Tightly Integrating Optical and Inertial Sensors for Navigation Using the UKF PDF Download

Author: Sedat Ebcin
Publisher:
ISBN:
Category : Imaging systems
Languages : en
Pages : 126

View

Book Description

Author: S. Ebcin
Publisher:
ISBN:
Category :
Languages : en
Pages : 12

View

Book Description
Accurate navigation information "position, velocity, and attitude" can be determined using optical measurements from imaging sensors combined with an inertial navigation system. This can be accomplished by tracking the locations of stationary optical features in multiple images and using the resulting geometry to estimate and remove inertial errors. In previous research efforts, we have demonstrated the effectiveness of fusing imaging and inertial sensors using an extended Kalman filter "EKF" algorithm. In this approach, the image feature correspondence search was aided using the inertial sensor measurements, resulting in more robust feature tracking. The resulting image-aided inertial algorithm was tested using both simulation and experimental data. While the tightly-coupled approach stabilized the feature correspondence search, the overall problem remained prone to filter divergence due to the well-known consequences of image scale ambiguity and the nonlinear measurement model. These effects are evidenced by the consistency divergence in the EKF implementation seen during our longdurationMonte-Carlo simulations. In other words, the measurement model is highly sensitive to the current parameter estimate, which invalidates the linearized measurement model assumed by the EKF. The unscented "sigma-point" Kalman filter "UKF" has been proposed in the literature in order to address the large class of recursive estimation problems which are not well-modeled using linearized dynamics and Gaussian noise models assumed in the EKF. The UKF leverages the unscented transformation in order to represent the state uncertainty using a set of carefully chosen sample points. This approach maintains mean and covariance estimates accurate to at least second order, by using the true nonlinear dynamics and measurement models. In this paper, a variation of the UKF is applied to the.

Author: Aboelmagd Noureldin
Publisher: Springer Science & Business Media
ISBN: 3642304656
Category : Technology & Engineering
Languages : en
Pages : 324

View

Book Description
Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more.

Author: Priyanka Aggarwal
Publisher: Artech House
ISBN: 1608070441
Category : Technology & Engineering
Languages : en
Pages : 213

View

Book Description
Due to their micro-scale size and low power consumption, Microelectromechanical systems (MEMS) are now being utilized in a variety of fields. This leading-edge resource focuses on the application of MEMS inertial sensors to navigation systems. The book shows you how to minimize cost by adding and removing inertial sensors. Moreover, this practical reference provides you with various integration strategies with examples from real field tests. From an introduction to MEMS navigation related applicationsOC to special topics on Alignment for MEMS-Based NavigationOC to discussions on the Extended Kalman Filter, this comprehensive book covers a wide range of critical topics in this fast-growing area."

Author: Chong Shen
Publisher: Springer Nature
ISBN: 9813345160
Category : Technology & Engineering
Languages : en
Pages : 131

View

Book Description
This book introduces typical inertial devices and inertial-based integrated navigation systems, gyro noise suppression, gyro temperature drift error modeling compensation, inertial-based integrated navigation systems under discontinuous observation conditions, and inertial-based brain integrated navigation systems. Integrated navigation is the result of the development of modern navigation theory and technology. The inertial navigation system has the advantages of strong autonomy, high short-term accuracy, all-day time, all weather, and so on. And it has been applied in most integrated navigation systems. Among them, the information processing of inertial-based integrated navigation system is the core technology. Due to the effect of the device mechanism and working environment, there are errors in the output information of the inertial-based integrated navigation system, including gyroscope noise, temperature drift, and discontinuous observations, which will seriously reduce the accuracy and robustness of the system. And the book helps readers to solve these problems. The intelligent information processing technology involved is equipped with simulation verification, which can be used as a reference for undergraduate, graduate, and Ph.D. students, and also scientific researchers or engineers engaged in navigation-related specialties.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 11

View

Book Description
Aircraft navigation information (position, velocity, and attitude) can be determined using optical measurements from imaging sensors combined with an inertial navigation system. This can be accomplished by tracking the locations of optical features in multiple images and using the resulting geometry to estimate and remove inertial errors. A critical factor governing the performance of optical inertial navigation systems is the robustness of the feature tracking algorithm. Robust feature tracking research has focused on developing multi-dimensional feature transformations which are invariant to camera pose variations. In addition, significant effort has been placed into algorithms designed to pair features between images from large sets (e.g., RANSAC). This traditional approach requires large computational resources, especially when presented with imaging situations with sparse, partially obscured, or repetitive features. In this paper, the method of multi-dimensional stochastic constraints is applied to the optical-inertial navigation problem in two dimensional feature space. The resulting navigation system uses inertial measurements to aid the feature tracking algorithm, which results in improvements in robustness and processing speed. The performance of the optical-inertial navigation system is demonstrated using experimental data.

