117 research outputs found
Exploiting Structural Signal Information in Passive Emitter Localization
The operational use of systems for passive geolocation of radio frequency emitters poses various challenges to single sensor systems or sensor networks depending on the measurement methods. Position estimation by means of direction finding systems often requires complex receiver and antenna technique. Time (Difference) of Arrival methods (TDOA, TOA) are based on measurements regarding the signal propagation duration and generally require broadband communication links to transmit raw signal data between spatially separated receivers of a sensor network. Such bandwidth requirements are particularly challenging for applications with moving sensor nodes. This issue is addressed in this thesis and techniques that use signal structure information of the considered signals are presented which allow a drastic reduction of the communication requirements. The advantages of using knowledge of the signal structure for TDOA based emitter localization are shown using two exemplary applications. The first case example deals with the passive surveillance of the civil airspace (Air Traffic Management, ATM) using a stationary sensor network. State of the art airspace surveillance is mainly based on active radar systems (Primary Surveillance Radar, PSR), cooperative secondary radar systems (Secondary Surveillance Radar, SSR) and automatic position reports from the aircraft itself (Automatic Dependent Surveillance-Broadcast, ADS-B). SSR as well as ADS-B relies on aircrafts sending transponder signals at a center frequency of 1090 MHz. The reliability and accuracy of the position reports sent by aircrafts using ADS-B are limited and not sufficient to ensure safe airspace separation for example of two aircrafts landing on parallel runways. In the worst case, the data may even be altered with malicious intent. Using passive emitter localization and tracking based on multilateration (TDOA/hyperbolic localization), a precise situational awareness can be given which is independent of the content of the emitted transponder signals. The high concentration of sending targets and the high number of signals require special signal processing and information fusion techniques to overcome the huge amount of data. It will be shown that a multilateration network that employs those techniques can be used to improve airspace security at reasonable costs. For the second case, a concept is introduced which allows TDOA based emitter localization with only one moving observer platform. Conventional TDOA measurements are obtained using spatially distributed sensor nodes which capture an emitted signal at the same time. From those signals, the time difference of arrival is estimated. Under certain conditions, the exploitation of signal structure information allows to transfer the otherwise only spatial into a spatial and temporal measurement problem. This way, it is possible to obtain TDOA estimates over multiple measurement time steps using a single moving observer and to thus localize the emitter of the signals. The concept of direct position determination is applied to the single sensor signal structure TDOA scheme and techniques for direct single sensor TDOA are introduced. The validity and performance of the presented methods is shown in theoretical analysis in terms of Cramér-Rao Lower Bounds, Monte-Carlo simulations and by evaluation of real data gained during field experiments
A Stationless Bikeshare Proof of Concept for College Campuses
Bikeshares promote healthy lifestyles and sustainability among commuters, casual
riders, and tourists. However, the central pillar of modern systems, the bike station,
cannot be easily integrated into a compact college campus. Fixed stations lack the
flexibility to meet the needs of college students who make quick, short-distance trips.
Additionally, the necessary cost of implementing and maintaining each station prohibits
increasing the number of stations for user convenience. Therefore, the team developed a
stationless bikeshare based on a smartlock permanently attached to bicycles in the
system. The smartlock system design incorporates several innovative approaches to
provide usability, security, and reliability that overcome the limitations of a station
centered design. A focus group discussion allowed the team to receive feedback on the
early lock, system, and website designs, identify improvements and craft a pleasant user
experience. The team designed a unique, two-step lock system that is intuitive to operate
while mitigating user error. To ensure security, user access is limited through near field
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communications (NFC) technology connected to a mechatronic release system. The said
system relied on a NFC module and a servo working through an Arduino microcontroller
coded in the Arduino IDE. To track rentals and maintain the system, each bike is fitted
with an XBee module to communicate with a scalable ZigBee mesh network. The
network allows for bidirectional, real-time communication with a Meteor.js web
application, which enables user and administrator functions through an intuitive user
interface available on mobile and desktop. The development of an independent
smartlock to replace bike stations is essential to meet the needs of the modern college
student. With the goal of creating a bikeshare that better serves college students, Team
BIKES has laid the framework for a system that is affordable, easily adaptable, and
implementable on any university expressing an interest in bringing a bikeshare to its
campus
Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation
Autonomous harvesting and transportation is a long-term goal of the forest
industry. One of the main challenges is the accurate localization of both
vehicles and trees in a forest. Forests are unstructured environments where it
is difficult to find a group of significant landmarks for current fast
feature-based place recognition algorithms. This paper proposes a novel
approach where local observations are matched to a general tree map using the
Delaunay triangularization as the representation format. Instead of point cloud
based matching methods, we utilize a topology-based method. First, tree trunk
positions are registered at a prior run done by a forest harvester. Second, the
resulting map is Delaunay triangularized. Third, a local submap of the
autonomous robot is registered, triangularized and matched using triangular
similarity maximization to estimate the position of the robot. We test our
method on a dataset accumulated from a forestry site at Lieksa, Finland. A
total length of 2100\,m of harvester path was recorded by an industrial
harvester with a 3D laser scanner and a geolocation unit fixed to the frame.
