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Special Issue "Optical Gyroscopes and Navigation Systems"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 August 2014)

Special Issue Editor

Guest Editor
Dr. Francesco De Leonardis (Website)

Department of Electrical and Information Engineering Polytechnic University of Bari, Via Edoardo Orabona n. 4, 70125 Bari, Italy
Fax: +39 08 0596 3410
Interests: photonic devices; non linear integrated optics; nonlinear photonic sensors; nanophotonic integrated sensors; semiconductor lasers; optical sensors for gyros

Special Issue Information

Dear Colleagues,

The practical feasibility of optical rotation sensing using the Sagnac effect has been clearly demonstrated. Today, these sensors are employed in a number of applications, such as in satellites, aircrafts and missile control, automobiles, robotics, and medicine. In general, the main properties required for optical gyroscopes in many applications are related to high sensitivity, differential detection, low cost batch fabrication, vibration immunity (from a lack of moving parts), small micro-fabricated components, most mature technology. The aim of this special issue is to collect, and make readily available, the most significant works in this research field. Papers addressing a wide range of applications of photonic gyroscopes are sought; topics include, but are not limited to, recent developments in the following areas: fiber optical gyroscopes, integrated optical gyroscopes both passive and active configurations, new generation optical sensors for gyro miniaturizing, noise control, high efficiency techniques of signal processing after photo-detection, new concepts of gyroscopes, accelerometers, and navigation systems.

Dr. Francesco De Leonardis
Guest Editor

Submission

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Keywords

  • sagnac effect
  • angular velocity
  • optical sensors
  • photonic
  • gyroscopes
  • optical resonators
  • optical interferometers
  • fiber optics
  • integrated photonic devices
  • accelerometers
  • satellite
  • automotive
  • medical
  • robotics
  • navigation systems

Published Papers (13 papers)

