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Low-latitude ionospheric behavior directly interferes with a wide range of applications dependent on signals and information from satellites. The most severe and variable events are plasma bubbles and ionospheric scintillation. During plasma bubble events, large and steep plasma density gradients may intersect transionospheric signal from satellites, especially around the equatorial anomaly region. Large ionospheric spatial gradients (or decorrelations) are a critical component of ionospheric threat models for global navigation satellite systems augmentation systems; however, the models cannot assimilate abrupt changes in ionospheric behavior. In this article, an investigation of the relationship between plasma depletions, the occurrence of scintillation, and strong ionospheric spatial decorrelation events was conducted. The results indicate that strong scintillations occur when large gradients are verified. Additionally, the most critical ionospheric spatial gradients were verified mostly under certain conditions: when satellite signals are aligned with the plasma bubble propagation along geomagnetic field lines. Therefore, even though amplitude scintillation may degrade communications, the critical gradient events seem to be related to a particular configuration of satellite signal across the ionosphere. Thus, it is recommended that ionospheric threat models for augmentation systems in low-latitude regions consider this alignment aspect. [ABSTRACT FROM AUTHOR]

This article proposes a global navigation satellite system (GNSS) spoofing detection and classification technique for single-antenna receivers. We formulate an optimization problem at the baseband correlator domain by using the Least Absolute Shrinkage and Selection Operator (LASSO). We model correlator tap outputs of the received signal to form a dictionary of triangle-shaped functions and leverage sparse signal processing to choose a decomposition of shifted matching triangles from said dictionary. The optimal solution of this minimization problem discriminates the presence of a potential spoofing attack peak by observing a decomposition of two different code-phase values (authentic and spoofed) in a sparse vector output. We use a threshold to mitigate false alarms. Furthermore, we present a variation of the minimization problem by enhancing the dictionary to a higher resolution of shifted triangles. The proposed technique can be implemented as an advanced fine-acquisition monitoring tool to aid in the tracking loops for spoofing mitigation. In our experiments, we are able to distinguish authentic and spoofer peaks from synthetic data simulations and from a real dataset, namely, the Texas spoofing test battery. The proposed method achieves 0.3% detection error rate for a spoofer attack in nominal signal-to-noise ratio conditions and an authentic-over-spoofer power of 3 dB. [ABSTRACT FROM AUTHOR]

In this article, the problem of detecting and excluding faulty global navigation satellite systems (GNSSs) measurements at the receiver end is formulated as a parameterized quadratic programming (PQP) problem. Compared to the existing fault detection and exclusion (FDE) methods, which mostly rely on exhaustive search, the PQP method is computationally efficient for finding the outliers even when the number of outliers is moderate or large. In the context of multiconstellation GNSS where the probability of multiple simultaneous faults is increased, the PQP method is ideal for the task of fault exclusion since the computation time does not increase with the number of fault hypotheses. It is noted that this article addresses the computational load due to the exclusion function only. The integrity risk bound and continuity risk bound are of fundamental importance to assess the performance of FDE algorithms for safety-critical applications. With the aim to benefit safety-critical applications, the PQP method is integrated with the integrity risk bound and the continuity risk bound derived for FDE using Chi-squared receiver autonomous integrity monitoring (RAIM). It is emphasized that the integration of the PQP method and the integrity and continuity risk bounds do not make the PQP method a practical integrity monitoring method. This is because the computation of the integrity risk bound is still combinatorial and the resulting integrity risk bound is rather conversative. Instead, the integration allows for the opportunity to refine the PQP method so that it can be considered a practical integrity monitoring method. In particular, improvements to reduce the computational load for the Chi-squared RAIM FDE integrity risk bound calculation can readily be applied to the integrity risk bound calculation for the PQP method. Also, further research on PQP parameter tuning can be pursued to tighten the integrity risk bound. [ABSTRACT FROM AUTHOR]

Modern infrastructure heavily relies on various location-based services using global navigation satellite systems (GNSSs) such as the U.S. global positioning system for access to positioning, navigation, and timing information. Location information enables guidance in many applications, including finding the location of vehicles for public safety emergency E-911 services. Nevertheless, GNSS signals can be jammed or manipulated by radio frequency spoofers, so receivers may produce unreliable location data. With increasing reliance on infrastructure and public services on location awareness, location data should be properly validated. This paper presents an approach of validating GNSS data using magnetic field fingerprint maps, which are not sensitive to potential spoofers. It first captures unique or rare geomagnetic profiles (referred to as fingerprints), including all location-dependent fluctuations and anomalies from both natural and man-made sources (referred to as landmarks), on a traveling vehicle. It then tracks their alignment with the GNSS data. A two-tier fingerprint matching localization framework has also been proposed to identify target landmarks by captured fingerprints. [ABSTRACT FROM AUTHOR]

