Heading Sensor Research Articles

A proposal of AHRS yaw angle correction with the use of roll angle

PurposeAttitude and heading are very important measurements on board aircraft. In modern solutions they are measured by the attitude and heading reference system (AHRS). In some small unmanned systems, the GPS track angle is used for heading corrections instead of the magnetometer; then, the system measures the track angle instead of heading. With a temporary lack of correction signals, the measurement error increases very quickly. Similarly, a quick increase in the measurement error is observed when a magnetic heading sensor used for correction stops working properly. This study aims to propose measurement of the roll angle for yaw angle correction.Design/methodology/approachAHRS algorithms were designed; typical maneuvers were analyzed. The method was verified by simulation and in flight testing analysis. For quantitative analyses, a performance index was proposed.FindingsThe method enables reduction of the yaw angle error caused by the gyros bias error. This study presents the idea, results of simulations and flight testing data analysis and discusses advantages and limitations of the presented method.Practical implicationsThe presented methodology can be implemented in AHRS systems for manned and unmanned aircraft.Originality/valueThis study enables more accurate measurement of the yaw angle in the case of missing correction signals.

CORRECTION SCHEMES FOR THE GYROMAGNETIC COMPASS

In connection with the significant progress in the improvement of sensitive elements (gyroscopes, accelerometers, magnetometers), as well as the increased possibilities of information processing by computational means, it became necessary to use modern algorithms for constructing correction systems for the gyromagnetic compass.
 The object of research is the correction circuits: with an adaptable proportional-integral-differential (PID) controller, with a Fuzzy controller, with a Kalman filter for correcting the gyroscopic meter according to the magnetic heading sensor. In this case, the well-known scheme of a gyromagnetic compass with a torque proportional-integral (PI) correction is taken as the basis for comparison. Smoothing of the oscillatory error of a magnetic compass, which may be predominant, is considered. The subject of research is the accuracy characteristics in the steady state.
 The study is carried out by simulating the operation of a gyromagnetic compass. The root mean square error (rms) and the mean value of the error are taken as the correction characteristics. At the same time, the transitional process of the initial exhibition is also controlled.
 In the algorithms under study, new solutions are applied.
 In the differential PID channel, a quarter-period delay of the dominant oscillations is applied, and the gain of the differential channel is adjusted according to the oscillation frequency. This setting allows you to almost completely smooth out the oscillatory error of the gyromagnetic compass by compensating for the oscillatory error with the received signal in the differential circuit.
 In the Kalman filter scheme, the resulting heading error estimate is in antiphase with the error. After the introduction of a delay in the estimate for half a period of fluctuations, the estimate almost completely corresponds to the error. As a result, the oscillatory error can be almost completely eliminated in the instrumental heading value.
 The article shows that all three investigated correction schemes show better characteristics in comparison with the known basic scheme. The highest accuracy can be achieved when applying the Kalman filter with the necessary settings for the perturbation, observation and initial error matrices.
 The simplest to implement is a circuit with an adaptable PID controller. Its characteristics are close to the scheme with the Kalman filter.

A Low-Cost Dead Reckoning Navigation System for an AUV Using a Robust AHRS: Design and Experimental Analysis

In navigation and motion control of an autonomous vehicle, estimation of attitude and heading is an important issue, especially when the localization sensors such as global positioning system (GPS) are not available and the vehicle is navigated by the dead reckoning (DR) strategies. In this paper, based on a new modeling framework, an extended Kalman filter (EKF) is utilized for estimation of attitude, heading, and gyroscope sensor bias using a low-cost microelectromechanical system (MEMS) inertial sensor. The algorithm is developed for accurate estimation of attitude and heading in the presence of external disturbances including external body accelerations and magnetic disturbances. In this study, using the proposed attitude and heading reference system (AHRS) and an identified surge dynamic model of an autonomous underwater vehicle, a low-cost model-aided DR navigation system has been designed for an AUV. The proposed algorithm application is evaluated by experimental tests in different acceleration bound and existence of external magnetic disturbances for an AUV. The results indicate that the roll, pitch, and heading are estimated by mean value errors about 0.35°, 0.29°, and 1.27°, respectively. Moreover, they indicate that a relative navigation error about 8% of the traveling distance can be achieved using the developed approach in during GPS outages.

