Digital Magnetic Compass Research Articles

Информационно-управляющая система сбора и передачи информации для безэкипажного судна

The article considers the principles of constructing and functioning the data collection and transmission system for developing an information and control system of an unmanned vessel. A problem of the information and control system developing is suggested in two stages: choosing methods and means of transmitting data from sensors to the data collection system, choosing the method of data transfer to the data collection system, implementing the data transmission channels; organizing data collection and storage for use in the autopilot device, implementing systems for receiving and synchronizing data and their placement in the storage system. There has been illustrated a block diagram of the information and control system for collecting and transmitting data for an unmanned vessel, which consists of two subsystems: data collection and data transmission. Selecting the main components and proposals on the software and hardware application is carried out. The detailed characteristics of the microcontroller, digital compass, microelectromechanical sensors and chartplotter are given. In the course of implementing the data collection system, a Maretron digital magnetic compass, CRM100 and CRM200 microelectromechanical sensors, which implement a yaw rate sensor and inclinometer, and an analog steering sensor were connected to the debug board. The software for the information and control system is written in the programming language using the STM32CubeIDE application development tools. It has been stated that the data transfer between different levels of the program is carried out using standard means of the program code.

Simplified KF-based energy-efficient vehicle positioning for smartphones

Recently, smart mobile devices, such as smartphone and tablet PC, have become so prevalent. Most of them are equipped with a set of sensors including a global positioning system (GPS) receiver, a digital magnetic compass, a gyroscope, and an ac-celerometer. Unlike traditional vehicle-fixed sensors, smartphone-embedded sensors can be utilized as a user-friendly and portable measurement probe for vehicle positioning systems, owing to their flexibility and mobility. However, GPS modules and inertial navigation system (INS) sensors, such as an accelerometer and a gyroscope, on smartphones consume a lot of battery power. Continued use of the battery for a long time may cause the battery to discharge immediately. Therefore, one of the main concerns for smartphone-based GPS/INS positioning algorithms is energy efficiency. Furthermore, low-cost INS sensors on smartphones may result in large localization errors due to sensor drift and bias. Unlike smartphone-based GPS/INS positioning algorithms, we use only the GPS receiver and digital compass without INS sensors. This makes it possible to offer more accurate positioning results and to save more energy. However, GPS receivers and digital compasses on smart-phones may continue to experience positional errors due to multi-path fading and disturbances in GPS signals and magnetic sources. Therefore, we propose an enhanced vehicle positioning method that provides more reliable localization results by fusing measurements from GPS receiver and digital compass based on a Bayesian filter, called a simplified Kalman filter (SKF). Compared to existing Bayes filters, such as Kalman filter (KF), unscented Kalman filter (UKF), and particle filter (PF), while the SKF is simple and intuitive to be implemented, it can achieve competitive positioning accuracy with less computational cost. Experimental results through various road configurations using the smartphone and test vehicle in real environments show that the SKF-based vehicle localization scheme can achieve about 92% higher energy-efficiency and about 31 % higher positioning accuracy than GPS/INS localization methods based on the KF, UKF, and PF.

A New Method of Improving the Azimuth in Mountainous Terrain by Skyline Matching

Augmented reality (AR) applications have a serious problem with the accuracy of the azimuth angle provided by mobile devices. The fusion of the digital magnetic compass (DMC), accelerometer and gyroscope gives the translation and rotation of the observer in 3D space. However, the precision is not always appropriate since DMC is prone to interference when using it near metal objects or electric currents. The silhouette of ridges separates the sky from the terrain and forms the skyline or horizon line in a mountainous scenery. This salient feature can be used for orientation. With the camera of the device and a digital elevation model (DEM) the correct azimuth angle could be determined. This study proposes an effective method to adjust the azimuth by identifying the skyline from an image and matches it with the skyline of the DEM. This approach does not require manual interaction. The algorithm has also been validated in a real-world environment.

Digital Magnetic Compass Integration with Stationary, Land-Based Electro-Optical Multi-Sensor Surveillance System.

