3,669 research outputs found

    Modeling Selective Availability of the NAVSTAR Global Positioning System

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    As the development of the NAVSTAR Global Positioning System (GPS) continues, there will increasingly be the need for a software centered signal model. This model must accurately generate the observed pseudorange which would typically be encountered. The observed pseudorange varies from the true geometric (slant) range due to range measurement errors. Errors in range measurement stem from a variety of hardware and environment factors. These errors are classified as either deterministic or random and, where appropriate, their models are summarized. Of particular interest is the model for Selective Availability which is derived from actual GPS data. The procedure for the determination of this model, known as the System Identification Theory, is briefly outlined. The synthesis of these error sources into the final signal model is given along with simulation results

    Positioning Accuracy Improvement via Distributed Location Estimate in Cooperative Vehicular Networks

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    The development of cooperative vehicle safety (CVS) applications, such as collision warnings, turning assistants, and speed advisories, etc., has received great attention in the past few years. Accurate vehicular localization is essential to enable these applications. In this study, motivated by the proliferation of the Global Positioning System (GPS) devices, and the increasing sophistication of wireless communication technologies in vehicular networks, we propose a distributed location estimate algorithm to improve the positioning accuracy via cooperative inter-vehicle distance measurement. In particular, we compute the inter-vehicle distance based on raw GPS pseudorange measurements, instead of depending on traditional radio-based ranging techniques, which usually either suffer from high hardware cost or have inadequate positioning accuracy. In addition, we improve the estimation of the vehicles' locations only based on the inaccurate GPS fixes, without using any anchors with known exact locations. The algorithm is decentralized, which enhances its practicability in highly dynamic vehicular networks. We have developed a simulation model to evaluate the performance of the proposed algorithm, and the results demonstrate that the algorithm can significantly improve the positioning accuracy.Comment: To appear in Proc. of the 15th International IEEE Conference on Intelligent Transportation Systems (IEEE ITSC'12

    High dynamic global positioning system receiver

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    A Global Positioning System (GPS) receiver having a number of channels, receives an aggregate of pseudorange code time division modulated signals. The aggregate is converted to baseband and then to digital form for separate processing in the separate channels. A fast fourier transform processor computes the signal energy as a function of Doppler frequency for each correlation lag, and a range and frequency estimator computes estimates of pseudorange, and frequency. Raw estimates from all channels are used to estimate receiver position, velocity, clock offset and clock rate offset in a conventional navigation and control unit, and based on the unit that computes smoothed estimates for the next measurement interval

    Multipath and interference errors reduction in gps using antenna arrays

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    The Global Positioning System (GPS) is a worldwide satellite based positioning system that provides any user with tridimensional position, speed and time information. The measured pseudorange is affected by the multipath propagation, which probably is the major source of errors for high precision systems. After a presentation of the GPS and the basic techniques employed to perform pseudorange measurements, the influence of the multipath components on the pseudorange measurement is explained. Like every system the GPS is also exposed to the errors that can be caused by the interferences, and a lot of civil applications need robust receivers to interferences for reasons of safety. In this paper some signal array processing techniques for reducing the code measurement errors due to the multipath propagation and the interferences are presented. Firstly, a non-adaptive beamforming is used. Secondly, a variant of the MUSIC and the maximum likelihood estimator can be used to estimate the DOA of the reflections and the interferences, and then a weight vector that removes these signals is calculated. In the third place, a beamforming with temporal reference is presented; the reference is not the GPS signal itself, but the output of a matched filter to the code. An interesting feature of the proposed techniques is that they can be applied to an array of arbitrary geometry.Peer ReviewedPostprint (published version

    Time transfer using NAVSTAR GPS

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    A time transfer unit (TTU) developed for the U.S. Naval Observatory (USNO) has consistently demonstrated the transfer of time with accuracies much better than 100 nanoseconds. A new time transfer system (TTS), the TTS 502 was developed. The TTS 502 is a relatively compact microprocessor-based system with a variety of options that meet each individual's requirements, and has the same performance as the USNO system. The time transfer performance of that USNO system and the details of the new system are presented

    Use of supervised machine learning for GNSS signal spoofing detection with validation on real-world meaconing and spoofing data : part I

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    The vulnerability of the Global Navigation Satellite System (GNSS) open service signals to spoofing and meaconing poses a risk to the users of safety-of-life applications. This risk consists of using manipulated GNSS data for generating a position-velocity-timing solution without the user's system being aware, resulting in presented hazardous misleading information and signal integrity deterioration without an alarm being triggered. Among the number of proposed spoofing detection and mitigation techniques applied at different stages of the signal processing, we present a method for the cross-correlation monitoring of multiple and statistically significant GNSS observables and measurements that serve as an input for the supervised machine learning detection of potentially spoofed or meaconed GNSS signals. The results of two experiments are presented, in which laboratory-generated spoofing signals are used for training and verification within itself, while two different real-world spoofing and meaconing datasets were used for the validation of the supervised machine learning algorithms for the detection of the GNSS spoofing and meaconing

    Specification of a NAVSTAR Global Positioning System (GPS) receiver for a differential GPS ground system

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    One step towards the successful completion of a functional ground unit for the Differential Global Positioning System (DGPS) will be in choosing a currently available GPS receiver that will accurately measure the propagation times of the satellite signals and have the capability to be electrically interfaced with and controlled by a Digital Equipment Corporation (DEC) PDP-11/34A computer. The minimum requirements and characteristics of a NAVSTAR Global Positioning System (GPS) receiver are described. The specific technical specifications addressed include data accuracies and resolutions, receiver interface/external control, enclosure dimensions and mounting requirements, receiver operation, and environmental specifications

    Economic Galileo E5 Receiver

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    The Galileo system introduces an extremely wideband civil E5 signal for high precision navigation. The structure of the receiver for the E5 signal is complicated due to the signal complexity and the large bandwidth. It is possible to process the whole E5 signal or process separately E5a and E5b parts combining obtained results afterwards (we call here such method as piece-wise processing). The second procedure has three times worse standard deviation of the pseudorange then first one. The main goal of the paper is to present a design of an E5 receiver which we will call the economic E5 receiver (ecoE5). It is built from jointly controlled correlators for the processing of the E5a and E5b signals which are parts of the E5 signal. Control of these partial E5a and E5b correlators is realized by only one delay and one phase lock loops. The performance, i.e. the pseudorange noise and multipath errors, of the receiver equipped with the ecoE5, is only slightly worse (the standard deviation of the pseudorange noise is 10 - 20% larger) than the performance of the optimal E5 receiver and it is much better than the performance of the receiver combining the piecewise (E5a and E5b) measurements. The ecoE5 receiver hardware demands are about one quarter of the hardware demands of the classical E5 receiver
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