Conventional Global Positioning System Research Articles

Detection and mitigation of GPS Spoofing Attacks on Phasor Measurement Units using deep learning

The widespread use of Phasor Measurement Units (PMUs) is considered one of the most important contributions to the quality of power system monitoring. PMUs are digital devices that provide synchronized phasor measurements time-referenced by the Global Positioning System (GPS). The lack of encryption in conventional GPS receivers used in PMUs makes them vulnerable to GPS Spoofing Attacks (GSAs) that cause the GPS receiver to lose track, resulting in a phase shift of all measurements of the affected PMU. Even small phase shifts can downgrade the performance of the state estimator, indicating their ability to propagate throughout the entire system. Therefore, ensuring the integrity of PMU measurements is of utmost importance. State-of-the-art statistical methods are insensitive to small phase shifts, and they become computationally intensive as the system size and the number of simultaneous attacks increase. This paper presents the first application of deep learning to simultaneously detect and mitigate the effects of GSAs against PMUs. The performance of the proposed method is evaluated on IEEE 14-, 57-, and 118-bus systems and compared to state-of-the-art statistical and deep learning methods.

Augmented CWT Features for Deep Learning-Based Indoor Localization Using WiFi RSSI Data

Localization is one of the current challenges in indoor navigation research. The conventional global positioning system (GPS) is affected by weak signal strengths due to high levels of signal interference and fading in indoor environments. Therefore, new positioning solutions tailored for indoor environments need to be developed. In this paper, we propose a deep learning approach for indoor localization. However, the performance of a deep learning system depends on the quality of the feature representation. This paper introduces two novel feature set extractions based on the continuous wavelet transforms (CWT) of the received signal strength indicators’ (RSSI) data. The two novel CWT feature sets were augmented with additive white Gaussian noise. The first feature set is CWT image-based, and the second is composed of the CWT PSD numerical data that were dimensionally equalized using principal component analysis (PCA). These proposed image and numerical data feature sets were both evaluated using CNN and ANN models with the goal of identifying the room that the human subject was in and estimating the precise location of the human subject in that particular room. Extensive experiments were conducted to generate the proposed augmented CWT feature set and numerical CWT PSD feature set using two analyzing functions, namely, Morlet and Morse. For validation purposes, the performance of the two proposed feature sets were compared with each other and other existing feature set formulations. The accuracy, precision and recall results show that the proposed feature sets performed better than the conventional feature sets used to validate the study. Similarly, the mean localization error generated by the proposed feature set predictions was less than those of the conventional feature sets used in indoor localization. More particularly, the proposed augmented CWT-image feature set outperformed the augmented CWT-PSD numerical feature set. The results also show that the Morse-based feature sets trained with CNN produced the best indoor positioning results compared to all Morlet and ANN-based feature set formulations.

Implementation and detection of the device location via synthesized antenna array

Currently, proximity service (ProSe), also known as device-to-device (D2D) communication, has been standardized by 3rd generation partnership project (3GPP) to provide the function of exchanging data directly among the user equipments (UE). It has the advantage of improving the signal quality for the cell-edge UE and can be applied to many applications such as the determination of device location for the purpose of public safety.In this paper, we implemented a device location detection system via using the synthesized antenna array. The multiple signal classification (MUSIC) algorithm and the channel delay profile are adopted to complete the detection of the device location. With the self-designed graphic user interface (GUI), the location of the device can be easily determined and displayed on the electronic map, such as the google map, and in the vision of the camera. Besides, according to the measurement results, the proposed method has better location determination performance than the conventional global positioning system (GPS) of the mobile phone, especially in the non line-of-sight (NLOS) scenarios, such as in the indoor environments.