Multi-sensor imaging systems using the global navigation satellite system (GNSS) and digital magnetic compass (DMC) for geo-referencing have an important role and wide application in long-range surveillance systems. To achieve the required system heading accuracy, the specific magnetic compass calibration and compensation procedures, which highly depend on the application conditions, should be applied. The DMC compensation technique suitable for the operation environment is described and different technical solutions are studied. The application of the swinging procedure was shown as a good solution for DMC compensation in a given application. The selected DMC was built into a system to be experimentally evaluated, both under laboratory and field conditions. The implementation of the compensation procedure and magnetic sensor integration in systems is described. The heading accuracy measurement results show that DMC could be successfully integrated and used in long-range surveillance systems providing required geo-referencing data.

Исследование, изготовление корабельного цифрового магнитного компаса и применение фильтра Калмана для фильтрации зашумленной информации данного компаса.

Исследование, изготовление корабельного цифрового магнитного компаса и применение фильтра Калмана для фильтрации зашумленной информации данного компаса.

Using signals from GLONASS/GPS navigation systems to correct the readings of a digital magnetic compass

The article describes the results obtained from research, manufacture and quality improvement of an inexpensive digital magnetic compass system. Given that the receivers of the global navigation satellite systems (GNSS) signals are not expensive, in order to increase the accuracy and reliability of the compass, in this paper, the authors propose a method to use the signal of the GNSS global positioning system to compare and adjust the azimuth value of the Digital magnetic compass (DMC).

Reliable location aware and Cluster-Tap Root based data collection protocol for large scale wireless sensor networks

Designing a stable and energy efficient routing protocol for mobility based Wireless Sensor Networks (WSNs) is a great challenge, because frequent link changes or failures make the network topology unstable. In this paper, we propose a Cluster-Tap Root based Data Collection (CTRDC) protocol which produces a highly stable and reliable routing path for data transmission. In cluster formation phase, the Cluster Heads (CHs) are elected in a distributed manner in two levels: (i) Tentative CH (TCH) candidate selection based on node's residual energy (ii) a fuzzy logic based final CHs selection which is obtained by using node speed, number of neighbor nodes, and average connection time. This distributed CH selection ensures the two hop distance between the CHs. Besides, we introduce the tap root principle for constructing a route between the CHs and Base Station (BS), in which it uses a minimal number of sensor nodes (i.e., O(n2)), whereas the tree topology utilized O(2n) nodes and n denotes the depth of the tap root. It is observed that it lessens the path setup delay, interference, collision, and also avoids the redundant searching of nodes in the same place. In addition, an effective localization method is proposed, in which all the sensor nodes are equipped with Digital Magnetic Compass (DMC). The DMC is used to measure the moving direction (azimuth) of the mobile node, thus the sensor node finds its location in the sensing area with the help of two anchor nodes. From the simulation results, it is showed that the proposed CTRDC protocol provides better performance in terms of Packet Delivery Ratio (PDR), throughput, Average Energy Consumption (AEC), Average End-to-End Delay (AEED) and control overhead as compared to MBC, OZEEP, and ES-WCA. Additionally, CTRDC adapts to mobility scenario, where the reliability, fault tolerance, scalability, and stability of the networks are enhanced, even if it gets frequent link failures.

Design and Development of Compact Hand Held Target Acquisition Device

A compact, lightweight hand held target acquisition device, comprising of an infra red imager, colour CCD camera, eye safe laser range finder, global positioning system and digital magnetic compass has been developed. The aim was to develop a compact, lightweight, modular and man-portable multi function electro-optical system with a recognition range of 1 km for vehicles and 500 m for human movement enabling day and night time surveillance, target ranging capability, ability to generate coordinates of the operator and estimation of target coordinates. Hand Held target acquisition device operates on 12 V DC, has integrated signal processing for all the sensors and display electronics with a weight of 3 kg. Overview of the system, design methodology, performance modeling, range simulation of both the IR imager and colour CCD camera and field results have been presented.