Recently, several global navigation satellite systems (GNSS) emerged following the transformative technology impact of the first GNSS—U.S. global positioning system (GPS). The power level of GNSS signals as measured at earth’s surface is below the noise floor and is consequently vulnerable against interference. Spoofers are smart GNSS-like interferers, which mislead the receivers into generating false position and time information. While many spoofing mitigation techniques exist, spoofers are continually evolving, producing a cycle of new spoofing attacks and counter-measures against them. Thus, upgradability of receivers becomes an important advantage for maintaining their immunity against spoofing. Software-defined radio implementations of a GPS receiver address such flexibility but are challenged by demanding computational requirements of both GNSS signal processing and spoofing mitigation. Therefore, this paper reviews reported SDRs in the context of instrumentation capabilities for both conventional and spoofing mitigation modes. This separation is necessitated by significantly increased computational loads when in spoofing domain. This is demonstrated by a case study budget analysis. [ABSTRACT FROM AUTHOR]

The ubiquitousness of location-based services has proven effective for many applications such as commercial, military, and emergency responders. Software-defined radio (SDR) has emerged as an adequate framework for the development and testing of global navigational satellite systems such as the global position system (GPS). SDR receivers are constantly developing in terms of acceleration factors and accurate algorithms for precise user navigation. However, many SDR options for GPS receivers currently lack real-time operation or could be costly. This paper presents a LabVIEW (LV) and C/C++-based GPS L1 receiver platform with real-time capabilities. The system relies on LV acceleration factors as well as other C/C++ techniques such as dynamic link library integration into LV and parallelizable loop structures, and single instruction, multiple data methods, which leverage host PC multipurpose processors. A hardware testbed is presented for compactness and mobility, as well as software functionality and data flow handling inherent in LV environment. Benchmarks and other real-time results are presented as well as compared with the other state-of-the-art open-source GPS receivers. [ABSTRACT FROM AUTHOR]

Ionospheric scintillation is one of the major threats and most challenging propagation scenarios affecting Global Navigation Satellite Systems (GNSS) and related applications. The fact that this phenomenon causes severe degradations only in equatorial and high latitude regions has led to very few contributions dealing with the fundamental scintillation mitigation problem, being of paramount importance in safety critical applications and advanced integrity receivers. The goal of this paper is twofold, first to bring together the most relevant contributions on GNSS receiver design under scintillation conditions, and then, to propose a new GNSS carrier tracking framework and scintillation mitigation methodology. Scintillation complex gain components are modeled as AR processes and embedded into the state-space formulation, providing the filter the capability to distinguish between dynamics and phase scintillation contributions. In addition, the actual need of robust solutions is solved by using an adaptive filtering approach and directly operating with the baseband received signal. Simulation results, using both synthetic and real scintillation data, are provided to support the theoretical discussion and to show the performance improvements of such new approach. [ABSTRACT FROM AUTHOR]

We propose a simple low-cost technique that enables civil global positioning system receivers and other civil global navigation satellite system (GNSS) receivers to reliably detect carry-off spoofing and jamming. The technique, which we call the power-distortion detector, classifies received signals as interference-free, multipath-afflicted, spoofed, or jammed according to observations of received power and correlation function distortion. It does not depend on external hardware or a network connection and can be readily implemented on many receivers via a firmware update. Crucially, the detector can with high probability distinguish low-power spoofing from ordinary multipath. In testing against more than 25 high-quality empirical datasets yielding more than 900,000 separate detection tests, the detector correctly alarms on all malicious spoofing or jamming attacks while maintaining a $<$0.6% single-channel false alarm rate. [ABSTRACT FROM PUBLISHER]