Multistatic Doppler Estimation Using Global Positioning System Passive Coherent Location

In previous works, methods were explored for position estimation utilizing satellite-borne signals of opportunity, mainly the global positioning system (GPS). The GPS signal was exploited for use in a multistatic passive coherent location (PCL) system. The GPS signal is especially attractive for PCL applications because of the native capability to produce position and velocity estimation. This paper examines the signal specifications for PCL implementation and explores the potential limitations of the proposed solutions. GPS specific methods are developed for multistatic PCL velocity estimation in a three-dimensional plane. The method developed is combined with previously completed work of GPS PCL position estimation for a complete system design in range and Doppler. The PCL system is evaluated against conventional GPS position estimation and velocity estimation and proves to have comparable metrics of performance. Analysis and simulation are performed for verification and validation of the developed methods.

Intelligent Agent Technology for Cellular-Assisted GPS Positioning using Bayesian and Self-Organizing Map

This paper presents the use of intelligent agent technology, cellular-assisted Global Positioning System (GPS) and data mining for positioning purpose. Due to overlapping coverage areas of cell towers, conventional cell-based positioning techniques have been reported to be inaccurate. Current cell-assisted GPS positioning setup with high accuracy is costly as it requires huge investments on hardware deployments. A new solution of using intelligent agent technology was proposed by the authors for an economical and satisfactory cell-assisted GPS positioning system. Location information in the form of cell identity (ID) and GPS coordinates pairs can be acquired via devices such as smart phones and GPS trackers. The cell ID-GPS coordinates pairs are then grouped by each individual cell ID. An intelligent agent equipped with data mining capabilities is then deployed to computer the optimal GPS coordinates of the cell ID to provide more precise location information. The proposed solution was evaluated via a prototype system. The system was built to collect raw data of cell-ID and GPS coordinate pairs from trackers and mobile phone applications. Using the reference GPS coordinate that was calculated by taking the mean of longitude and mean of latitude for all the GPS coordinates clustered in the same group, the geographical distance between each GPS coordinate and the reference GPS coordinate in the same group was computed to evaluate the performance of the proposed solution.. Experimental results showed that the proposed solution based on intelligent agent equipped with data mining capability helped in improving the prediction of location with sub-kilometer accuracy, in contract to the conventional cell-assisted GPS positioning system which have low accuracy with distance rate various in kilometers.

Fuzzy Logic Vehicle Positioning System Based on Chromaticity and Frequency Components of LED Illumination

Given their wide applicability, vehicle positioning systems are being actively studied currently. As the conventional global positioning system (GPS) cannot determine the vehicle position inside tunnels and other GPS-shaded areas, we propose to improve vehicle positioning using a fuzzy logic system that can retrieve the position of a moving vehicle in such areas. The proposed system analyzes the chromaticity and frequency components of active LED illumination, which is being commonly installed at locations like inside tunnels. We verify the system performance in a test environment that resembles a tunnel. As the proposed method uses the chromaticity and frequency of LED lights for vehicle positioning, it is suitable for areas where GPS reception is poor or unavailable.

A Combined Antijamming and Antispoofing Algorithm for GPS Arrays

The Global Positioning System (GPS), with its accurate positioning and timing information, has become a commonly used navigation instrument for many applications. However, it is susceptible to intentional interference such as jamming and spoofing. The conventional antijamming GPS receiver fails to work in a combined jamming and spoofing attack scenario. To solve the problem, a combined antijamming and antispoofing algorithm for a GPS receiver based on an antenna array is proposed. In this method, the jamming is eliminated by subspace projection, and then a compressed sensing framework is adopted to obtain the direction of arrival (DOA) of the despreading satellite navigation signal and detect the spoofing signal. According to the DOA of the authentic and spoofing signals, the receiver uses adaptive multibeamforming to concurrently achieve the undistorted reception of the authentic satellite signal and the suppression of the spoofing. We analyse three aspects of algorithmic performance: the antenna array direction diagram, the spoofing detection and the acquisition results. The simulation results and their analysis preliminarily show that the proposed method can detect and suppress GPS jamming and spoofing effectively.

