Digital Compass Research Articles

Reliability considerations of multi-sensor multi-network pedestrian navigation

This study discusses a simple multi-sensor multi-network positioning system that integrates global positioning satellite (GPS) measurements, accelerometers and a digital compass with wireless network localisation utilising a pedestrian motion model and dead reckoning. The feasibility of the multi-technology system for seamless outdoor to indoor pedestrian navigation is discussed with the emphasis on reliability issues and adaptability requirements. The multi-sensor multi-network positioning system is developed for challenging navigation environments such as indoors and deep urban canyons. This study considers how to estimate and improve such a multi-sensor multi-network system's reliability and estimate its accuracy. An outdoor to indoor pedestrian test is conducted. Adaptive filtering performance of the multi-technology solution as well as general measurement quality monitoring and error detection when an over-determined solution is at hand is shown. Reliability estimation utilising adaptation in the form of environment detection to estimate the final positioning accuracy is also presented.

Wireless Traffic Light Controller for Emergency Vehicle through XBee and Basic Stamp Microcontroller

The existing traffic light systems are unable to detect the presence of emergency vehicles on the road, especially in the emergency situation. The delay cause due to this situation can affect the life of the person in need of the emergency vehicles while delivering ther best service to the society. A wireless traffic light controller can resolve this problem. With a certain operating range (80m-1500m) the receiver and transmitter can correspond to each other to enable green light on the path of the travelling emergency vehicles. A simple approach using this method is done by using two wireless X-Bee modules, Basic Stamp Microcontroller and a Digital Compass. Upon using this system, the delay caused waiting for the green light can be reduced. This reduction in delay can increase the efficiency of the emergency vehicles and have a better potential to safe the life of person in need of the emergency vehicles service.

Collective Discovery of Geographic Locations of FrequentlyPhotographed Objects Only using the Metadata of Digital Photographs

In this paper, we propose an algorithm to classify a set of digital photographs by location of frequently photographed objects. The location is estimated by collective intelligence approach based on a collection of intersections of camera vectorsofthe metadatawhichaphotograph records.Inemergency,arescueteamneeds informationabouttheroadtoits disaster area as quick as possible. One of the best solutions for this purpose is an information sharing system between the refugees and the rescue team who share images takenby the refugees. Forbuilding this system, the following2 difficulties are known. Firstly, this system should not inhibit refugee's evacuation behavior while it engages in this sharing system. Secondly, the huge amount of disorganized images received is useless for the rescue team who has not enough time and other resources. The images should be categorized quick and adequately. In this paper, we propose a new classification method of images by geographic location of objects taken by them by collective intelligence. We only use metadata of digital image for this quick classification, namely, time to shoot, the latitude, the longitude and the bearing of its camera. Our method can accept consumer’sdigital cameraand smartphonewhichhasalowendGPSunit and digital compass. Also, refugees need not to input any more information about objects taken than the photograph while name or location of objects taken have to be inputed in traditional works. In our method, the location of objects taken is estimated by an algorithm based on intersections of camera vectors automatically. The algorithm is confirmed by a series of experiments which use actual photographs taken by a broadly using smartphone.

On the need for a reputation system in mobile phone based sensing

The continual advancement in semiconductor technology has enabled vendors to integrate an increasing number of sensors, e.g., accelerometer, gyroscope, digital compass, high resolution cameras and others, in modern mobile phones. Combining with the ever expanding market penetration of mobile phones, the onboard sensors are driving the sensing community towards a new paradigm called participatory sensing in which ordinary citizens voluntarily collect and share information from their local environment using personal mobile devices. The inherent openness of this platform is a double-edged sword. While encouraging user participation on the one hand, it also makes it easy to contribute corrupted data. As such, data trustworthiness becomes a key issue which needs to be addressed to ensure sustainable development of this emerging paradigm. In this paper, we propose a reputation system in which a reputation score is calculated for each device as a reflection of the trustworthiness of its sensor data. We adopt the Gompertz function as a fundamental building block of our system, since it is better suited to deal with the unique characteristics of participatory sensing. We present an application-agnostic implementation of the system, which can work with a wide variety of participatory sensing applications. We evaluate the performance of our reputation system in the context of two real-world participatory sensing applications. Our results show that the proposed reputation system outperforms existing solutions by up to a factor of six.

스마트폰의 현황 분석을 통한 상황인식서비스의 발전방향 제시

일상생활에 미치는 영향이 확산되고 있는 상황인식서비는 위치기반서비스와 소셜네트워크서비스로 분류되며, 스마트폰의 GPS 및 전자나침반 기술의 정확도에 따라 상황인식서비스 품질이 달라질 수 있다. 본 연구에서는 상황인식서비스를 이용할 때 가장 중요한 단초가 될 수 있는 GPS, 전자나침반(Digital Compass), 무선통신, 공간정보(Geospatial Web)를 활용함에 있어서의 위치적 정확도에 대하여 분석하였다. 스마트폰을 이용한 위치 및 방향 결정 정확도 실험 결과 실외에 비하여 낮은 실내 위치 및 방향 정확도와 플랫폼으로 활용되는 공간정보가 갖고 있는 오차에 의해 상황인식서비스 이용 시 정확한 정보를 제공 받지 못하는 문제점이 발생하는 것으로 나타났다. 실내 위치 결정 정확도 향상 방안으로 Wi-Fi를 이용한 측위 방법 등이 있으나 실외에서 사용하는 GPS에 비해 많은 보완 사항이 있는 것으로 나타났으며, 상황인식서비스의 플랫폼으로 활용되는 공간정보의 품질 향상을 위하여 DSM을 이용해 폐색영역을 보정한 실감 정사영상의 제작이 필요한 것으로 판단된다. Situation awareness services which increasingly expand their influence in everyday life can be classified into location-based service and social network service. Their quality of service (QoS) can be differed based on the location accuracy of smart phones and accuracy of directional recognition technology. This study was conducted to analyze GPS, digital compass, radio communication, and geospatial web information which can provide a clue in using the situation aware services based on lab experiments and surveys. According to the result of lab experiment on accuracy of determining location / direction with smart phones, owing to inherent lack of indoor accuracy in determining position and direction, as well as errors in spatial data used as platform, it was found that devices were not provided with sufficiently accurate data when using the situation aware services indoors compared to outdoors. To enhance accuracy of determining indoor positions, there are several methods including location metering based on Wi-Fi, which had several problems compared with GPS used in outdoor environment. Thus, it was determined that more study would be necessary to solve these issues.

A calibration approach based on Takagi–Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi–Sugeno (TS) fuzzy model. TS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on TS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated TS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the TS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests.

LifeMap: A Smartphone-Based Context Provider for Location-Based Services

LifeMap, a smartphone-based context provider operating in real time, fuses accelerometer, digital compass, Wi-Fi, and GPS to track and automatically identify points of interest with room-level accuracy.

Sensor-Assisted Video Encoding for Mobile Devices in Real-World Environments

In this paper, we present a comprehensive study on sensor-assisted video encoding (SaVE) schemes for video capturing on mobile devices in real-world environments. Our purpose is to reduce the computational complexity of video encoding by leveraging sensors that are increasingly available on mobile devices, e.g., accelerometers and digital compasses. Motion estimation is a key component of video encoding. In this paper, SaVE calculates the rotational movement of a camera (on mobile devices) and then infers the global motion in the camera imager. SaVE subsequently employs the estimated global motion as predictors to simplify motion estimation algorithms for state-of-the-art H.264/AVC video coding. We have constructed a prototype of SaVE and evaluated its performance with a pair of accelerometers, a digital compass, and their combination. Our experimental results show that SaVE can significantly reduce the computations of motion estimation while achieving equal or better video quality. Our results also show that SaVE has a strong noise-resistant capability. Therefore, it can be practically employed in real-world environments.

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.

Robot Self-localization with Optimized Error Minimizing for Soccer Contest

This paper proposed an integrated solution for robot self-localization in the RoboCup middle size league. Firstly, a kind of radial scan-lines are introduced to preprocess the images from the omni-directional camera so as to reduce the computational load and improve efficiency. The key points of this algorithm are minimizing the errors between the mark points and the detect points. In order to improve the self-location performance and reduce the effect by the dithering image, an optimized approach was presented and the extended Kalman filter was utilized to fuse visual information, odometry information and digital compass data. Secondly, before applying this approach into our robots, we built the simulate environment and compared the result to the existing particle filtering approach with 200 particles. Simulation result showed this approach is computational efficient and precise. Our method is computationally cheaper than the particle filtering approach. Finally, we tested the approach in the real RoboCup middle size league robot contest field. The experiments showed the optimized error minimizing self-localization provided high level capabilities.

Indoor radio location algorithm using empirical propagation models and probability distribution heuristics

Research is conducted at the Budapest University of Technology in the field of indoor positioning using radio waves, with practical application issues in focus. Our goal is to enhance and combine existing algorithms and create an implementation that is efficient enough to enable real-time operation in 3D space in multi-level office environments while retaining the accuracy of more complex systems. The proposed solution is based on proven empirical propagation models (the Motley-Keenan Model and the New Empirical Model of Cheung, Sau and Murch), with the ability to augment and refine with surveyed radio fingerprint data. The propagation model described in this paper can be used to generate estimated signal strength patterns for locations that were left out of the survey; and the values coming from the two different sources can be further handled in a common way. An algorithm is proposed to calculate a probability distribution over the floor plan using these expected values and the positioning-time measurements. The results from this location algorithm are combined with other probability distributions, generated by heuristics such as the distribution of walls, previous walking directions and typical indoor movement patterns, as well as data from G-sensors and digital compasses built into modern handheld devices. Other real-world issues are investigated like reaction to changes in the placement of radio beacons, and the comparability of various devices with different signal characteristics. The proposed algorithm can achieve an average positioning error of 3 metres in a common office environment using fingerprinting data, and errors are only about 50%greater when relying solely on simulated signal strength values.