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Open AccessArticle A New Open-Loop Fiber Optic Gyro Error Compensation Method Based on Angular Velocity Error Modeling
Sensors 2015, 15(3), 4899-4912; doi:10.3390/s150304899
Received: 11 October 2014 / Revised: 21 January 2015 / Accepted: 6 February 2015 / Published: 27 February 2015
Cited by 1 | PDF Full-text (1033 KB) | HTML Full-text | XML Full-text
Abstract
With the open-loop fiber optic gyro (OFOG) model, output voltage and angular velocity can effectively compensate OFOG errors. However, the model cannot reflect the characteristics of OFOG errors well when it comes to pretty large dynamic angular velocities. This paper puts forward [...] Read more.
With the open-loop fiber optic gyro (OFOG) model, output voltage and angular velocity can effectively compensate OFOG errors. However, the model cannot reflect the characteristics of OFOG errors well when it comes to pretty large dynamic angular velocities. This paper puts forward a modeling scheme with OFOG output voltage  and temperature  as the input variables and angular velocity error  as the output variable. Firstly, the angular velocity error  is extracted from OFOG output signals, and then the output voltage , temperature  and angular velocity error  are used as the learning samples to train a Radial-Basis-Function (RBF) neural network model. Then the nonlinear mapping model over T,  and  is established and thus  can be calculated automatically to compensate OFOG errors according to  and . The results of the experiments show that the established model can be used to compensate the nonlinear OFOG errors. The maximum, the minimum and the mean square error of OFOG angular velocity are decreased by ,  and  relative to their initial values, respectively. Compared with the direct modeling of gyro angular velocity, which we researched before, the experimental results of the compensating method proposed in this paper are further reduced by ,  and , respectively, so the performance of this method is better than that of the direct modeling for gyro angular velocity. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter
Sensors 2015, 15(2), 2496-2524; doi:10.3390/s150202496
Received: 13 June 2014 / Accepted: 2 December 2014 / Published: 23 January 2015
Cited by 2 | PDF Full-text (702 KB) | HTML Full-text | XML Full-text
Abstract
As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and [...] Read more.
As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Odometry for Ground Moving Agents by Optic Flow Recorded with Optical Mouse Chips
Sensors 2014, 14(11), 21045-21064; doi:10.3390/s141121045
Received: 5 July 2014 / Revised: 17 October 2014 / Accepted: 23 October 2014 / Published: 6 November 2014
Cited by 2 | PDF Full-text (5341 KB) | HTML Full-text | XML Full-text
Abstract
Optical mouse chips—equipped with adequate lenses—can serve as small, light, precise, fast, and cheap motion sensors monitoring optic flow induced by self motion of an agent in a contrasted environment. We present a device that extracts self motion parameters exclusively from flow [...] Read more.
Optical mouse chips—equipped with adequate lenses—can serve as small, light, precise, fast, and cheap motion sensors monitoring optic flow induced by self motion of an agent in a contrasted environment. We present a device that extracts self motion parameters exclusively from flow in eight mouse sensors. Four pairs of sensors with opposite azimuth are mounted on a sensor head, each individual sensor looking down with \(-\)45\(^{\circ}\) elevation. The head is mounted on a carriage and is moved at constant height above a textured planar ground. The calibration procedure and tests on the precision of self motion estimates are reported. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Laser Gyro Temperature Compensation Using Modified RBFNN
Sensors 2014, 14(10), 18711-18727; doi:10.3390/s141018711
Received: 9 July 2014 / Revised: 2 September 2014 / Accepted: 16 September 2014 / Published: 9 October 2014
Cited by 4 | PDF Full-text (1094 KB) | HTML Full-text | XML Full-text
Abstract
To overcome the effect of temperature on laser gyro zero bias and to stabilize the laser gyro output, this study proposes a modified radial basis function neural network (RBFNN) based on a Kohonen network and an orthogonal least squares (OLS) algorithm. The [...] Read more.
To overcome the effect of temperature on laser gyro zero bias and to stabilize the laser gyro output, this study proposes a modified radial basis function neural network (RBFNN) based on a Kohonen network and an orthogonal least squares (OLS) algorithm. The modified method, which combines the pattern classification capability of the Kohonen network and the optimal choice capacity of OLS, avoids the random selection of RBFNN centers and improves the compensation accuracy of the RBFNN. It can quickly and accurately identify the effect of temperature on laser gyro zero bias. A number of comparable identification and compensation tests on a variety of temperature-changing situations are completed using the multiple linear regression (MLR), RBFNN and modified RBFNN methods. The test results based on several sets of gyro output in constant and changing temperature conditions demonstrate that the proposed method is able to overcome the effect of randomly selected RBFNN centers. The running time of the method is about 60 s shorter than that of traditional RBFNN under the same test conditions, which suggests that the calculations are reduced. Meanwhile, the compensated gyro output accuracy using the modified method is about 7.0 × 10−4 °/h; comparatively, the traditional RBFNN is about 9.0 × 10−4 °/h and the MLR is about 1.4 × 103 °/h. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
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Open AccessArticle Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter
Sensors 2014, 14(9), 17600-17620; doi:10.3390/s140917600
Received: 6 May 2014 / Revised: 5 September 2014 / Accepted: 12 September 2014 / Published: 19 September 2014
Cited by 4 | PDF Full-text (1056 KB) | HTML Full-text | XML Full-text
Abstract
Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated [...] Read more.
Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds  and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Figures