Intelligent Mobile Robots

Background/Objectives: A new method is devised to build a collection of wheeled robots that are capable of communicating with each other and mapping a maze in a minimum amount of time by dividing the work between two or more robots. Methods/Statistical analysis: The design and implementation of multiple mapping robots are undertaken using Digital Magnetic Compass, Ultrasonic Sensor, and Arduino. The designed robots use a metric, world-centric approach for mapping algorithm. Robots follow the wall while continuously sending its co-ordinates to the base station. The base station or map monitor has PC with NRF module link connected with mobile robots, and the map is plotted on a GUI. The proposed approach is a low-cost robotic application to solve SLAM problem. Findings: The proposed work is an approach for mapping and exploration of mobile robots. Initially, each robot explores the environment by themselves, and later they communicate with other robots by exchanging sensor information. Magnetometer readings help the robot to estimate their relative location. The predictive models are updated by the robots based on their exploration of the environment. Based on the experiments done it is proved that mapping and map merging decisions made using multiple robots provided better performance than using some other technique which uses a single robot for exploration. The robots communicate with each other very often and verify their location to avoid false-acceptance map matches. In case the robots are about to meet at a point known as meeting point, these robots have prior information about their relative locations, and henceforth these robots can combine their data into a map named as shared map. SLAM technique is used to find out the uncertainty in the mapping of individual robots and merging the map provided by each robot. The coordination of robots and estimation of other robot's location is done using the shared map. The robots used their wireless network available with them for exchanging information with each other. In all official runs, all the robots successfully mapped, merged the maps and explored the environment. The maps produced by the robots during each run looked alike which indicates a high level of accuracy of the system. Application/Improvements: This concept can be implemented for exploration on planets or on rescue missions It can be made further into a SWARM system in which the robots has a very high level of intelligence..

Error-separation method for the calibration of magnetic compass

Magnetic compass is widely used in the navigation system by measuring the orientation of the earth’s magnetic field and must be calibrated before used to eliminate the errors caused by the bias, misalignment, inconsistence in sensitivity, etc. In this paper, the fully digital magnetic compass was developed by using magnetic-induced magnetometers and MEMS accelerometers and the error-separation method based on a non-magnetic three-axis rotation platform was presented to calibrate the magnetic compass. The parameters about misalignment and non-orthogonality of the sensor axes and the response curve of the sensor’s output signals to earth magnetic fields were obtained. Furtherly, the sensitivity of magnetometers and the bias from the offset and hard-magnetic interference were estimated according to the response curve. The independent effect of non-orthogonality and misalignment, bias and inconsistence in sensitivity on the heading error can be evaluated with the error-separation method, respectively. After calibration, the maximum heading error of magnetic compass was about 0.4° when both pitch angle and roll angle were in the range from −60° to 60°, indicating the error-separation method is effective and efficient to calibrate magnetic compasses.

North Finding System using Multi-Position Method with a 2-Axis Rotray Table for a Mortar

North-finding techniques involve detecting and calculating the azimuth angle, thus determining north using various kinds of sensors. North identification can be accomplished through the use of a digital magnetic compass. However, the accuracy of a magnetic sensor is easily degraded by spatial and temporal distortions due to a ferrous material or electromagnetic interference. Moreover, GPS-based north-finding systems (NFSs) can accurately determine the azimuth by two separated GPS antennas. However, this still has a practical limitation in jamming or indoor environments. Therefore, an inertial NFS has been developed to replace the classic equipment used in estimating the fire direction of hand-carried projectile weapons such as with mortars. To improve the precision of seeking north with a middle grade gyro, a multi-position method is implemented. Using only a single fiber-optic gyroscope and two MEMS accelerometers on a rotary platform, the north orientation is accurately found by observing the horizontal component of the earth’s rotation vector. With a minimum number of inertial sensors on a manual rotary platform, the NFS can be compact, light-weight, low-cost, and robust enough for easily portable mortar. Using additional auxiliary information, which can be obtained by magnetic sensors, the time for locating north can be dramatically reduced. The test results compared with the navigation grade inertial navigation system show that a single digit mrad heading accuracy can be achieved. The operability of NFS mounted beside a mortar was tested in the field, in which the reference positions were acquired by differential GPS. To insure the durability in gun-fire shock, the drop-tower test was performed based on the shock profile measured in real mortar fire.

Design and Implementation of Mapping Robot using Digital Magnetic Compass and Ultrasonic Sensor

Design and Implementation of Mapping Robot using Digital Magnetic Compass and Ultrasonic Sensor

Heading Measurement Based on Ultrasonic and Magnetic Compass

Describes briefly ultrasonic positioning system (UPS) and digital magnetic compass (DMC) heading measurement principle,analyzed the advantages and disadvantages of each option. To improve the accuracy of the heading measurement, As the theoretical basis of adaptive Kalman filter, designed a kind of ups and dmc integrated navigation system. Based on both real measurement data, made a simulation experiment and confirmed the feasibility of the navigation system.