Author: AMITAVA BOSE
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120348591
Category : Technology & Engineering
Languages : en
Pages : 341

View

Book Description
Navigation fundamentally provides information on position, velocity and direction which are needed for travel in ocean, land, air and in space. The myriad forms of navigation developed so far are collectively called modern navigation. This recent text discusses new promising developments that will assist the students when they enter their future professional career. It is the outcome of authors’ wide experience in teaching, research and development in the field of navigation and inertial sensors. The content of the book is designed to impart adequate knowledge to the students in the area of navigation and related sensors. The text discusses inertial navigation, inertial sensors, MEMS based inertial sensors, satellite navigation, integrated inertial navigation, signal processing of inertial sensors and their applications. The chapters introduce all the topics in an easy to understand manner so that an appreciative understanding of the text matter can be made without resorting to equations and mathematics. Considerable references have been provided to enable both the students and the professors to dwell and learn more on the topics of their interest. This textbook is primarily intended to meet the academic needs of undergraduate and postgraduate students of aerospace engineering and avionics.

Author: David Titterton
Publisher: IET
ISBN: 0863413587
Category : Technology & Engineering
Languages : en
Pages : 578

View

Book Description
Inertial navigation is widely used for the guidance of aircraft, missiles ships and land vehicles, as well as in a number of novel applications such as surveying underground pipelines in drilling operations. This book discusses the physical principles of inertial navigation, the associated growth of errors and their compensation. It draws current technological developments, provides an indication of potential future trends and covers a broad range of applications. New chapters on MEMS (microelectromechanical systems) technology and inertial system applications are included.

Author: Anthony Lawrence
Publisher: Springer Science & Business Media
ISBN: 146840444X
Category : Technology & Engineering
Languages : en
Pages : 279

View

Book Description
Automatic navigation makes ocean-going and flying safer and less expensive: Safer because machines are tireless and always vigilant; inexpensive because it does not use human navigators who are, unavoidably, highly trained and thus expensive people. What is more, unmanned deep space travel would be impossible without automatic navigation. Navigation can be automated with the radio systems Loran, Omega, and the Global Positioning System (GPS) of earth satellites, but its most versatile form is completely self-contained and is called inertial navigation. It uses gyroscopes and accelerometers (inertial sensors) to measure the state of motion of the vehicle by noting changes in that state caused by accelerations. By knowing the vehicle's starting position and noting the changes in its direction and speed, one can keep track of the vehicle's present position. Mankind first used this technology in World War n, in guided weapons where cost was unimportant; only 20-30 years later did it become cheap enough to be used commercially. The electronics revolution, in which vacuum tubes were replaced by integrated circuits, has dramatically altered the field of inertial navigation. Early inertial systems used complex mechanical gimbal structures and mechanical gyroscopes with spinning wheels. The gimbals allowed the gyroscopes to stabilize a mass (called a "platform") so that it remained in a fixed attitude relative to a chosen coordinate frame, even as the vehicle turned around any or all of its three major axes.

Author: Jonathan M. Neu
Publisher:
ISBN: 9781423520627
Category : Global Positioning System
Languages : en
Pages : 112

View

Book Description
Micro-Electro-Mechanical Systems (MEMS) technology holds great promise for future navigation systems because of the reduced size and cost of MEMS inertial sensors relative to conventional devices. Current MEMS devices are much less accurate than standard inertial sensors, but they can still be useful. In this thesis, data was recorded from an inexpensive MEMS inertial measurement unit and integrated with GPS measurements using a tightly-coupled Kalman filter. The overall goal of this research is to investigate the usefulness of MEMS sensors for a small, real-time, low-cost INS/GPS integration. A golf cart was used to collect dynamic data, along with a commercial INS/GPS system to provide reference data. This data was then post-processed, and the filter's performance in the position, velocity, and attitude outputs were evaluated by comparing them to the reference system. The important system features of system alignment, bias feedback, and INS resets are described, and the filter's performance is analyzed using its estimate and covariance outputs and comparing them to the true error. Filter residuals are also shown and discussed. The final results show that, with adequate processing available, the INS/GPS filter using the MEMS instruments provides good position, velocity, and attitude results over a period of up to 15 minutes, as long as the data is at least somewhat dynamic. Without vehicle motion, the vehicle yaw state tends to wander excessively, due to the bias and noise of the MEMS gyroscopes. Over a long static period, the filter's position outputs would most likely diverge and become unstable. Recommendations are made to combat this problem, among them to conduct more characterization of the MEMS sensors, and to add GPS velocity measurements as an input to the filter.