Monitoring of large-scale deformation in mining areas using sub-band InSAR and the probability integral fusion method

ABSTRACTThe large-scale and rapid land subsidence that occurs in mining areas often leads to problems, such as densely spaced interference fringes and the temporal decorrelation of interferometric synthetic aperture radar (InSAR) interferograms. To solve these problems, sub-band InSAR is applied to monitor the large-scale deformation that occurs in mining areas. First of all, four different bandwidth images with three sub-band bandwidth parameters are used to extract simulated mining-induced subsidence with seven different deformation magnitudes. The results of the simulation experiment suggest the following conclusions. In monitoring subsidence with different deformation magnitudes using images with different bandwidths, an optimal monitoring value exists; wider image bandwidths lead to smaller optimal monitoring values and higher monitoring accuracies. Therefore, an appropriate sub-band bandwidth should be selected that depends upon the image bandwidth and the subsidence level to achieve optimal monitoring. The optimal sub-band bandwidth for monitoring subsidence of different magnitudes in mining areas is determined through simulation experiments, and these conclusions can provide a technical basis for selecting the appropriate sub-band bandwidth for the monitoring of subsidence in mining areas. Although sub-band InSAR can reduce the number of interference fringes and the difficulty of unwrapping, the simultaneous introduction of large amounts of noise leads to reduced monitoring precision, and the application of the probability integral method in the prediction of mine subsidence is more mature. Therefore, the combined use of sub-band InSAR and the probability integral fusion method to monitor mining-induced deformation is proposed in this paper. The probability integral method is used to perform noise peeling on the interferometric phases of the sub-bands to improve the monitoring accuracy of sub-band interferometry. Then, according to the results of the simulation experiment, the fusion method with the appropriate sub-band bandwidth parameters is applied to monitor the surface deformation associated with working face 52,304 from 2 December 2012 to 13 December 2012. Finally, the monitoring results are compared with the results of monitoring using conventional differential interferometric synthetic aperture radar (D-InSAR) and global positioning system (GPS) field survey data. The results show that the reliability and accuracy of the fusion method are much better than those of conventional D-InSAR in monitoring the large-scale deformation that occurs at the edges of subsidence basins.

Performance Assessment of Multi-GNSS Precise Velocity and Acceleration Determination over Antarctica

A conventional Differential GPS (DGPS) techniques-based velocity and acceleration method (named here as ‘DVA’) may be difficult to implement in the Antarctic as there is a sparse distribution of reference stations over Antarctica. Thus, in order to overcome the baseline limitations and to obtain highly accurate and reliable velocity and acceleration estimates for airborne gravimetry, a network-based velocity and acceleration determination approach (named here as ‘NVA’), which introduces a wide network of stations and is independent of precise clock information, is applied. Here its performance for velocity and acceleration determination is fully exploited by using Global Positioning System (GPS), GLONASS, Galileo and BeiDou observations. Additionally, a standalone receiver-based method named ‘SVA’, which requires precise clock information, is also implemented for comparison. During static tests and a flight experiment over Antarctica, it was found that the NVA method yields more robust results than the SVA and DVA methods when applied to a wide area network. Moreover, the addition of GLONASS, Galileo and BeiDou systems can increase the accuracy of velocity and acceleration estimates by 39% and 43% with NVA compared to a GPS-only solution.

Dual-polarized GPS antenna array algorithm to adaptively mitigate a large number of interference signals

Intentional or unintentional interference experienced by the Global Positioning System (GPS) is a significant concern for GPS-based critical infrastructures and services including aviation. An effective way to mitigate GPS interference is to utilize a GPS antenna array capable of electronically changing its gain pattern. Although a conventional GPS antenna array consists of single-polarized antenna elements, a dual-polarized antenna array has the potential to mitigate approximately twice the number of interference signals in the spatial domain as a single-polarized array because of the additional degrees of freedom provided. This paper proposes an adaptive beamforming algorithm using a dual-polarized GPS antenna array for mitigation of interference signals with various polarizations. In this paper, a dual-polarized antenna element specifically refers to two co-located crossed linearly polarized dipole antennas. The proposed minimum-variance-distortionless-response (MVDR)-based space–time adaptive processing (STAP) method utilizes a novel constraint vector that is specially designed for a dual-polarized GPS array. As the proposed constraint vector considers realistic radiation patterns of the antenna, the performance of the proposed method in terms of the signal-to-interference-plus-noise power ratio (SINR) is noticeably superior to that of previous methods under a representative interference scenario. The performance of the proposed method is compared with three previous methods utilizing dual-polarized antenna arrays.