Finding Declinations Using Lookup Tables and Bilinear Interpolation in the Application of Digital Magnetic Compass

This paper describes Declination interpolation method in the application of Digital Magnetic Compass(DMC) with small capacity memory for relatively low-priced system. The purpose of this study is to find accurate declination values using Declination Lookup Table(DLT) and Secular Variation Table(SVT) with the Bilinear interpolation method having four points data only. World Magnetic Model with Gauss coefficients produced by NOAA is used in the calculation of DLT and SVT at desired years. To verify the applicability of the proposed method, the simulation tests and the error analysis are carried out in this work. As results from tests, the interpolation error is within 0.01 degree that is much enough to implement high accurate DMC comparing with commercial DMCs on the market. In summary, the declination interpolation method, proposed in this study, can be useful in the application of DMC.

A new calibration method for tri-axial field sensors in strap-down navigation systems

This paper presents a novel calibration method for tri-axial field sensors, such as magnetometers and accelerometers, in strap-down navigation systems. Strap-down tri-axial sensors have been widely used as they have the advantages of small size and low cost, but they need to be calibrated in order to ensure their accuracy. The most commonly used calibration method for a tri-axial field sensor is based on ellipsoid fitting, which has no requirement for external references. However, the self-calibration based on ellipsoid fitting is unable to determine and compensate the mutual misalignment between different sensors in a multi-sensor system. Therefore, a novel calibration method that employs the invariance of the dot product of two constant vectors is introduced in this paper. The proposed method, which is named dot product invariance method, brings a complete solution for the error model of tri-axial field sensors, and can solve the problem of alignment in a multi-sensor system. Its effectiveness and superiority over the ellipsoid fitting method are illustrated by numerical simulations, and its application on a digital magnetic compass shows significant enhancement of the heading accuracy.

Research on a Combined Directional Instrument of DMC and Gyro for Vehicles

In the view of the disadvantages brought by DMC(digital magnetic compass) and gyro when they are used separately, a combined directional instrument composed by a 3-axes digital magnetic compass and a 3-axes MEMS gyro for vehicles is introduced, which is less influenced to the magnetic field interference and random drift. In the abnormal magnetic field, the MEMS gyro is used for correcting the heading angle of DMC. The experiment data shows that this instrument can output a stable and high-precision heading angle. It can be used to provide heading angle for vehicles.

Multitarget Three-Dimensional Indoor Navigation on a PDA in a Wireless Sensor Network

The development of wireless sensor networks has greatly encouraged the use of sensors in the location tracking industry by introducing various researches have exploited the high accuracy of position determination using distinct tracking models predominantly as low-cost solutions. This paper presents an indoor tracking model that uses the depreciated IEEE 802.15.4 compliant radio frequency and immersive 3-D graphics to present data in an extraordinary way. Our motivation is to manipulate the erratic and unstable received signal strength indicator (RSSI) signal to deliver stable and precise position information in an indoor environment. A sensor (target node) receives RSSI signals from at least three designated sensors (reference nodes) and predicts the location on the basis of trilateration. The nature of a limited indoor space is such that there is signal fluctuation and noise in radio-frequency transmission between sensors. In light of this issue, we proposed an accuracy refinement algorithm to filter out noise in the received RSSI signals. To display useful 3-D information, an additional feature is required in conjunction with the user's position to illustrate the view of the user. Therefore, a digital magnetic compass is used to determine the orientation of the target in real- time and a sensor transmits DMC data to a receiver in wireless transmission.

