GNSS Array-based Acquisition: Theory and Implementation

This Dissertation addresses the signal acquisition problem using antenna arrays in the general framework of Global Navigation Satellite Systems (GNSS) receivers. GNSSs provide the necessary infrastructures for a myriad of applications and services that demand a robust and accurate positioning service. GNSS ranging signals are received with very low signal-to-noise ratio. Despite that the GNSS CDMA modulation offers limited protection against Radio Frequency Interferences (RFI an interference that exceeds the processing gain can easily degrade receivers’ performance or even deny completely the GNSS service. A growing concern of this problem has appeared in recent times. A single-antenna receiver can make use of time and frequency diversity to mitigate interferences, even though the performance of these techniques is compromised in the presence of wideband interferences. Antenna arrays receivers can benefit from spatial-domain processing, and thus mitigate the effects of interfering signals. Spatial diversity has been traditionally applied to the signal tracking operation of GNSS receivers. However, initial tracking conditions depend on signal acquisition. Surprisingly, the application of antenna arrays to GNSS signal acquisition has not received much attention. This Thesis pursues a twofold objective: it proposes novel array-based acquisition algorithms using a well-established statistical detection theory framework and it demonstrates both their real-time implementation feasibility and their performance in realistic scenarios. The Dissertation starts with a brief introduction to GNSS receivers fundamentals, providing some details about the navigation signals structure and the receiver’s architecture of both GPS and Galileo systems. It follows with an analysis of GNSS signal acquisition as a detection problem, using the Neyman-Pearson detection theory framework and the single-antenna signal model. We derived both the optimum detector and the so-called Generalized Likelihood Ratio Test (GLRT) detector. Going further, a novel detector test statistic intended to jointly acquire a set of GNSS satellites is obtained, thus reducing both the acquisition time and the required computational resources. The GLRT is extended to the array signal model to obtain an original detector which is able to mitigate temporally uncorrelated interferences even if the array is unstructured and moderately uncalibrated. The key statistical feature is the assumption of an arbitrary and unknown covariance noise matrix, which attempts to capture the statistical behavior of the interferences and other non-desirable signals, while exploiting the spatial dimension provided by antenna arrays. The proposed algorithm is compared to conventional acquisition techniques and analyzed under realistic conditions, accounting for the presence of errors in the covariance matrix estimation, residual Doppler and delay errors, and signal quantization effects. The work introduces also the design and the implementation of a novel Field Programmable Gate Array (FPGA)-based GNSS real-time antenna-array receiver platform. A complete signal reception chain including the antenna array and the multichannel phase-coherent RF front-end for the GPS L1/ Galileo E1 was designed, implemented, and tested. The performance of the algorithms was compared to single antenna acquisition techniques, measured under strong in-band interference scenarios, including narrow/wide band interferers and communication signals. Finally, we introduce a novel software defined GNSS receiver. The proposed software receiver targets multi-constellation/multi-frequency architectures. The so-named GNSS-SDR contributes with several novel features such as the use of software design patterns and shared memory techniques to manage efficiently the data flow between receiver blocks, the use of hardware-accelerated instructions such as intermediate signals or data extraction and algorithms interchangeability.