Global positioning system processing methods for GPS passive coherent location

This study addresses processing methods for the use of the global positioning system (GPS) as a signal of opportunity in a multistatic passive coherent location (PCL) system. The signal properties of the GPS signal are designed for position estimation, which makes it particularly suited for GPS PCL applications. The signal specifications are examined and the potential limitations of a proposed system are explored. Conventional GPS processing techniques are implemented in the framework of multistatic GPS PCL. GPS specific methods are developed for target position estimation of a multistatic PCL system in a three-dimensional plane. The PCL system has comparable performance metrics to conventional GPS positioning. Two methods are developed utilising measurements available in a conventional GPS system. The first involves a short time scale, which is in the order of milliseconds. The second involves a long time scale method, which is on the order of seconds. Simulation and analysis are performed to verify the methods. Experimental validation was also conducted using a hardware in the loop approach, as well as, an active radar calibrator.

Pursuing Precise Vehicle Movement Trajectory in Urban Residential Area Using Multi-GNSS RTK Tracking

Close-to-reality vehicle movement trajectory data can be useful in many transport and geography studies when precise vehicle localization or timing is required in the application. Vehicle kinematic tracking by GPS (Global Positioning System) varies in the data accuracy depending on both the receiver capability and the tracking environment. Advanced positioning techniques offer possibilities to enhance the tracking data quality. In this paper, the high performance of multi-GNSS (multiple Global Navigation Satellite Systems) with Real-time Kinematic (RTK) solution was investigated aiming to pursue precise vehicle movement trajectory in an urban residential area of Australia. This study systematically compared vehicle kinematic recordings between different positioning solutions by multi-GNSS and GPS-only approaches. Different elevation cut-off angles ranging from 5 - 35° were applied to simulate the satellite availability under different sky view conditions. The results show that the multi-GNSS approach outperformed conventional GPS positioning in the satellite availability and the positioning accuracy. The 10 Hz RTK solution proved to generate optimal vehicle movement trajectories for driving behaviours assessment.

Open-Loop Tracking of Rising and Setting GPS Radio-Occultation Signals From an Airborne Platform: Signal Model and Error Analysis

Global Positioning System (GPS) radio-occultation (RO) is an atmospheric sounding technique utilizing the received GPS signal through the stratified atmosphere to measure refractivity, which provides information on temperature and humidity. The GPS-RO technique is now operational on several Low Earth Orbiting (LEO) satellites, which cannot provide high temporal and spatial resolution soundings necessary to observe localized transient events, such as tropical storms. An airborne RO (ARO) system has thus been developed for localized GPS-RO campaigns. RO signals in the lower troposphere are adversely affected by rapid phase accelerations and severe signal power fading. These signal dynamics often cause the phase-locked loop in conventional GPS survey receivers to lose lock in the lower troposphere, and the open-loop (OL) tracking in postprocessing is used to overcome this problem. OL tracking also allows robust processing of rising GPS signals, approximately doubling the number of observed occultations. An approach for “backward” OL tracking was developed, in which the correlations are computed sequentially in reverse time so that the signal can be acquired and tracked at high elevations for rising occultations. Ultimately, the signal-to-noise ratio (SNR) limits the depth of tracking in the atmosphere. We have developed a model relating the SNR to the variance in the residual phase of the observed signal produced from OL tracking. In this paper, we demonstrate the applicability of the phase variance model to airborne data. We then apply this model to set a threshold on refractivity retrieval based upon the cumulative unwrapping error bias to determine the altitude limit for reliable signal tracking. We also show consistency between the ARO SNR and collocated COSMIC satellite observations and use these results to evaluate the antenna requirements for an improved ARO system.