Our experiments show a 12\,cm s.t.d. in the location accuracy and with
real-time data processing for speeds not exceeding 0.5\,m/s. The accuracy and
speed limit is realistic during forest operations
Wireless capsule gastrointestinal endoscopy: direction of arrival estimation based localization survey
One of the significant challenges in Capsule Endoscopy (CE) is to precisely determine the pathologies location. The localization process is primarily estimated using the received signal strength from sensors in the capsule system through its movement in the gastrointestinal (GI) tract. Consequently, the wireless capsule endoscope (WCE) system requires improvement to handle the lack of the capsule instantaneous localization information and to solve the relatively low transmission data rate challenges. Furthermore, the association between the capsule’s transmitter position, capsule location, signal reduction and the capsule direction should be assessed. These measurements deliver significant information for the instantaneous capsule localization systems based on TOA (time of arrival) approach, PDOA (phase difference of arrival), RSS (received signal strength), electromagnetic, DOA (direction of arrival) and video tracking approaches are developed to locate the WCE precisely. The current article introduces the acquisition concept of the GI medical images using the endoscopy with a comprehensive description of the endoscopy system components. Capsule localization and tracking are considered to be the most important features of the WCE system, thus the current article emphasizes the most common localization systems generally, highlighting the DOA-based localization systems and discusses the required significant research challenges to be addressed
Analysis of Ultra Wide Band (UWB) Technology for an Indoor Geolocation and Physiological Monitoring System
The goal of this research is to analyze the utility of UWB for indoor geolocation and to evaluate a prototype system, which will send information detailing a person’s position and physiological status to a command center. In a real world environment, geolocation and physiological status information needs to be sent to a command and control center that may be located several miles away from the operational environment. This research analyzes and characterizes the UWB signal in the various operational environments associated with indoor geolocation. Additionally, typical usage scenarios for the interaction between UWB and other devices are also tested and evaluated
An Assessment of Indoor Geolocation Systems
Currently there is a need to design, develop, and deploy autonomous and portable indoor geolocation systems to fulfil the needs of military, civilian, governmental and commercial customers where GPS and GLONASS signals are not available due to the limitations of both GPS and GLONASS signal structure designs. The goal of this dissertation is (1) to introduce geolocation systems; (2) to classify the state of the art geolocation systems; (3) to identify the issues with the state of the art indoor geolocation systems; and (4) to propose and assess four WPI indoor geolocation systems. It is assessed that the current GPS and GLONASS signal structures are inadequate to overcome two main design concerns; namely, (1) the near-far effect and (2) the multipath effect. We propose four WPI indoor geolocation systems as an alternative solution to near-far and multipath effects. The WPI indoor geolocation systems are (1) a DSSS/CDMA indoor geolocation system, (2) a DSSS/CDMA/FDMA indoor geolocation system, (3) a DSSS/OFDM/CDMA/FDMA indoor geolocation system, and (4) an OFDM/FDMA indoor geolocation system. Each system is researched, discussed, and analyzed based on its principle of operation, its transmitter, the indoor channel, and its receiver design and issues associated with obtaining an observable to achieve indoor navigation. Our assessment of these systems concludes the following. First, a DSSS/CDMA indoor geolocation system is inadequate to neither overcome the near-far effect not mitigate cross-channel interference due to the multipath. Second, a DSSS/CDMA/FDMA indoor geolocation system is a potential candidate for indoor positioning, with data rate up to 3.2 KBPS, pseudorange error, less than to 2 m and phase error less than 5 mm. Third, a DSSS/OFDM/CDMA/FDMA indoor geolocation system is a potential candidate to achieve similar or better navigation accuracy than a DSSS/CDMA indoor geolocation system and data rate up to 5 MBPS. Fourth, an OFDM/FDMA indoor geolocation system is another potential candidate with a totally different signal structure than the pervious three WPI indoor geolocation systems, but with similar pseudorange error performance
An analysis of the impact of wireless technology on public vs. private traffic data collection, dissemination and use