This paper presents a precorrelation interference detection method based on statistical analysis in the time-frequency (TF) domain for global navigation satellite system signals. In particular, the short-time Fourier transform (STFT) is considered as the TF tool due to its linear property and low computational complexity. A goodness-of-fit (GoF) test is applied to each frequency slice in the spectrogram of the received signal, which approximately follows a chi-square distribution in the absence of interference. The expected probability density function (PDF) of the observed TF-domain samples can be computed based on an interference-free signal or the noise power estimate. Two versions of the proposed technique are presented: one based on the canonical STFT with the maximum overlap size, and the other based on the block-wise STFT using nonoverlapped samples. The canonical STFT-based method shows better detection capability at the expense of degraded false alarm performance caused by the PDF distortion in the canonical STFT samples. The block-wise STFT-based method alleviates the false alarm issue but slightly weakens the detection capability. Simulations show that the proposed canonical and block-wise STFT-based methods improve the detection performance for both narrow- and wideband interference in low jammer-to-noise ratio environments when compared with the existing GoF test applied to the time-domain samples. [ABSTRACT FROM AUTHOR]

Accurate, reliable, and robust global positioning system (GPS) localization is desirable for many navigation applications. Unfortunately, it is challenging for a single GPS receiver to always provide accurate positioning solutions. In urban environments, intermittent signal availability leads to degraded GPS signal tracking and position estimation of the single GPS receiver. In addition, equipment malfunction of the single GPS receiver results in inaccurate navigation solutions. This paper presents a deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation. MRVT jointly tracks GPS signals received by multiple GPS receivers, mitigating GPS signal tracking disruptions, improving the reliability of GPS localization in periods of intermittent signal availability. In addition, the MRVT receiver is more robust to equipment malfunctions than the single GPS receiver. We implemented an MRVT receiver using commercial radio frequency front ends and our PyGNSS software. We experimentally validated the reliability of our MRVT receiver in periods of intermittent GPS availability experienced in downtown San Francisco. Our MRVT receiver exhibited consistent GPS signal tracking and position estimation as compared to vector tracking. In addition, we experimentally validated the robustness of our MRVT receiver to the failure of a single GPS receiver. [ABSTRACT FROM AUTHOR]

The results of processing preexisting ionospheric storm data are presented to demonstrate the use of the long-term ionospheric anomaly monitoring (LTIAM) tool for developing a ground-based augmentation system (GBAS) ionospheric anomaly threat model. The LTIAM not only detect the worst ionospheric gradients successfully, but also populate the current GBAS threat space with newly discovered ionospheric anomalies. As an application of LTIAM, the paper also proposes a method of utilizing its outputs to understand the distribution of anomalous spatial gradients. Examining the gradients above 50 mm/km on known storm days demonstrates that smaller (but still anomalous) gradients are far more likely than extreme gradients above 200 mm/km. The continued use of LTIAM over the current and upcoming solar peaks is discussed to estimate the likelihood of large spatial gradients. [ABSTRACT FROM PUBLISHER]

A postprocessing methodology is developed to validate abnormal ionospheric spatial decorrelation observed during the equatorial plasma bubble (EPB) events. While the Global Navigation Satellite System (GNSS) remote sensing techniques have been used to measure the ionospheric gradients, the measurements can be easily corrupted during the ionospheric disturbances. Extremely large ionospheric gradients are required to be validated before being declared real ionospheric events as opposed to the artifacts of erroneous measurements. The use of existing methods is however limited due to the small size of EPBs compared with the baseline distances between GNSS network stations in equatorial regions. This paper proposes a new validation procedure which utilizes a time-step method to estimate gradients over any short distance. Equatorial anomaly events are visualized in multiple time series by combining all available sources, including severe gradients observed from the multiple widely spread stations, the estimated EPB and known satellite motions, and the known station locations. A similar ionospheric pattern over multiple station–satellite pairs supports the fact that they are impacted by the same EPB at different times and locations. An extreme ionospheric gradient of 3.09 TECU/km observed in the Brazilian region during the December 31, 2013 EPB event is validated to be real using this methodology. The results demonstrate the effectiveness of the methodology for validating EPB-induced ionospheric spatial decorrelation. [ABSTRACT FROM PUBLISHER]

This paper establishes the role of sparse arrays and sparse sampling in antijam global navigation satellite systems (GNSS). We show that both jammer direction of arrival estimation methods and mitigation techniques benefit from the design flexibility of sparse arrays and their extended virtual apertures or coarrays. Taking advantage of information redundancy, significant reduction in hardware and computational cost materializes when selecting a subset of array antennas without sacrificing jammer nulling or localization capabilities. In addition to the spatial array sparsity, antijam can utilize sparsity of jammers in the spatio–temporal frequency domains. By virtue of their finite number, jammers in the field of view are sparse in the azimuth and elevation directions. For the class of frequency modulated jammers, sparsity is also exhibited in the joint time-frequency signal representation. These spatial and signal characteristics have called for the development of sparsity-aware antijam techniques for the accurate estimation of jammer space-time-frequency signature, enabling its effective sensing and excision. Both theory and simulation examples demonstrate the utility of coarrays, sparse reconstructions, and antenna selection techniques for antijam GNSS. [ABSTRACT FROM AUTHOR]

