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

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.

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.

Multipath is known to be one of the most dominant sources of accuracy degradation in satellite-based navigation systems. Multipath may cause biased position estimates that could jeopardize high-precision applications. This paper considers the problem of tracking the time-variant synchronization parameters of both the line-of-sight signal (LOSS) and its multipath replicas. In particular, the proposed algorithm tracks time-delays, amplitudes, phases and proposes a procedure to extract Doppler shifts from complex amplitudes. However, the interest is focused on LOSS time-delay estimates, since those provide the means to compute user's position. The undertaken Bayesian approach is implemented by a particle filter. The selection of the importance density function, from which particles are generated, is performed using a Gaussian approximation of the posterior function. This selection provides a particle generating function close to the optimal, which yields to an efficient usage of particles. The complex-linear part of the model, i.e., complex amplitudes, is tackled by a Rao-Blackwellization procedure that implements a complex Kalman filter for each generated particle, thus reducing the computational load. Computer simulation results are compared to other Bayesian filtering alternatives (namely, the extended Kalman filter, the unscented Kalman filter and the sequential importance resampling algorithms) and the posterior Cramer-Rao bound.

This paper addresses the estimation of the code-phase (pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code- and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Crame/spl acute/r-Rao lower bound of the problem at hand.

Recently, direct position estimation (DPE) has arisen as a potential approach to deal with the positioning problem in global navigation satellite system receivers. The conventional navigation solution is obtained in two steps: synchronization parameters are estimated and then a trilateration procedure is in charge of computing user's position, based on those parameters. In contrast, DPE estimates receiver's position directly from digitized signal. DPE was seen to provide GNSS receivers with appealing capabilities, such as multipath mitigation. However, a theoretical bound for those estimates is still missing and the answer to ldquohow better can DPE perform compared to the conventional approach?rdquo has not been addressed in the literature. Aiming at clarifying those issues, this paper presents the derivation of the CramEacuter-Rao bound (CRB) of position for both conventional and DPE approaches. We present the derivation for a multiantenna receiver as a general case. In addition, a number of realistic scenarios are tested in order to compare the theoretical performance bounds of both alternatives and the actual root mean squared error performance of the corresponding maximum likelihood estimator.