Autonomous Underwater Vehicle for Vision Based Tracking

This paper describes about the design, construction and control of an “Autonomous Underwater Vehicle for Vision Based Tracking”, built in Vignan’s Institute of Information Technology, Centre for Innovation Lab. The underwater vision robot is essentially an Autonomous Underwater Vehicle (AUV) for study of marine animals by automatically tracking and following them using computer vision. The AUV can also be used as a platform for Photo-mapping of the Seafloor using the onboard camera and light arrangement. The robot is proposed to have 5 thrusters configurations to achieve 4 degrees of freedom controlled by an Inertial Measurement Unit (IMU) interfaced with control unit and powered by commercial LiPo battery packs. The robot is equipped with roll, pitch, heading, and depth sensors which provide sufficient feedback signals to automatically control the vehicle to track a pre-planned trajectory. The centre of gravity and centre of buoyancy of the vehicle are positioned in such a way that it is self-stabilized. Along with this the combinations of sensors and speed control drivers provide more stability to the system using a closed loop control system, without the operator involvement.The AUV also captures videos during its mission using the camera. It is planned to have a multi-core umbilical cable for video signal, water leakage alarm, feedback signals and battery charging lines. This will be only used for development and test purposes and will be removed during autonomous missions. Various control schemes can be applied for the vehicle to track different paths. The AUV is designed to the dimension of 575×210×175mm.TheAUV uses O-rings for the hulls for good water sealing effect as well as for faster assembly and disassembly.We expect this AUV development to mature in to an advanced system can be used as a platform for study of the ocean by scientists, for environmental studies and for defense applications.

Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS

In navigation and motion control of an autonomous vehicle, estimation of attitude and heading is an important issue especially when the localization sensors such as GPS are not available and the vehicle is navigated by the dead reckoning (DR) strategies. In this paper, based on a new modeling framework an Extended Kalman Filter (EKF) is utilized for estimation of attitude, heading and gyroscope sensor bias using a low-cost MEMS inertial sensor. The algorithm is developed for accurate estimation of attitude and heading in the presence of external disturbances including external body accelerations and magnetic disturbances. In this study using the proposed attitude and heading reference system (AHRS) and an odometer sensor, a low-cost aided DR navigation system has been designed. The proposed algorithm application is evaluated by experimental tests in different acceleration bound and existence of external magnetic disturbances for a land vehicle. The results indicate that the roll, pitch and heading are estimated by mean value errors about 0.83%, 0.68% and 1.13%, respectively. Moreover, they indicate that a relative navigation error about 3% of the traveling distance can be achieved using the developed approach in during GPS outages.

A shoreline-estimation system using remote radar sensing and image-processing techniques

Este trabajo propone un sistema de detección basado en radar para calcular las orillas de un rio usando procesamiento de imágenes. El sistema estima orillas sin pérdida apreciable en resolución evitando costos asociados con batimetrías y/o imágenes satelitales. El sistema está compuesto por un radar comercial, un GPS, y un sensor de rumbo que se comunican a un nodo central que georrefencia las mediciones del radar y ejecuta los algoritmos de procesamiento de imágenes. El hardware se basa en un FPGA para interactuar con la señalización interna del radar y extraer la información requerida. El nodo central implementa un novedoso modelo para georreferenciar las mediciones en coordenadas WSG-84. Posteriormente, un algoritmo de tipo “seam-carving” se aplica sobre las coordenadas estimadas para crear las orillas basándose en la probabilidad de la medición. El sistema se valida usando información oficial, y los resultados muestran un ECP de hasta 6 m.

On Shipboard Marine X-Band Radar Near-Surface Current ‘‘Calibration’’

AbstractThe ocean wave signatures within conventional noncoherent marine X-band radar (MR) image sequences can be used to derive near-surface current information. On ships, an accurate near-real-time record of the near-surface current could improve navigational safety. It could also advance understanding of air–sea interaction processes. The standard shipboard MR near-surface current estimates were found to have large errors (of the same order of magnitude as the signal) that are associated with ship speed and heading. For acoustic Doppler current profilers (ADCPs), ship heading errors are known to induce a spurious cross-track current that is proportional to the ship speed and the sine of the error angle. Conventional mechanical gyrocompasses are very reliable heading sensors, but they are too inaccurate for shipboard ADCPs. Within the ADCP community, it is common practice to correct the gyrocompass measurements with the help of multiantenna carrier-phase differential GPS systems. This study shows how a similar multiantenna GPS-based ship heading correction technique stands to improve the accuracy of MR near-surface current estimates. Changes to the standard MR near-surface current retrieval method that are necessary for high-quality results from ships are also introduced. MR and ADCP data collected from R/V Roger Revelle during the Impact of Typhoons on the Ocean in the Pacific (ITOP) program in 2010 are used to demonstrate the MR currents’ accuracy and reliability.