Locating a compact odor source using a four-channel insect electroantennogram sensor

Here we demonstrate the feasibility of using an array of live insects to detect concentrated packets of odor and infer the location of an odor source (∼15 m away) using a backward Lagrangian dispersion model based on the Langevin equation. Bayesian inference allows uncertainty to be quantified, which is useful for robotic planning. The electroantennogram (EAG) is the biopotential developed between the tissue at the tip of an insect antenna and its base, which is due to the massed response of the olfactory receptor neurons to an odor stimulus. The EAG signal can carry tens of bits per second of information with a rise time as short as 12 ms (K A Justice 2005 J. Neurophiol. 93 2233–9). Here, instrumentation including a GPS with a digital compass and an ultrasonic 2D anemometer has been integrated with an EAG odor detection scheme, allowing the location of an odor source to be estimated by collecting data at several downwind locations. Bayesian inference in conjunction with a Lagrangian dispersion model, taking into account detection errors, has been implemented resulting in an estimate of the odor source location within 0.2 m of the actual location.

RANCANG BANGUN PERANGKAT LUNAK SISTEM AUTO TRACKING SATELLITE ANTENNA MOBILE MENGGUNAKAN METODE AZIMUT-ELEVASI DAN KOREKSI MODEM

Software Design of Mobile Antenna for Auto Satellite Tracking Using Modem Correction and Elevation Azimuth Method. Pointing accuracy is important in satellite communication. Because the satellite’s distance to the surface of the earth's satellite is so huge, 1 degree of pointing error will make the antenna unable to send data to satellites. To overcome this, the auto-tracking satellite controller is made. This system uses a microcontroller as the controller, with the GPS as the location indicator of the antenna, a digital compass as the beginning of antenna pointing direction, a rotary encoder as azimuth and elevation censor, and a modem to see Eb/No signal. The microcontroller uses serial communication to read the input. Thus, the programming should be focused on the Universal Asynchronous Receiver/Transmitter (UART) and serial communication software UART. This controller has 2 phases in the process of tracking satellites. The early stage is the elevation-azimuth method, in which with input from the GPS and digital compass, the position of satellites (both coordinates and height) is stored in the microcontroller. The controller will measure the elevation and azimuth angle, then it will move the antenna according to the antenna azimuth and elevation angle. The next stage is correction modem, in which the controller only uses the modem as the input, and antenna movement is set up to obtain the largest value of Eb/No signal. The results of the controller operation show that there is a change in the value of the original input level from -81.7 dB to -30.2 dB with end of Eb/No value reaching 5.7 dB.

A survey of mobile phone sensing

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.

가속도 센서를 이용한 무선 센서 네트워크하에서의 위치 인식 알고리즘

노드들 모두가 움직이는 환경에서 센서 노드는 통신반경 안의 앵커 노드 위치정보를 수신 받아 자신이 이동한 거리와 방향만큼 수신한 앵커 노드 위치정보를 수정하여 자신의 메모리에 저장하고, 3개 이상이 되면 삼변 측량에 의해 localization을 수행하여 자신의 위치를 결정한다. 일정한 거리를 유지하고 노드들이 같은 방향으로 움직이는 환경에서는 센서 노드가 1홉 범위에서 절대좌표를 가진 앵커 노드를 3개 이상 만날 확률이 적다. 만약 센서 노드가 3개 이상의 비콘 정보로 자신의 위치를 추정하였다고 하여도 시간이 경과하면서 가속도기와 디지털 나침반의 각 <TEX>${\theta}$</TEX> 오차가 지속적으로 적용되어 오차범위는 커지고 추정된 위치도 신뢰받지 못한다. Dead reckoning 기술은 GPS가 동작하지 않는 곳에서 보조적인 위치 추적 항법 기술로 사용되고 있는데 가속도 센서와 디지털 나침반으로 노드가 움직인 거리와 방향을 알면 자신의 위치를 추정할 수 있다. 위치 인식 알고리즘은 Dead reckoning 을 이용한 위치인식 기법으로 모든 노드가 전방향성 안테나를 장착하고, 가속도기와 디지털 나침반으로 자신이 이동한 거리와 이동 방향을 알 수 있다고 가정한다. Matlab을 이용하여 시뮬레이션한 결과 다른 기법(MCL,DV-distance)들 보다 우수함을 증명하였다. In an environment where all nodes move, the sensor node receives anchor node's position information within communication radius and modifies the received anchor node's position information by one's traveled distance and direction in saving in one's memory, where if there at least 3, one's position is determined by performing localization through trilateration. The proposed localization mechanisms have been simulated in the Matlab. In an environment where certain distance is maintained and nodes move towards the same direction, the probability for the sensor node to meet at least 3 anchor nodes with absolute coordinates within 1 hub range is remote. Even if the sensor node has estimated its position with at least 3 beacon information, the angle <TEX>${\theta}$</TEX> error of accelerator and digital compass will continuously apply by the passage of time in enlarging the error tolerance and its estimated position not being relied. Dead reckoning technology is used as a supplementary position tracking navigation technology in places where GPS doesn't operate, where one's position can be estimated by knowing the distance and direction the node has traveled with acceleration sensor and digital compass. The localization algorithm to be explained is a localization technique that uses Dead reckoning where all nodes are loaded with omnidirectional antenna, and assumes that one's traveling distance and direction can be known with accelerator and digital compass. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

