. In the event of no GPS signals, the overall system will solely depend on the INU to predict the position, velocity and orientation. The prediction results will eventually drift from its true value due to the INU's resided stochastic noise. In this study, a remedy system using Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed to improve the performance of the GPS-aided INS during GPS outage condition. UAV motion sensing experiment was carried out and GPS outage conditions were imposed at several locations during the UAV navigation. The motion prediction dataduring GPS outages, with and without ANFIS implementation, were compared and the results clearly show that the GPS-aided INS with ANFIS implementation achieved better performance than the GPS-aided INS without ANFIS.

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“…The error modeling and inertial sensor integration algorithms for the MEMS-based IMUs have been discussed for years [1][2][3][4][5][6][7][8]. Technically, with aiding sensors such as GPS receivers or odometers, the rapid-growing navigation solution errors in a low cost land vehicle system can be constrained within a level of meters [9].…”

Section: Introductionmentioning

confidence: 99%

Low Cost Multisensor Kinematic Positioning and Navigation System with Linux/RTAI

Qian

Gopaul

2012

JSAN

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Despite its popularity, the development of an embedded real-time multisensor kinematic positioning and navigation system discourages many researchers and developers due to its complicated hardware environment setup and time consuming device driver development. To address these issues, this paper proposed a multisensor kinematic positioning and navigation system built on Linux with Real Time Application Interface (RTAI), which can be constructed in a fast and economical manner upon popular hardware platforms. The authors designed, developed, evaluated and validated the application of Linux/RTAI in the proposed system for the integration of the low cost MEMS IMU and OEM GPS sensors. The developed system with Linux/RTAI as the core of a direct geo-referencing system provides not only an excellent hard real-time performance but also the conveniences for sensor hardware integration and real-time software development. A software framework is proposed in this paper for a universal kinematic positioning and navigation system with loosely-coupled integration architecture. In addition, general strategies of sensor time synchronization in a multisensor system are also discussed. The success of the loosely-coupled GPS-aided inertial navigation Kalman filter is represented via post-processed solutions from road tests.

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GPS/INS uses low-cost MEMS IMU

Cited by 49 publications

References 0 publications

Structural Behavior of a Multi-Layer Based Microbeam Actuator

Structural Behavior of a Multi-Layer Based Microbeam Actuator

Implementation of Anfis for GPS-Aided Ins Uav Motion Sensing at Short Term GPS Outage

Low Cost Multisensor Kinematic Positioning and Navigation System with Linux/RTAI

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