Simultaneous localization and mapping of a wheel-based autonomous vehicle with ultrasonic sensors

An autonomous vehicle should recognize its position when the vehicle is moving, otherwise the vehicle would not operate correctly. In addition, the “kidnapping“ problem sometimes appears when the vehicle starts at an unknown position. The theoretical basis of the solution to this problem, known as simultaneous localization and mapping (SLAM), is now well understood. A number of approaches to SLAM have appeared in the recent literature. The SLAM algorithm consists of two methods. One is a map-building method that makes a map to represent the environment. The other is a mapping method to compute the position of the vehicle in absolute coordinates. However, it is difficult to apply the SLAM algorithm to an actual autonomous vehicle because it needs a certain amount of operating time. In this article, we explain the use of ultrasonic sensors for detecting obstacles in corridors, and a digital magnetic compass, a gyro, and two encoders for immediate localization. Experiments showed that this algorithm can be executed with a high degree of accuracy and reliability in an unknown environment. This algorithm could also solve the “kidnapping“ problem in a fast operating time.

3D virtual viewer on mobile device for wireless sensor network-based RSSI indoor tracking system

Most of recent research on indoor location sensing information has been presented in dull and unpleasant 2D image standard. This paper focuses on high precision three-dimensional received signal strength indication (RSSI)-based location information in an interactive virtual reality on PDA. The developed system operates by capturing and extracting signal strength information at multiple pre-defined reference nodes to provide information in the area of interest, thus updating user's location in 3D indoor virtual map. Virtual Reality Modeling Language (VRML), which specifically developed for 3D objects modeling is utilized to design 3D indoor environment. To shorten the rendering time in low-power processing PDA, culling algorithm is introduced to render only essential 3D objects needed for navigation. Meanwhile, RSSI accuracy refinement algorithm introduced reduces noises in signal strength mainly caused by the effect of reflecting and attenuating objects in the indoor environment. PDA user's position is computed with respect to VRML specification, synchronized with real indoor environment. Moreover, interpolating of digital magnetic compass shows real-time dynamic orientation processing, generated projected 3D view to be displayed on PDA screen.

전자 나침반과 초음파 센서를 이용한 이동 로봇의 Simultaneous Localization and Mapping

전자나침반(DMC)은 실내의 전자기적 요소나 강한 자성체 건물구조에서는 쉽게 방해를 받던 나침반보다 실내에서 간섭에 강한 특징을 가지고 있다. 그리고 초음파 센서는 물체와의 거리를 계산해 줄뿐만 아니라 값싼 센서로서 경제적인 이점을 가지고 있어 Simultaneous Localization and Mapping(SLAM)에서 많이 사용하고 있다. 본 논문에서는 자율 이동 로봇의 구동에서 전자나침반과 초음파 센서를 이용한 SLAM의 구현에 대해 연구하였다. 로봇의 특성상 한정된 센싱 데이터만으로 방향과 위치를 파악하고 그 데이터 값으로 가능한 빠르게 위치 측정을 하여야 한다. 그러므로 자율 이동 로봇에서의 SLAM 적용함으로 위치측정의 구현과 지도 작성을 수행한다. 그리고 SLAM 구현상의 주된 연구 중의 하나인 Kid Napping 문제에 중점을 두고 연구한다. 특히, 위치 측정의 구현을 수행하기 위한 데이터의 센싱 방법으로 초음파 센서를 사용하였고 비슷한 위치의 데이터 값이 주어지거나 사전 정보 없는 상태에서는 로봇의 상태를 파악하기 위해서 전자 나침반을 사용하였다. 그래서 자율 이동 로봇의 위치를 정확하게 측정하기 위해서 활용하였다. Digital Magnetic Compass(DMC) has a robust feature against interference in the indoor environment better than compass which is easily disturbed by electromagnetic sources or large ferromagnetic structures. Ultrasonic Sensors are cheap and can give relatively accurate range readings. So they ate used in Simultaneous Localization and Mapping(SLAM). In this paper, we study the Simultaneous Localization and Mapping(SLAM) of mobile robot in the indoor environment with Digital Magnetic Compass and Ultrasonic Sensors. Autonomous mobile robot is aware of robot's moving direction and position by the restricted data. Also robot must localize as quickly as possible. And in the moving of the mobile robot, the mobile robot must acquire a map of its environment. As application for the Simultaneous Localization and Mapping(SLAM) on the autonomous mobile robot system, robot can find the localization and the mapping and can solve the Kid Napping situation for itself. Especially, in the Kid Napping situation, autonomous mobile robot use Ultrasonic sensors and Digital Magnetic Compass(DMC)'s data for moving. The robot is aware of accurate location By using Digital Magnetic Compass(DMC).