Traditional GNSS Real-Time Kinematic (RTK) infrastructure requires significant financial investment and technical expertise. Recent developments in low-cost GNSS networks leverage commercially available receivers and simplified processing methods to improve accessibility. This study focuses on the practical implementation of ultra-low-cost GNSS chipsets, particularly those integrated into modern Android smartphones, for precise positioning. The broader objective is to enhance the usability of smartphone-based GNSS devices as reference or master stations in diverse fields such as location-based services, wearable technology, urban monitoring, and transportation systems. Since Google’s introduction of raw GNSS measurement access in Android 7 (2016), there has been substantial progress in carrier-phase processing using smartphones; however, the precision and reliability of these measurements remain limited due to high noise levels and frequent data unavailability. The work investigates the generation of synthetic carrier-phase measurements for Android GNSS receivers through three complementary approaches: (1) Interpolation using cubic spline method, (2) Doppler-based carrier-phase estimation, and (3) Hybrid estimation combining Doppler measurements with spline-based interpolation. These techniques aim to restore carrier-phase continuity across data gaps typically lasting 5–30 seconds, where direct measurements are unavailable due to duty cycling or weak signal conditions. Preliminary analyses on post-processed datasets demonstrate that cubic spline interpolation alone can recover up to 90% of short gaps without introducing visible cycle slips, while the integration of Doppler-derived phase rates further improves phase consistency and physical plausibility. The results highlight the feasibility of combining interpolation and Doppler modeling to reconstruct continuous phase histories from noisy, intermittent smartphone GNSS measurements. By enhancing carrier-phase availability and smoothness, the proposed framework supports improved float ambiguity estimation and relative positioning performance in low-cost RTK and Precise Point Positioning (PPP) contexts. This study contributes to the growing body of research seeking to extend precise GNSS capabilities to consumer-grade devices through signal reconstruction techniques.