With the fast growing diffusion of the real-time high accuracy applications based on the Global Navigation Satellite System (GNSS), the robustness of the GNSS receiver performance has become a compelling requirement. Disruptive effects can be induced to the signal processing stages of GNSS receivers due to the disturbances from Radio-Frequency Interference (RFI), even leading to a complete outage of the positioning and timing service. A typical RFI threat to the GNSS signals is represented by portable jammers which transmit swept-frequency (chirp) signals in order to span the overall GNSS bandwidth. The implementation in the receivers of Adaptive Notch Filters (ANFs) for chirp cancellation has been extensively investigated and proved to be an efficient countermeasure. However, the performance of ANF is strongly dependent on its configuration setup. Inappropriate parameter settings of the ANF for interference removal may induce severe distortion to the correlation process. In addition, an effective mitigation will still introduce a vestigial signal distortion contributed by the residual unmitigated chirp and the ANF operation itself, being not negligible for high accuracy solutions. This paper addresses the detailed analysis for assessing the effects of interference mitigation by notch filtering. A bias compensation strategy is proposed, wherein for each Pseudo Random Noise (PRN) the biases due to the parameter settings of the notch filter are estimated and compensated. The impact of using the ANF operation on chirp signals at the acquisition and tracking stages of GNSS receivers is analyzed. On the basis of the three proposed metrics, the effects can be quantitatively estimated to depict a complete picture of the most influential parameters of the chirp and the ANF configurations, as well as the optimal achievable performance at the acquisition and tracking stages.

Adaptive Notch Filters have been widely investigated in literature for their low complexity and good performance, and used in many signal processing applications. More recently they have been proven to be an effective solution against jamming interferences, considered more than ever a real threat to Global Navigation Satellite System (GNSS) signals.

Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests.

The Software Defined Radio (SDR) technology, applied to the reception of Global Navigation Satellite Signals (GNSS), allows the implementation of a positioning device with a high flexibility level. The advantage is twofold: not only the GNSS SDR receiver can be easily updated during its operational life, but it becomes an outstanding tool in prototyping innovative algorithms for signal processing and signal quality monitoring. These aspects have been the key-drivers to the implementation of the NGene fully software receiver, developed by the NavSAS group in Torino. This paper exemplifies some of the opportunities opened by SDR in the field of GNSS receivers.

The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites have been looked at as a good opportunity for GNSS RFI monitoring, and the last five years have seen the proliferation of many commercial and academic initiatives. In this context, this paper proposes a new spaceborne system to detect, classify, and localize terrestrial GNSS RFI signals, particularly jamming and spoofing, for civil use. This paper presents the implementation of the RFI detection software module to be hosted on a nanosatellite. The whole development work is described, including the selection of both the target platform and the algorithms, the implementation, the detection performance evaluation, and the computational load analysis. Two are the implemented RFI detectors: the chi-square goodness-of-fit (GoF) algorithm for non-GNSS-like interference, e.g., chirp jamming, and the snapshot acquisition for GNSS-like interference, e.g., spoofing. Preliminary testing results in the presence of jamming and spoofing signals reveal promising detection capability in terms of sensitivity and highlight room to optimize the computational load, particularly for the snapshot-acquisition-based RFI detector.