# Low-Cost SDR for GNSS Interference Mitigation Using Spatial Diversity Techniques +
## 5 Conclusions  
The present paper evaluated the feasibility of exploiting spatial diversity in GNSS mass-market receivers, whose performance in adverse conditions is largely affected by their low-cost components. To solve these deficiencies, the use of two low-complexity multi-antenna techniques was analyzed and proved to be effective when counteracting the effects of undesired contributions, which remain a serious threat in the GNSS domain. The two techniques under study, the PI and PREW beamformers, were implemented using a representative mass-market SDR, the KrakenSDR, whose four channels were configured forming a ULA. This device, together with the Spinert simulator, allowed us to analyze the behavior of the GNSS receiver implementing the two beforementioned techniques when a CW interference is present. The results obtained prove the efficiency of multi-antenna algorithms in this domain, particularized for the cases of the PI and PREW beamformers, showing that the negative impact of external contributions can be effectively mitigated by deploying undemanding beamforming techniques suitable for low-cost devices. Conceptualization, L.P.-R., D.G.-C. and N.B.-L.; methodology, L.P.-R., D.G.-C. and N.B.-L.; software, L.P.-R.; formal analysis, L.P.-R.; writing--original draft preparation, L.P.-R.; writing--review and editing, all authors; supervision, all authors. All authors have read and agreed to the published version of the manuscript. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partly supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. Not applicable. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partly supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. Not applicable. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partly supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partly supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTRTR. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partially supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTRTR. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partially supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR. This research was conducted during a six-month internship at the European Space Agency (ESA). This work has also been partially supported by the Spanish Agency of Research (AEI) under the grant PDC2023-145858-I00 funded by MICIU/AEI/10. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] IEEE 802.11 be Wi-Fi 7: New Challenges and Opportunities. _IEEE Commun. Surv. Tutor._**2020**, _22_, 2136-2166. [CrossRef]
* _[PERSON] et al. (2017)_ [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Adaptive probabilistic model using angle of arrival estimation for IoT indoor localization.