Open AccessArticle HOPIS: Hybrid Omnidirectional and Perspective Imaging System for Mobile Robots
Sensors 2014, 14(9), 16508-16531; doi:10.3390/s140916508
Received: 9 July 2014 / Revised: 10 August 2014 / Accepted: 22 August 2014 / Published: 4 September 2014
PDF Full-text (1044 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we present a framework for the hybrid omnidirectional and perspective robot vision system. Based on the hybrid imaging geometry, a generalized stereo approach is developed via the construction of virtual cameras. It is then used to rectify the hybrid [...] Read more.
In this paper, we present a framework for the hybrid omnidirectional and perspective robot vision system. Based on the hybrid imaging geometry, a generalized stereo approach is developed via the construction of virtual cameras. It is then used to rectify the hybrid image pair using the perspective projection model. The proposed method not only simplifies the computation of epipolar geometry for the hybrid imaging system, but also facilitates the stereo matching between the heterogeneous image formation. Experimental results for both the synthetic data and real scene images have demonstrated the feasibility of our approach. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle An Improved Method for Dynamic Measurement of Deflections of the Vertical Based on the Maintenance of Attitude Reference
Sensors 2014, 14(9), 16322-16342; doi:10.3390/s140916322
Received: 15 May 2014 / Revised: 15 August 2014 / Accepted: 26 August 2014 / Published: 3 September 2014
Cited by 3 | PDF Full-text (931 KB) | HTML Full-text | XML Full-text
Abstract
A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body’s attitude with respect to the [...] Read more.
A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body’s attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch–Tung–Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Fast Field Calibration of MIMU Based on the Powell Algorithm
Sensors 2014, 14(9), 16062-16081; doi:10.3390/s140916062
Received: 5 June 2014 / Revised: 21 August 2014 / Accepted: 25 August 2014 / Published: 29 August 2014
Cited by 2 | PDF Full-text (2579 KB) | HTML Full-text | XML Full-text
Abstract
The calibration of micro inertial measurement units is important in ensuring the precision of navigation systems, which are equipped with microelectromechanical system sensors that suffer from various errors. However, traditional calibration methods cannot meet the demand for fast field calibration. This paper [...] Read more.
The calibration of micro inertial measurement units is important in ensuring the precision of navigation systems, which are equipped with microelectromechanical system sensors that suffer from various errors. However, traditional calibration methods cannot meet the demand for fast field calibration. This paper presents a fast field calibration method based on the Powell algorithm. As the key points of this calibration, the norm of the accelerometer measurement vector is equal to the gravity magnitude, and the norm of the gyro measurement vector is equal to the rotational velocity inputs. To resolve the error parameters by judging the convergence of the nonlinear equations, the Powell algorithm is applied by establishing a mathematical error model of the novel calibration. All parameters can then be obtained in this manner. A comparison of the proposed method with the traditional calibration method through navigation tests shows the classic performance of the proposed calibration method. The proposed calibration method also saves more time compared with the traditional calibration method. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Observability Analysis of a MEMS INS/GPS Integration System with Gyroscope G-Sensitivity Errors
Sensors 2014, 14(9), 16003-16016; doi:10.3390/s140916003
Received: 5 June 2014 / Revised: 12 August 2014 / Accepted: 25 August 2014 / Published: 28 August 2014
Cited by 4 | PDF Full-text (815 KB) | HTML Full-text | XML Full-text
Abstract
Gyroscopes based on micro-electromechanical system (MEMS) technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system [...] Read more.
Gyroscopes based on micro-electromechanical system (MEMS) technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS) and the Global Positioning System (GPS). The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle Time- and Computation-Efficient Calibration of MEMS 3D Accelerometers and Gyroscopes
Sensors 2014, 14(8), 14885-14915; doi:10.3390/s140814885
Received: 18 June 2014 / Revised: 30 July 2014 / Accepted: 11 August 2014 / Published: 13 August 2014
Cited by 4 | PDF Full-text (1210 KB) | HTML Full-text | XML Full-text
Abstract
We propose calibration methods for microelectromechanical system (MEMS) 3D accelerometers and gyroscopes that are efficient in terms of time and computational complexity. The calibration process for both sensors is simple, does not require additional expensive equipment, and can be performed in the [...] Read more.
