Economic Galileo E5 Receiver

The Galileo system introduces an extremely wideband civil E5 signal for high precision navigation. The structure of the receiver for the E5 signal is complicated due to the signal complexity and the large bandwidth. It is possible to process the whole E5 signal or process separately E5a and E5b parts combining obtained results afterwards (we call here such method as piece-wise processing). The second procedure has three times worse standard deviation of the pseudorange then first one. The main goal of the paper is to present a design of an E5 receiver which we will call the economic E5 receiver (ecoE5). It is built from jointly controlled correlators for the processing of the E5a and E5b signals which are parts of the E5 signal. Control of these partial E5a and E5b correlators is realized by only one delay and one phase lock loops. The performance, i.e. the pseudorange noise and multipath errors, of the receiver equipped with the ecoE5, is only slightly worse (the standard deviation of the pseudorange noise is 10 - 20% larger) than the performance of the optimal E5 receiver and it is much better than the performance of the receiver combining the piecewise (E5a and E5b) measurements. The ecoE5 receiver hardware demands are about one quarter of the hardware demands of the classical E5 receiver

Universality and Realistic Extensions to the Semi-Analytic Simulation Principle in GNSS Signal Processing

Semi-analytic simulation principle in GNSS signal processing bypasses the bit-true operations at high sampling frequency. Instead, signals at the output branches of the integrate&dump blocks are successfully modeled, thus making extensive Monte Carlo simulations feasible. Methods for simulations of code and carrier tracking loops with BPSK, BOC signals have been introduced in the literature. Matlab toolboxes were designed and published. In this paper, we further extend the applicability of the approach. Firstly, we describe any GNSS signal as a special instance of linear multi-dimensional modulation. Thereby, we state universal framework for classification of differently modulated signals. Using such description, we derive the semi-analytic models generally. Secondly, we extend the model for realistic scenarios including delay in the feed back, slowly fading multipath effects, finite bandwidth, phase noise, and a combination of these. Finally, a discussion on connection of this semi-analytic model and position-velocity-time estimator is delivered, as well as comparison of theoretical and simulated characteristics, produced by a prototype simulator developed at CTU in Prague

The Witch Navigator - A Low Cost GNSS Software Receiver for Advanced Processing Techniques

The developement of advanced GNSS signal processing algorithms such as multi-constellation, multi-frequency and multi-antenna navigation requires an easily reprogrammable software defined radio solution. Various receiver architectures for this purpose have been introduced. RF front-end with FPGA universal correlators on ExpressCard connected directly to PC was selected and manufactured. Such a~unique hardware combination provides the GNSS researchers and engineers with a~great convenience of writing the signal processing algorithms including tracking, acquisition and positioning in the Linux application programming interface and enables them to reconfigure the RF front-end easily by the PC program. With more of these ExpressCards connected to the PC, the number of the RF channels, correlators or antennas can be increased to further boost the computational power. This paper reveals the implementation aspects of the receiver, named the Witch Navigator, and~gives the key test results

Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers

Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity