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This paper addresses both the efficiency and the portability of a computer program in charge of the baseband signal processing of a GNSS receiver. Efficiency, in this context, refers to optimizing the speed and memory requirements of the software receiver. Specifically, the interest is focused on how fast the software receiver can process the incoming stream of raw signal samples and, in particular, if signal processing up to the position fix can be executed in real-time (and how many channels the host computer executing the receiver application can sustain in parallel). This is achieved by applying the concept of parallelization at different abstraction levels. The paper describes strategies based on task, data and instructionlevel parallelism, as well as actual implementations released under an open source license and the results obtained with different commercially available computing platforms. At the same time, the proposed solution also addresses portability, understood as the usability of the same software in different computing environments. ; Grant numbers : Authors ere also support by the Government of Catalonia under Grant 2014–SGR–1567.

One of the main vulnerabilities of GNSS receivers is their exposure to intentional or unintentional jamming signals, which could even cause service unavailability. Several alternatives to counteract these effects were proposed in the literature, being the most promising those based on multiple antenna architectures. This is specially the case for high-grade receivers used in applications requiring reliability and robustness. This article provides an overview of the possible receiver architectures encompassing antenna arrays and the associated signal processing techniques. Emphasis is also put on the most typical implementation issues found when dealing with such technology. A thorough survey is complemented with a set of experiments, including real data processing by a working prototype, which exemplifies the above ideas. ; Grant numbers : This work has been partially supported by the Spanish Ministry of Economy and Competitiveness through project TEC2015-69868-C2-2-R (ADVENTURE) and by the Government of Catalonia under Grant 2014–SGR–1567.© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

The aim of this paper is to trigger a conversation about the assessment, definition of metrics and testing procedures of software-defined GNSS receivers. While the evaluation of traditional (i.e., built on application–specific integrated circuit technology) GNSS receivers is now well–understood, and enjoys both a solid testing industry providing the required equipment and universally agreed figures of merit, the particularities of software–defined radio technologies claim for a more comprehensive approach. In order to account for such a multi–faceted nature, the authors identify sixteen design forces, or dimensions in which a software-defined GNSS can improve. Upon those definitions, a wide list of performance indicators, metrics and procedures are then proposed for each of the identified thrusts. The list can be used as a generative source of ideas when defining key performance indicators in projects, products or services involving a software–defined GNSS receiver. ; Grant numbers : Authors were also support by the Government of Catalonia under Grant 2014–SGR–1567.

Nonlinear filtering is a major problem in statistical signal processing applications and numerous techniques have been proposed in the literature. Since the seminal work that led to the Kalman filter to the more advanced particle filters, the goal has been twofold: to design algorithms that can provide accurate filtering solutions in general systems and, importantly, to reduce their complexity. If Gaussianity can be assumed, the family of sigma-point KFs is a powerful tool that provide competitive results. It is known that the quadrature KF provides the best performance among the family, although its complexity grows exponentially on the state dimension. This article details the asymptotic complexity of the legacy method and discusses strategies to alleviate this cost, thus making quadrature-based filtering a real alternative in high-dimensional Gaussian problems. ; Grant number : This work has been partially funded by the Spanish Ministry of Economy and Competitiveness through project TEC2012-39143 (SOSRAD) and by the Government of Catalonia (2014–SGR–1567).© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Ionospheric scintillation is the name given to the disturbance caused by electron density irregularities along the propagation path of electromagnetic waves through the ionosphere. These non-nominal propagation conditions mainly cause carrier phase variations and amplitude fades. It is important to point out that both degradations are correlated, and thus deep amplitude fades and rapid phase variations (the so-called canonical fades) occur in a simultaneous and random manner. Regarding the carrier synchronization problem under harsh propagation conditions, such as high dynamics, multipath effects or ionospheric scintillation, canonical fades make the latter the most challenging scenario, which can be considered as a benchmark on the performance of robust carrier tracking techniques. This phenomenon particularly affects satellite-based positioning systems in the equatorial regions and at high latitudes. In this work, both amplitude and phase variations due to scintillation are first modeled using an autoregressive (AR) model, and then included into the system state-space formulation. Therefore, a Kalman filter (KF) based solution can be aware of both dynamics and scintillation phase evolutions. This arises as the natural solution to mitigate those undesired propagation effects. Moreover, in order to counteract the main drawbacks of standard KF-based tracking solutions, an extended KF (EKF) architecture is considered, tracking both the phase dynamics, scintillation phase and amplitude. This implies directly operating with the baseband received signal's complex samples, avoiding the use discriminators and thus its saturation and the loss of Gaussianity. Simulation results are provided to support the theoretical discussion and to show the performance improvements of such new approach. ; Grant numbers : This work has been partially supported by the European Commission and by the Spanish Ministry of Economy and Competitiveness project TEC2012-39143 (SOSRAD), and by the Government of Catalonia (2014-SGR-1567).© 2015 ...