Managing cohort movement of mobile sensors via GPS-free and compass-free node localization

A critical problem in mobile ad hoc wireless sensor networks is each node’s awareness of its position relative to the network. This problem is known as localization. In this paper, we introduce a variant of this problem, directional localization, where each node must be aware of both its position and orientation relative to its neighbors. Directional localization is relevant for applications that require uniform area coverage and coherent movement. Using global positioning systems for localization in large scale sensor networks may be impractical in enclosed spaces, and might not be cost effective. In addition, a set of pre-existing anchors with globally known positions may not always be available. In this context, we propose two distributed algorithms based on directional localization that facilitate the collaborative movement of nodes in a sensor network without the need for global positioning systems, seed nodes or a pre-existing infrastructure such as anchors with known positions. Our first algorithm, GPS-free Directed Localization (GDL) assumes the availability of a simple digital compass on each sensor node. We relax this requirement in our second algorithm termed GPS- and Compass-free Directed Localization (GCDL). Through experimentation, we demonstrate that our algorithms scale well for large numbers of nodes and provide convergent localization over time, despite errors introduced by motion actuators and distance measurements. In addition, we introduce mechanisms to preserve swarm formation during directed sensor network mobility. Our simulations confirm that, in a number of realistic scenarios, our algorithms provide for a mobile sensor network that preserves its formation over time, irrespective of speed and distance traveled. We also present our method to organize the sensor nodes in a polygonal geometric shape of our choice even in noisy environments, and investigate the possible uses of this approach in search-and-rescue type of missions.

Development of a Low-Cost Attitude and Heading Reference System Using a Three-Axis Rotating Platform

A development procedure for a low-cost attitude and heading reference system (AHRS) with a self-developed three-axis rotating platform has been proposed. The AHRS consists of one 3-axis accelerometer, three single-axis gyroscopes, and one 3-axis digital compass. Both the accelerometer and gyroscope triads are based on micro electro-mechanical system (MEMS) technology, and the digital compass is based on anisotropic-magnetoresistive (AMR) technology. The calibrations for each sensor triad are readily accomplished by using the scalar calibration and the least squares methods. The platform is suitable for the calibration and validation of the low-cost AHRS and it is affordable for most laboratories. With the calibrated parameters and data fusion algorithm for the orientation estimation, the self-developed AHRS demonstrates the capabilities of compensating for the sensor errors and outputting the estimated orientation in real-time. The validation results show that the estimated orientations of the developed AHRS are within the acceptable region. This verifies the practicability of the proposed development procedure.

초음파센서와 RFID 시스템을 이용한 이동로봇의 맵 빌딩에 관한 연구

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

지향성 안테나를 이용한 무선 센서 네트워크에서의 위치 인식 알고리즘

The proposed algorithm to be explained in this paper is the localization technique using directional antenna. Here, it is assumed that anchor node has the ability to transfer the azimuth of each sector using GPS modules, sector antenna, and the digital compass. In the conventional sensor network, the majority of localization algorithms were capable of estimating the position information of the sensor node by knowing at least 3 position values of anchor nodes. However, this paper has proposed localization algorithm that estimates the position of nodes to continuously move with sensor nodes and traveling nodes. The proposed localization mechanisms have been simulated in the Matlab. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance). ▸Keyword : Localization, Sensor network, Antenna, Ubiquitous, Anchor ∙제1저자 : 홍성화 ∙투고일 : 2009. 10. 15, 심사일 : 2009. 11. 11, 게재확정일 : 2010. 01. 26. *동양공업전문대학 전산학부 소프트웨어공학과 112 韓國컴퓨터情報學會 論文誌(2010. 1.)

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.