We propose calibration methods for microelectromechanical system (MEMS) 3D accelerometers and gyroscopes that are efficient in terms of time and computational complexity. The calibration process for both sensors is simple, does not require additional expensive equipment, and can be performed in the field before or between motion measurements. The methods rely on a small number of defined calibration measurements that are used to obtain the values of 12 calibration parameters. This process enables the static compensation of sensor inaccuracies. The values detected by the 3D sensor are interpreted using a generalized 3D sensor model. The model assumes that the values detected by the sensor are equal to the projections of the measured value on the sensor sensitivity axes. Although this finding is trivial for 3D accelerometers, its validity for 3D gyroscopes is not immediately apparent; thus, this paper elaborates on this latter topic. For an example sensor device, calibration parameters were established using calibration measurements of approximately 1.5 min in duration for the 3D accelerometer and 2.5 min in duration for the 3D gyroscope. Correction of each detected 3D value using the established calibration parameters in further measurements requires only nine addition and nine multiplication operations. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle A Class of Coning Algorithms Based on a Half-Compressed Structure
Sensors 2014, 14(8), 14289-14301; doi:10.3390/s140814289
Received: 7 May 2014 / Revised: 7 July 2014 / Accepted: 23 July 2014 / Published: 6 August 2014
Cited by 3 | PDF Full-text (732 KB) | HTML Full-text | XML Full-text | Correction
Abstract
Aiming to advance the coning algorithm performance of strapdown inertial navigation systems, a new half-compressed coning correction structure is presented. The half-compressed algorithm structure is analytically proven to be equivalent to the traditional compressed structure under coning environments. The half-compressed algorithm coefficients [...] Read more.
Aiming to advance the coning algorithm performance of strapdown inertial navigation systems, a new half-compressed coning correction structure is presented. The half-compressed algorithm structure is analytically proven to be equivalent to the traditional compressed structure under coning environments. The half-compressed algorithm coefficients allow direct configuration from traditional compressed algorithm coefficients. A type of algorithm error model is defined for coning algorithm performance evaluation under maneuver environment conditions. Like previous uncompressed algorithms, the half-compressed algorithm has improved maneuver accuracy and retained coning accuracy compared with its corresponding compressed algorithm. Compared with prior uncompressed algorithms, the formula for the new algorithm coefficients is simpler. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)
Open AccessArticle A Measuring System for Well Logging Attitude and a Method of Sensor Calibration
Sensors 2014, 14(5), 9256-9270; doi:10.3390/s140509256
Received: 10 March 2014 / Revised: 12 May 2014 / Accepted: 21 May 2014 / Published: 23 May 2014
Cited by 1 | PDF Full-text (721 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes an approach for measuring the azimuth angle and tilt angle of underground drilling tools with a MEMS three-axis accelerometer and a three-axis fluxgate sensor. A mathematical model of well logging attitude angle is deduced based on combining space coordinate [...] Read more.
This paper proposes an approach for measuring the azimuth angle and tilt angle of underground drilling tools with a MEMS three-axis accelerometer and a three-axis fluxgate sensor. A mathematical model of well logging attitude angle is deduced based on combining space coordinate transformations and algebraic equations. In addition, a system implementation plan of the inclinometer is given in this paper, which features low cost, small volume and integration. Aiming at the sensor and assembly errors, this paper analyses the sources of errors, and establishes two mathematical models of errors and calculates related parameters to achieve sensor calibration. The results show that this scheme can obtain a stable and high precision azimuth angle and tilt angle of drilling tools, with the deviation of the former less than ±1.4° and the deviation of the latter less than ±0.1°. Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)

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Open AccessCorrection Correction: Tang, C. Y. and Chen, X.Y. A Class of Coning Algorithms Based on a Half-Compressed Structure. Sensors 2014, 14, 14289–14301
Sensors 2015, 15(2), 4425-4429; doi:10.3390/s150204425
Received: 23 December 2014 / Revised: 23 December 2014 / Accepted: 11 February 2015 / Published: 13 February 2015
PDF Full-text (688 KB) | HTML Full-text | XML Full-text
Abstract Due to an oversight by MDPI and the authors, the following numerical corrections were not made in the originally published article [1]. MDPI-Sensors and the authors would like to apologize for any inconvenience brought to the readers.[...] Full article
(This article belongs to the Special Issue Optical Gyroscopes and Navigation Systems)

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