Space-based positioning, navigation, and timing (PNT) technologies, such as the global navigation satellite systems (GNSS) provide position, velocity, and timing information to an unlimited number of users around the world. In recent years, PNT information has become increasingly critical to the security, safety, and prosperity of the World's population, and is now widely recognized as an essential element of the global information infrastructure. Due to its vulnerabilities and line-of-sight requirements, GNSS alone is unable to provide PNT with the required levels of integrity, accuracy, continuity, and reliability. A multisensor navigation approach offers an effective augmentation in GNSS-challenged environments that holds a promise of delivering robust and resilient PNT. Traditionally, sensors such as inertial measurement units (IMUs), barometers, magnetometers, odometers, and digital compasses, have been used. However, recent trends have largely focused on image-based, terrain-based and collaborative navigation to recover the user location. This paper offers a review of the technological advances that have taken place in PNT over the last two decades, and discusses various hybridizations of multisensory systems, building upon the fundamental GNSS/IMU integration. The most important conclusion of this study is that in order to meet the challenging goals of delivering continuous, accurate and robust PNT to the ever-growing numbers of users, the hybridization of a suite of different PNT solutions is required. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the coding aspects of a GNSS receiver. Coding allows detection and correction of channel-induced errors at the receiver, here the focus is on the mitigation of threats from malicious interferences. Although the effects of interference at different stages of GNSS baseband processing has been deeply analyzed in the literature, little attention was devoted to its impact on the navigation message decoding stage. Theis paper provides an introduction to the various coding schemes employed by current GNSS signals, discussing their performance in the presence of noise in terms of block-error rate. Additionally, the benefits of soft-decoding schemes for navigation message decoding are highlighted when jamming interferences are present. The proposed scheme requires estimating the noise plus interference power, yielding to enhanced decoding performances under severe jamming conditions. Finally, cryptographic schemes as a means of providing anti-spoofing for geosecurity location-based services, and their potential vulnerability are discussed, with particular emphasis on the dependence on the dependence of the scheme on successful navigation message decoding. [ABSTRACT FROM AUTHOR]

In Global Navigation Satellite System (GNSS) positioning, urban environments represent an issue particularly because of multipath and nonline-of-sight effects. The latter effects induce erroneous pseudorange observations that then should be discarded in order not to affect the estimation of the receiver position. This paper proposes a new approach for the detection of outliers in the pseudorange observations. Based on two models representing the distribution of inconsistent data (naive models), two criteria are proposed to partition the data between inliers and outliers and to estimate the location parameters. These criteria are then implemented in two localization algorithms. In addition, by considering hypotheses specific to GNSS localization, pseudorange selection and a regularization step are implemented in order to reduce the complexity and to improve the problem conditioning. Using simulated and actual datasets, the proposed algorithms are compared with popular and recent methods addressing the GNSS positioning problem. We show that the outlier detection improves the estimation of the receiver location and outperforms the classical approaches particularly when the environment is constrained. [ABSTRACT FROM PUBLISHER]

Global Navigation Satellite Systems (GNSS) are applicable to deliver train locations in real time. This train localization function should comply with railway functional safety standards; thus, the GNSS performance needs to be evaluated in consistent with railway EN 50126 standard [Reliability, Availability, Maintainability, and Safety (RAMS)]. This paper demonstrates the performance of the GNSS receiver for train localization. First, the GNSS performance and railway RAMS properties are compared by definitions. Second, the GNSS receiver measurements are categorized into three states (i.e., up, degraded, and faulty states). The relations between the states are illustrated in a stochastic Petri net model. Finally, the performance properties are evaluated using real data collected on the railway track in High Tatra Mountains in Slovakia. The property evaluation is based on the definitions represented by the modeled states. [ABSTRACT FROM PUBLISHER]