Software Defined Radio (SDR) has an infinite number of interpretations depending on the context in which it is designed and used. By way of a starting definition the authors choose to use that of 'a reconfigurable radio system whose characteristics are partially or fully defined via software or firmware'. In various forms, SDR has permeated a wide range of user groups, from military, business, academia and to the amateur radio enthusiast.

Carrier synchronization is a fundamental stage in the receiver side of any communication or positioning system. Traditional carrier phase tracking techniques are based on well-known phase-locked loop (PLL) closed-loop architectures, which are still the methods of choice in modern receivers. Those techniques are well understood, easy to tune, and perform well under benign propagation conditions, but their applicability is seriously compromised in harsh propagation environments, where the signal may be affected by high dynamics, shadowing, strong fadings, multipath effects, or ionospheric scintillation. From an optimal filtering standpoint, the Kalman filter (KF) is clearly a powerful alternative, but the synchronization community seems still reluctant to exploit all the potential it has to offer. The purpose of this article is twofold: i) to review the basics and state of the art on both PLL and KF-based tracking techniques and ii) to present and justify the reasoning behind the systematic use of KF-based tracking approaches instead of the well-established PLL-based architectures from both theoretical and practical points of view. To support the discussion, two specific scenarios of interest to the aerospace community are numerically evaluated: robust carrier tracking of global navigation satellite systems' signals and synchronization in a deep space communications system. ; Grant numbers : This work has been supported by the Spanish Ministry of Economy and Competitiveness through project TEC2015-69868-C2-2-R (ADVENTURE) and by the Government of Catalonia under Grant 2014–SGR–1567.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Carrier tracking is typically implemented by well-known phase-locked loops (PLLs), a receiver architecture that has shown its benefits for many decades. Equivalences between the PLL and the Kalman filter (KF) exists, being the former a particularization of the KF. Progressive substitution of PLL schemes by more sophisticated KF-based carrier tracking loops would allow receivers to tackle effects that are currently degrading PLLs performance and, consequently, carrier-phase estimates. This comes at the price of slightly larger number of parameters to tune. Particularly, this article points out a caveat as to the difficulties in tuning covariance matrices for the dynamical system, which turns to be a critical factor in KF performance. It is desirable to use techniques that, autonomously, select the appropriate values for such covariance matrices. The paper discusses the main covariance estimation techniques for KF adjustment and its applicability in the context of GNSS carrier-tracking with meaningful computer simulation results. ; Grant numbers : This work has been supported by the Spanish Ministry of Economy and Competitiveness through project TEC2015-69868-C2- 2-R (ADVENTURE) and by the Government of Catalonia under Grant 2014–SGR–1567.

This article presents a new multiple state-partitioning solution to the Bayesian smoothing problem in nonlinear high-dimensional Gaussian systems. The key idea is to partition the original state into several low-dimensional subspaces, and apply an individual smoother to each of them. The main goal is to reduce the state dimension each filter has to explore, to reduce the curse of dimensionality and eventual loss of accuracy. We provide the theoretical multiple smoothing formulation and a new nested sigma-point approximation to the resulting smoothing solution. The performance of the new approach is shown for the 40-dimensional Lorenz model. ; Grant numbers : This work has been supported by the Spanish Ministry of Economy and Competitiveness through project TEC2015-69868-C2-2-R (ADVENTURE) and by the Government of Catalonia under Grant 2014–SGR–1567.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.