# Variance-Triggered Two-Step GPS Acquisition
## 7 Conclusions  
This paper presents the Variance-Triggered Two-Step (VTTS) algorithm, a robust method for the efficient acquisition of GNSS signals. It is based on strategies that explore the signal characteristics to reduce acquisition time without increasing the hardware requirements. Additionally, the new technique uses less memory than the conventional approach in the proportion of the number of samples per chip, i.e., the higher the sampling frequency, the larger the memory saving offered by the VTTS acquisition.  
Results of extensive experiments with simulated GPS signals with different levels of noise demonstrated that the proposed method presents lower false positive rates than the conventional Serial Acquisition (SA) with slightly better success rate, both at low and high levels of noise. Moreover, the time to acquisition of the VTTS algorithm is about 1/5 of the SA for similar levels of success rates.  
The VTTS acquisition achieves a comparable success rate already with 10 rounds, as Figure 8c shows. With 16 rounds, the VTTS presents a superior success rate for all C/N0 ratios, except for very high ratios where all methods reach the maximum success rate, as seen in Figure 8d. Moreover, as Figure 10 shows, the VTTS method with 16 and 10 rounds is much faster than all other methods for all levels of C/N0 ratios.  
The levels of improvement in success and false-positive rates and in acquisition time were possible due to a variance-triggered detection threshold that allows arbitrary-size correlation peaks to be detected incrementally during a Coarse Search (CS) step. Although the CS step of the VTTS acquisition may generate false-positive overhead working at lower resolutions to reduce computational complexity, the final success rate is not affected or even improves, when compared to the conventional SA, because a Fine Search (FS) step follows the CS step to ensure higher search resolution.  
As future work, we pretend to analyze the robustness of the proposed method for longer integration periods, to explore its intrinsic parallelism to further improve acquisition time, to extend the approach to other types of GNSS signals, and to develop a working prototype system with a radio-frequency front-end for use with real signals.  
Conceptualization, F.C. and S.X.-d.-S.; Data curation, F.C.; Formal analysis, F.C., L.F.S. and S.X.-d.-S.; Investigation, F.C.; Methodology, C.V. and S.X.-d.-S.; Project administration, S.X.-d.-S.; Resources, C.V. and S.X.-d.-S.; Software, F.C. and G.L.A.; Supervision, L.F.S., C.V. and S.X.-d.-S.; Validation, F.C., G.L.A. and S.X.-d.-S.; Visualization, F.C.; Writing--original draft, F.C. and S.X.-d.-S.; Writing--review and editing, G.L.A., L.F.S. and C.V.  
This research was funded by Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior--Brazil (CAPES)--Finance Code 001, and the APC was funded by Universidade Federal do Rio Grande do Norte (UFRN)  
This study received the support of the High-Performance Computing Center at UFRN (NPAD/UFRN) for the use of computational resources.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.