The Approach of Error Calibration for Three-axis Magnetic Heading Sensor

The accuracy of magnetic heading sensor is reduced by the impact of manufacturing technology and local magnetic interferences. The singularity of constraint matrix in traditional calibration algorithm leads to unstable results. Therefore, an improved least-square ellipsoid fitting method is proposed in this paper. The error source and the deviation mathematical model are introduced. On the basis of the analysis on singularity of the constraints matrix, parameter extraction by the improved least-square ellipsoid fitting method is given. The new method successfully overcomes the instability of the traditional algorithm, and reduces the computation load. Simulation and experimental results show that this method is effective in calibrating magnetic heading sensor. The heading precision of the sensor acquired after calibration is better than 0.42o DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4837

Flight Test of a Polarisation Compass Integrated into an Unmanned Aerial Vehicle Autopilot

We report on the first successful development and implementation of an automatic polarisation compass as the primary heading sensor for a UAV. Polarisation compassing is the primary navigation sense of many flying and walking insects, including bees, ants and crickets. Manually operated polarisation astrolabes were fitted in passenger airliners operating over the arctic prior to the implementation of the global positioning system, to compensate for the overall degradation of navigation sensors in polar regions. The device we developed demonstrated accurate determination of the direction of the Sun, with repeatability of better than 0.2 degrees. These figures are comparable to any solid state magnetic compass, including flux gate based devices. Flight trials were undertaken in which the output of the polarimeter was the only heading reference used by the aircraft as it flew GPS waypoints and fixed heading commands without GPS.

Heading and hydrophone data fusion for towed array shape estimation

This paper addresses the problem of towed array shape estimation for passive, horizontal sonar arrays. Beamforming and localization techniques significantly degrade when an assumed linear array bends due to tow platform maneuvers or ocean currents. In this paper, heading sensors along the array and acoustic hydrophone data are jointly used to estimate the shape of the array. Previously, heading data have been filtered using a dynamical motion model to reduce noise during turns. In recent work, a time-varying noise field directionality estimate that incorporates a dynamical model for the acoustic field provides a second, albeit biased, estimate of the array shape. In this paper, these two estimates are combined via adaptive weights to obtain improved shape estimates during maneuvers. A multi-source simulation is used to demonstrate the robustness of the combined array shape estimate when compared to the separate heading or acoustic sensor based techniques.

Reliability-Centered Development of Deep Water ROV ROSUB 6000

AbstractThis paper presents the reliability-centered development of a deep water Remotely Operable Vehicle (ROV) ROSUB 6000 by the National Institute of Ocean Technology (NIOT), India. ROV operations are required during deep water interventions, such as well head operations, emergency response situations, bathymetric surveys, gas hydrate surveys, poly-metallic nodule exploration, and salvage operations. As per our requirements, the system needs to be capable of deep water operation for a period of 300 h/year and to be extremely reliable. Methodologies applied during the development and enhancement phases of electrical and control systems, taking into consideration the cost, space, and time constraints to attain the best possible reliability are detailed. Reliability, availability, and maintainability (RAM) studies are carried out to identify possible failure cases. It is found that ROV-Tether Management System (TMS) docking failure could be detrimental to the ROV system, and manipulator system failure could be detrimental to subsea operations. It has been calculated and found that the improved design has a mean time between failure (MTBF) of 4.9 and 6.2 years for ROV-TMS docking and manipulator system operations, respectively. The importance of monitoring tether cable healthiness during normal and winding operations and the systems implemented for effectively monitoring and maintaining the tether cable operational and functional healthiness, using the tether cable pay-out, vehicle heading, electric insulation, and optical performance sensors with the aid of a sea battery, are discussed. Maintenance decision support tables, which detail the operational personnel for the upkeep of the systems during the indicated interval so that the highest possible reliability is maintained during the mission period, are also presented.