Precision enhancement of pavement roughness localization with connected vehicles

Transportation agencies rely on the accurate localization and reporting of roadway anomalies that could pose serious hazards to the traveling public. However, the cost and technical limitations of present methods prevent their scaling to all roadways. Connected vehicles with on-board accelerometers and conventional geospatial position receivers offer an attractive alternative because of their potential to monitor all roadways in real-time. The conventional global positioning system is ubiquitous and essentially free to use but it produces impractically large position errors. This study evaluated the improvement in precision achievable by augmenting the conventional geo-fence system with a standard speed bump or an existing anomaly at a pre-determined position to establish a reference inertial marker. The speed sensor subsequently generates position tags for the remaining inertial samples by computing their path distances relative to the reference position. The error model and a case study using smartphones to emulate connected vehicles revealed that the precision in localization improves from tens of metres to sub-centimetre levels, and the accuracy of measuring localized roughness more than doubles. The research results demonstrate that transportation agencies will benefit from using the connected vehicle method to achieve precision and accuracy levels that are comparable to existing laser-based inertial profilers.

A Robust GPS Signal Acquisition Technique Using Discrete Wavelet Transform

A novel Global Positioning System (GPS) signal acquisition scheme based on Discrete Wavelet Transform (DWT) is proposed to improve acquisition performance. Acquisition in GPS system is primary and important step to calculate the code phase in Pseudo Random Noise (PRN) code and Doppler shift in carrier frequency of received GPS signal, which is used for continuous tracking of the satellite. The performance of a GPS receiver system depends on the ability to precisely measure the code range and Doppler shift continuously in the presence of noise. Conventional GPS receivers use Fast Fourier Transform (FFT) to carry out convolution in the acquisition process. This method is unable to precisely acquire the GPS signal in the presence of noise. In this paper, a substitute algorithm using DWT is proposed to perform convolution in order to carry out robust, less complex GPS signal acquisition. The proposed algorithm is implemented on Intermediate Frequency (IF) GPS signal with different levels of noise and also compared with the conventional FFT search algorithm. The proposed algorithm allows implementation of the FFT with a reduced number of samples (2500 instead of 5000 samples), is implemented by collecting the one millisecond period data sampled at 5MHz. Performance of the algorithms are compared based on correlation ratio. Results show that the proposed algorithm using DWT outperforms the FFT search method of acquisition.

Fast Acquisition of GPS Signal Using FFT Decomposition

Acquisition in Global Positioning System (GPS) is primary and important step to measure the code phase of Pseudo Random Noise (PRN) code and Doppler shift in carrier frequency of received GPS signal. The performance of a GPS receiver system depends on the fast and accurate measure of the code phase and Doppler shift in the recived signal. A new GPS signal acquisition method based on decomposition of FFT is proposed to improve the acquisition performance. Conventional GPS receivers use Fast Fourier Transform (FFT) to carry out correlation in the acquisition process. However, this paper proposes a new method that reduces the complexity of FFT computation. The proposed algorithm is implemented, validated and compared the performance with conventional serial search and radix2 FFT search algorithms using Intermediate Frequency (IF) GPS signal. Acquisition algorithms are implemented on 1.25MHz signal data of one millisecond period, sampled at 5MHz. For the sampled data, the proposed algorithm uses 5000 samples insted of number of samples raised to nearest power of 2 i.e. 8192 samples as in the case of radix2 FFT search method to compute FFT. Performance of the algorithms are compared based on computational time and correlation peak magnitude.

VANET BASED SECURE AND EFFICIENT TRANSPORTATION SYSTEM

This paper presents a recent advance of vehicular technology (VANET) offers many opportunities for developing new navigation systems to avoid the problem of GPS (Global positioning system) based navigation systems. The proposed system is uses VSPN scheme for to know the real time road information. This scheme advice the drivers to reach to the destination. In order to integrate vehicular technology into conventional GPS based navigation systems securely, a secure and privacy preserving navigation is required. This VSPN scheme provides security and authentication to the system and it also helps in preserving privacy of the system. In this proposed system the concept of proxy re-encryption scheme and anonymous credentials are used.

Network delay modeling for assisted GPS

Currently, conventional Global Positioning System (GPS) receivers work well in open-sky environments. However, location finding in weak-signal conditions, such as urban canyons and indoors, is challenging and has been the subject of extensive research. Assisted GPS (A-GPS) is one of the concepts that helps receivers acquire weak signals by receiving assistance data from wireless networks, such as orbital parameters, and coarse time and location references. A-GPS also improves time-to-first-fix (TTFF) through faster delivery of information that is recovered from navigation data broadcast by GPS satellites. Receiver technology developers rely on signal simulators for testing real-world scenarios. While A-GPS support has been integrated in many simulators, probabilistic models of delays occurring during assistance data delivery have not been studied properly. This paper provides a methodology of A-GPS network delay modeling that is applicable to various simulation environments. Particularly, a testbed is designed to collect delay data, model them statistically and integrate the model in a simulator. The testbed employs secure user plane location (SUPL) architecture in two modes, mobile station (MS) based (MS-based) and MS-assisted, where data channels are used to communicate A-GPS assistance data.Measurement campaigns are conducted and network delay models are derived for various representative distances between assistance servers and receivers, and for various networks that users connect to, such as LAN, WLAN, third-generation mobile telecommunication (3G), high-speed downlink packet access (HSDPA), and fourth-generation long term evolution (4G LTE), with the Transmission Control Protocol and the Internet Protocol (TCP/IP) connection between a server and a receiver.

Measurement and Modeling of Network Delays for MS-Based A-GPS Assistance Delivery

While conventional global positioning system (GPS) receivers have gained popularity for applications in open-sky environments, their performance degrades in challenging conditions, such as urban canyons and indoors. The assisted GPS (A-GPS) concept enhanced receiver capability to operate in weak signal conditions using terrestrial links to communicate helpful information such as satellite orbital parameters, coarse estimates of time and location, and so forth. The A-GPS mode has been standardized for many wireless networks and is integrated in high-end simulators to support development and testing efforts. As the terrestrial-assistance data channel becomes an important link for the receiver, the statistical modeling of information delivery delays should be addressed to simulate more adequate operation scenarios. This paper addresses this aspect by presenting a delay measurement and modeling approach for Mobile Station Based assistance data. Even though the approach can be applied to other measurement setups, this paper is presented for standardized secure user plane location architecture that exploits data channels of wireless networks to deliver assistance data. Measurement data are collected and modeled for various scenarios of relative deployment of assistance servers and receivers. Delays are modeled for LAN, WLAN, third-generation mobile telecommunication, high-speed downlink packet access, and fourth-generation long-term evolution networks, with the transmission control protocol and the Internet protocol connection between a server and receiver.

A T-DMB navigation system for seamless positioning in both indoor and outdoor environments

Abstract The conventional global positioning system (GPS) can often fail to provide position determination for a mobile user in indoor and urban environments. To cope with GPS failure in such environments, a new navigation system which utilizes a terrestrial digital multimedia broadcasting (T-DMB) signal to obtain the mobile user's position is presented. Since the T-DMB transmitters in Korea construct a single frequency network (SFN), which forces the transmitters to be synchronized, the mobile user can measure a time difference of arrival (TDOA) for all audible T-DMB transmitter pairs. The time difference between T-DMB transmitters is converted to a distance difference by multiplying the time difference by the speed of light. Using these measurements and a TDOA positioning method, the mobile user position can be estimated. An experiment with a T-DMB receiver and a data acquisition (DAQ) board is performed in Seoul to analyze the error characteristic of TDOA measurements. It is certified that the measurement error is bounded under 300 m and can be used to determine the mobile user's position with a small standard deviation.