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.

This paper investigates the application of the Generalized Likelihood Ratio Test detector to the Global Navigation Satellite System array-based acquisition problem. We consider an unstructured channel model which includes colored noise with an arbitrary covariance matrix. We show that the proposed test function is a Constant False Alarm Rate detector and we provide closed form expressions for false alarm, detection probabilities, and the Receiver Operating Characteristic. Furthermore, this work analyzes the Sample Covariance Matrix structure and the capability of the detector to reject uncorrelated interferences. Simulation results validate the theoretical analysis.

It is known that satellite radiolocalization was born in the military environment and was originally conceived for defense purposes. Nevertheless, the commercial explosion (dated to 20 years ago) of global positioning system (GPS) in the civil market (automotive, tourism, etc.) significantly changed the original perspectives of this technology. Another big change is expected when other global navigation satellite systems (GNSSs) such as the European Galileo or the Chinese COMPASS become operational and commercial. In fact, modern GNSSs are conceived principally for the civil market (at the opposite of GPS, whose civil employment is given as a sort of “kind gift,” with lower performance than that one granted to military users). The scope of this paper is to provide readers with a clear focus about the potentialities of current and forthcoming GNSSs and associated technologies in a renewed mass-market perspective. The paper also opens a window to the future of radiolocalization technology beyond GPS and GNSS, dealing with the role of digital signal processing and software-defined radio (SDR) in next-generation navigation systems and with the seamless integration of satellite-based navigation with other technologies in order to provide reliable position information also in hostile environments.

The performance of Global Navigation Satellite Systems (GNSS) is known to be severely affected in multipath scenarios, providing a biased position solution which could jeopardize possible geodetic-grade applications. Indeed, multipath estimation and/or mitigation has attracted the attention of many researchers in the recent years. Nevertheless, few attention has been given to the detection of multipath. That is to say, acknowledging that a given scenario is corrupted by multiple propagation paths, and thus using adequate techniques to combat its effect. This paper proposes a statistical multipath detector based on an antenna array GNSS receiver. Specifically, the detector resorts to the estimated noise covariance matrix to compute a statistic that measures the dispersion of its eigenvalues. The theoretical distribution of such statistic is known. This is used by the proposed method to perform a Kolmogorov-Smirnov one-sample test to assess departures from the theoretical distribution, with the resulting detector being Constant False Alarm Rate. The detector is analyzed in terms of its probability of detection and an analysis is provided regarding its behavior under synchronization errors. Results of the detector under realistic scenarios are also discussed.

This paper considers the problem of ultra-tight GNSS/INS integration. We propose a new approach, deriving the direct relation between Inertial Measurement Unit (IMU) measurements and synchronization parameters, used in the trilateration algorithm to compute the position of the receiver. We take into account the IMU's eventual biased behavior by introducing it into the state representation. We use a recently-developed, square-root derivative-free Gaussian nonlinear filter to solve the estimation problem.

This paper shows the applicability of recently-developed Gaussian nonlinear filters to sensor data fusion for positioning purposes. After providing a brief review of Bayesian nonlinear filtering, we specially address square-root, derivative-free algorithms based on the Gaussian assumption and approximation rules for numerical integration, namely the Gauss--Hermite quadrature rule and the cubature rule. Then, we propose a motion model based on the observations taken by an Inertial Measurement Unit, that takes into account its possibly biased behavior, and we show how heterogeneous sensors (using time-delay or received-signal-strength based ranging) can be combined in a recursive, online Bayesian estimation scheme. These algorithms show a dramatic performance improvement and better numerical stability when compared to typical nonlinear estimators such as the Extended Kalman Filter or the Unscented Kalman Filter, and require several orders of magnitude less computational load when compared to Sequential Monte Carlo methods, achieving a comparable degree of accuracy.

Multipath is one of the dominant sources of error in high-precision GNSS applications. A tracking algorithm is presented that explicitely accounts for direct signal and multipath replicas in the model, in order to mitigate the contributions of the latter. A Bayesian approach has been taken, to infer some information from the time evolution model of the parameters. Due to the nonlinearity of the measurement model, a Particle Filtering algorithm has been designed. The proposed PF considers Rao-Blackwellization with a CKF and the selection of the importance density is performed via the use of Laplace’s method, which yields to an importance density close the optimal. Simulations compare performance to EKF and PCRB.

In this paper, the maximum likelihood estimator (MLE) of the position in satellite based navigation systems is studied. Recent results have shown that this novel approach provides an interesting way of introducing prior information in the position estimation and that the estimator is consistent for large sample sizes. However, one of the main drawbacks of this approach is the lack of a computationally efficient optimization algorithm due to the high dimensionality and nonlinearity of the resulting cost function, since there is not a closed form solution for this estimator. The aim of this paper is to investigate the application of the space-alternating generalized expectation maximization (SAGE) algorithm to the estimation of position. The SAGE algorithm is a low-complexity generalization of the EM (expectation-maximization) algorithm, which iteratively approximates the MLE. Computer simulation results are provided, comparing the performance obtained by the algorithm with the Cramer-Rao bound.

In this letter, we obtain the maximum likelihood estimator of position in the framework of global navigation satellite systems. This theoretical result is the basis of a completely different approach to the positioning problem, in contrast to the conventional two-step position estimation, consisting of estimating the synchronization parameters of the in-view satellites and then performing a position estimation with that information. To the authors' knowledge, this is a novel approach that copes with signal fading, and it mitigates multipath and jamming interferences. Besides, the concept of position-based synchronization is introduced, which states that synchronization parameters can be recovered from a user position estimation. We provide computer simulation results showing the robustness of the proposed approach in fading multipath channels. The root mean square error performance of the proposed algorithm is compared to those achieved with state-of-the-art synchronization techniques. A sequential Monte Carlo-based method is used to deal with the multivariate optimization problem resulting from the maximum likelihood solution in an iterative way

In direct-sequence spread-spectrum(DS-SS) navigation based systems, multipath can degrade seriously synchronization performance causing time delay and code phase estimates, to deviate from the actual value. This bias depends on the relative amplitudes and delays of multipath replicas with respect to the direct signal. The error in the estimated position due to multipath, when using a standard Delay Lock Loop, can be on the order of several tens of meters, which is a critical aspect in high-precision applications. This works presents a Sequential Monte Carlo based algorithm which tries to iteratively estimate complex amplitudes and delays of the direct signal and multipath replicas by characterizing the posterior probability density function of these parameters relying on particle filter theory. Simulations are presented for navigation systems, which are particular applications of DS-SS systems.

This paper deals with the reception of several Global Navigation Satellite Systems (GNSS) signals using antenna arrays in the presence of interference, multipath propagation and array manifold uncertainties. The proposed method is a new space-time approach where all the line-of-sight signals (LOSS) are pointed by the array, and the temporal reference of the signal is exploited. The work also presents an extension of this beamforming that takes into account the uncertainties in the steering matrix due to pointing errors or array miscalibration. The robustness of this new method is achieved using second-order cone programming, allowing its implementation with highly efficient algorithms. Simulations show the performance of these beamformers in scenarios where coherent multipath and pointing errors are present.