Thesis (M.C.P. and S.M.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2001.Includes bibliographical references (leaves 151-154).The collection of data concerning traffic conditions (e.g., incidents, travel times, average speed, traffic volumes, etc.) on roadways has traditionally been carried out by those public entities charged with managing traffic flow, responding to incidents, and maintaining the surface of the roadway. Pursuant to this task, public agencies have employed inductive loop detectors, closed circuit television cameras, technology for tracking electronic toll tags, and other surveillance devices, in an effort to monitor conditions on roads within their jurisdictions. The high cost of deploying and maintaining this surveillance equipment has precluded most agencies from collecting data on roads other than freeways and important arterials. In addition, the "point" nature of most commonly utilized surveillance equipment limits both the variety of data available for analysis, as well as its overall accuracy. Consequently, these problems have limited the usefulness of this traffic data, both to the public agencies collecting it, as well as private entities who would like to use it as a resource from which they can generate fee-based traveler information services. Recent Federal Communications Commission (FCC) mandates concerning E-911 have led to the development of new technologies for tracking wireless devices (i.e., cellular phones). Although developed to assist mobile phone companies in meeting the FCC's E-911 mandate, a great deal of interest has arisen concerning their application to the collection of traffic data. That said, the goal of this thesis has been to compare traditional traffic surveillance technologies' capabilities and effectiveness with that of the wireless tracking systems currently under development. Our technical research indicates that these newly developed tracking technologies will eventually be able to provide wider geographic surveillance of roads at less expense than traditional surveillance equipment, as well as collect traffic information that is currently unavailable. Even so, our overall conclusions suggest that due to budgetary, institutional, and/or political constraints, some organizations may find themselves unable to procure this high quality data. Moreover, we believe that even those organizations (both public and private) that find themselves in a position to procure data collected via wireless tracking technology should first consider the needs of their "customers," the strength of the local market for traffic data, and their organization's overall mission, prior to making a final decision.by Armand J. Ciccarelli, III.M.C.P.and S.M
Bio-inspired approach for long-range underwater navigation using model predictive control
Lots of evidence has indicated that many kinds of animals can achieve goal-oriented navigation by spatial cognition and dead reckoning. The geomagnetic field (GF) is a ubiquitous cue for navigation by these animals. Inspired by the goal-oriented navigation of animals, a novel long-distance underwater geomagnetic navigation (LDUGN) method is presented in this article, which only utilizes the declination component (D) and inclination component (I) of GF for underwater navigation without any prior knowledge of the geographical location or geomagnetic map. The D and I measured by high-precision geomagnetic sensors are compared periodically with that of the destination to determine the velocity and direction in the next step. A model predictive control (MPC) algorithm with control and state constraints is proposed to achieve the control and optimization of navigation trajectory. Because the optimal control is recalculated at each sampling instant, the MPC algorithm can overcome interferences of geomagnetic daily fluctuation, geomagnetic storms, ocean current, and geomagnetic local anomaly. The simulation results validate the feasibility and accuracy of the proposed algorithm
Measuring, Modeling, and Evaluating the Spatial Properties of Northeast Oregon Forests Using Unmanned Aerial Systems
There is an ever expanding range of applications for the aerial images that unmanned aerial systems can uniquely provide. One such application is the use of high-resolution imagery for stand-level forest inventory. Inventory techniques utilizing unmanned aerial systems could be attractive where conditions demand high-resolution data, or where other aerial imagery sources are cost prohibitive. Here the effectiveness of unmanned aerial systems in this application was tested. Over the summer of 2015, a remote-controlled hexacopter equipped with a micro four thirds camera was flown over multiple 1600 meter-squared forested plots in Eastern Oregon. Additional ground-level validation measurements were collected including stem location, crown radius, and tree height. Agisoft Photoscan was used to construct 3-D point-clouds which then allowed the production of digital surface models of the stands. The first section of this project assesses the accuracy of stem locations derived from segmented imagery. The next section evaluates the accuracy of estimates for tree height, crown radius, and diameter at breast height. In the final section, various spatial metrics such as stand contagion and species mingling were compared with more commonly used metrics to see if significant correlations emerged. The utilized methods did not yield sufficiently accurate estimates for stem location or the various forest biometrics. Yet this work revealed stand density to be a significant influence on model accuracy. Finally, stand density and species diversity were found to be well correlated with the nearest neighbor and species mingling indexes, respectively, potentially supporting a complementary relationship indicating the clustering of various factors within the stand
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