The modernization of global positioning systems (GPS) boosts the development of civil and military applications as accuracy and coverage of receivers continually improve. Recently, software defined radio (SDR) approach for GPS receivers (GPS-SDR) gained attention because of its flexibility for multimode operations in different environments. The SDR receiver developers continually advance algorithmic and/or hardware accelerator solutions. However, they need fast prototyping and testing instrumentation to refine and evaluate high performance multimode receivers. This paper presents a feasibility study of fast prototyping of the GPS receiver accelerators using graphical user interface environments. It also describes a testbed with integrated RF front-ends, GPS simulator, receiver, and assistance support. Particularly, a novel host-target codesign solution is demonstrated using a field programmable gate array (FPGA) peripheral and LabVIEW FPGA tool for a case study of a GPS acquisition module. Distributing tasks between the FPGA target and the personal computer host achieves a high performance solution. The fast prototyped solution is compared with a conventional FPGA and state-of-the-art implementations. [ABSTRACT FROM PUBLISHER]

The observability analysis of a collaborative opportunistic navigation (COpNav) environment whose states may be partially known is considered. A COpNav environment can be thought of as a radio frequency (RF) signal landscape within which one or more RF receivers locate themselves in space and time by extracting and, possibly, sharing information from ambient signals of opportunity (SOPs). These receivers, whether vehicle mounted or integrated into handheld devices, exploit signal diversity to improve navigation and timing robustness compared with stand-alone Global Positioning System (GPS) receivers in deep urban, indoor, or, otherwise, GPS-hostile environments. Available SOPs may have a fully known, partially known, or unknown characterization. In this paper, the receivers are assumed to draw only pseudorange-type measurements from the SOPs. Separate observations are fused to produce an estimate of each receiver's position, velocity, and time (PVT). Since not all SOP states in the COpNav environment may be known a priori, the receivers must estimate the unknown SOP states of interest simultaneously with their own PVT. This paper establishes the minimal conditions under which a COpNav environment consisting of multiple receivers and multiple SOPs is completely observable. Moreover, in scenarios where the COpNav environment is unobservable, the unobservable directions in the state space are specified. Simulation and experimental results are presented to confirm the theoretical observability conditions. [ABSTRACT FROM PUBLISHER]

This paper proposes a fast unambiguous acquisition technique for binary-offset-carrier (BOC)-modulated signals. We remove the ambiguities (side peaks) of the BOC autocorrelation function (ACF), exploiting a reduced-complexity (real and symmetric) filter composed of only seven nonzero samples. The proposed scheme is applicable to both generic sine- and cosine-phased BOC signals. Theoretical and simulation results show that the proposed method removes the ambiguities in the acquisition problem without requiring an auxiliary signal in the receiver. [ABSTRACT FROM PUBLISHER]

A Carrier-to-Noise spectral density-based criterion for selecting Binary Offset Carrier signals (both sine and cosine) for the purpose of a cognitive tracking unit is derived in this letter. The paper presents the C/N_0 gap between two signals in terms of positioning capability expressed via the Cramer Rao lower bounds on time-delay estimation accuracy. [ABSTRACT FROM PUBLISHER]

We propose an unambiguous tracking method for Alternative Binary Offset Carrier (AltBOC) modulated signals based on the Dual Estimate Tracking (DET) loops. The proposed method employs a combined PRN code and a pure cosine signal which can be easily implemented in the hardware to make DET loops available to the complicated AltBOC signal structure. The two dimensional correlation function for AltBOC is derived, and an unambiguous delay estimate is deduced according to the correlation function. Simulation results reveal that the proposed method performed better in tracking performance than the traditional unambiguous tracking methods. [ABSTRACT FROM PUBLISHER]

This letter proposes a new multipath mitigation technique based on the concept of S-curve shaping for the new cosine phased binary offset carrier (cosine-BOC) modulated signals, which will most likely be used in both European Galileo system and Chinese Compass system. The definition of an optimum S-curve is employed to reduce the false lock points and to improve the multipath mitigation capability via determining the weights of the local linear combined code. The structure of the code tracking loop for cosine-BOC signals is quite simple and only requires one correlator. Results demonstrate that the proposed technique provides superior multipath mitigation performance and removes the ambiguity completely. [ABSTRACT FROM PUBLISHER]

This paper summarizes the main results obtained during the development of an Enhanced Precise Point Positioning (EPPP) Global Navigation Satellite Systems multifrequency user algorithm. The main innovations include the application of precise ionospheric corrections to facilitate the resolution of undifferenced carrier phase ambiguities, ambiguity validation, and integrity monitoring. The performance of the EPPP algorithm in terms of accuracy, convergence time, and integrity is demonstrated with actual GPS and simulated Galileo data. This can be achieved with very limited bandwidth requirements for EPPP users (less than 300 b/s for dual-frequency GPS data). [ABSTRACT FROM PUBLISHER]