Geometry and Motion-Based Positioning Algorithms for Mobile Tracking in NLOS Environments

This paper presents positioning algorithms for cellular network-based vehicle tracking in severe non-line-of-sight (NLOS) propagation scenarios. The aim of the algorithms is to enhance positional accuracy of network-based positioning systems when the GPS receiver does not perform well due to the complex propagation environment. A one-step position estimation method and another two-step method are proposed and developed. Constrained optimization is utilized to minimize the cost function which takes account of the NLOS error so that the NLOS effect is significantly reduced. Vehicle velocity and heading direction measurements are exploited in the algorithm development, which may be obtained using a speedometer and a heading sensor, respectively. The developed algorithms are practical so that they are suitable for implementation in practice for vehicle applications. It is observed through simulation that in severe NLOS propagation scenarios, the proposed positioning methods outperform the existing cellular network-based positioning algorithms significantly. Further, when the distance measurement error is modeled as the sum of an exponential bias variable and a Gaussian noise variable, the exact expressions of the CRLB are derived to benchmark the performance of the positioning algorithms.

Photolithographic fabrication of a high-precision bar-code pattern on the surface of a sphere

Bar-code patterns were produced upon gold-coated glass spheres 8 mm in diameter with a novel projection photolithography exposure system that included a computer-controlled rotation stage-and-shutter arrangement. The patterns extended in an equatorial band about the entire 360 degrees periphery of the sphere. To obtain uniform thickness of the photoresist layer, we dip coated the spheres and removed the excess with an absorption pad. The widths of the bars in the pattern were in the range 21.85 +/- 0.6 microm at the equator, and the relative error in the angular position of the pattern features was less than 0.025 degrees. The patterned spheres are suitable for use in optically interrogated flying spot magnetic heading sensors.

Array shape estimation and tracking using active sonar reverberation

This paper concerns the problem of array shape estimation and tracking for towed active sonar arrays, using received reverberation returns from a single transmitted CW pulse. Uniform linear arrays (ULAs) deviate from their nominal geometry while being towed due to ship maneuvers as well as ocean currents. In such scenarios, conventional beamforming performed under the assumption of a ULA can sometimes lead to unacceptably high spatial sidelobes. The reverberation leaking through the sidelobes can potentially mask weak targets in Doppler, especially when the target Doppler is close to that of the mainlobe reverberation and the reverberation-to-target ratio (RTR) is very high. Although heading sensors located along the array can be used to provide shape estimates, they may not be sufficiently available or accurate to provide the required sidelobe levels. We propose an array shape calibration algorithm using multipath reverberation returns from each ping as a distributed source of opportunity. More specifically, a maximum likelihood (ML) array shape calibration algorithm is developed, which exploits a deterministic relationship between the reverberation spatial and Doppler frequencies causing it to be low rank in the space-time vector space formed across a single coherent processing interval (CPI). In this application, a sequence of overlapped CPI length snapshots of duration less than the CW pulse is used. The ML estimates obtained for each snapshot are tracked using a Kalman filter with a state equation corresponding to the water pulley model for array dynamics. Simulations performed using real heading sensor data in conjunction with simulated reverberation suggest that 8-10 dB improvement in sidelobe level may be possible using the proposed array shape tracking algorithm versus an algorithm that uses only the available heading information.

C301 水中でのリアル・タイム三次元音響映像

The EchoScope Real Time 3D sonar generates instantaneous 3D images. Every 3D data set is the result of a single acoustic transmitter pulse, hence movement of the sonar head does not distort the data. All data points based on the same transmitter pulse are consistent. An acoustic volume is insonified by the transmitter pulse and the echoes are detected by using a 2D array of 1600 hydrophones. Phase and amplitude are used for parallel generation of 4096 receiver beams (New version: 16384) and 2D lateral images are generated in range slices.The resulting 3D data set contains intensity as well as 3D co-ordinates (x, y and z). These co-ordinates are automatically georeferenced through a GPS receiver and a heading sensor. The Echoscope is also equipped with a roll & pitch sensor.

Fiber optic sensing of magnetic fields

Interferometric fiber sensors using highly magnetostrictive amorphous metals have demonstrated the capability to detect magnetic fields with high resolution. These sensors have potential applications in the areas of geophysics, medical technology, and a variety of commercial and military fields. This paper discusses the magnetoelastic properties of amorphous metal transducers in terms of the coherent rotation model for a magnetic domain. The general operating principles of fiber optic magnetic sensors, including single and multiple axis devices, are developed and theoretical limitations arising from phase noise, shot noise, and thermal noise are discussed. Finally, the results of a number of experiments with fiber magnetometers for both low-(⩽ 100 Hz) and high-frequency (> 100 Hz) magnetic field measurements are presented. These include high-resolution measurements on laboratory devices, testing of a compact three-axis magnetic heading sensor, and a demonstration of fiber optic detection of the mixing of spin wave modes in a metallic glass sample.

Heading and Attitude Sensors

Heading and Attitude Sensors