The Integration of PPP, Stand-Alone double differencing carrier phase relative positioning and MEMS-Based INS

The integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS) is widely recognized as an effective approach to overcome the individual limitations of each system, resulting in a navigation solution superior to either system operating independently. Similarly, the integration of kinematic Precise Point Positioning (PPP) with Stand-Alone Double Differencing Carrier Phase (SADDCP) enables the combination of the absolute positioning capability of PPP with the high precision and low satellite requirement of SADDCP, forming an Enhanced PPP (E-PPP) solution. Furthermore, SADDCP can be integrated with a Micro-Electro-Mechanical Systems (MEMS)-based INS to generate a Relative Navigation Solution (R-NS). In this integration, the high precision of SADDCP is utilized to smooth the noisy observations of the MEMS-INS, while the independence of the INS helps mitigate the impact of cycle slips affecting the carrier-phase measurements. In this study, the integration of PPP, SADDCP, and MEMSINS is investigated to develop an innovative Enhanced PPP Navigation Solution (EPPP-NS), which combines the strengths of all three techniques while minimizing their individual weaknesses. The EPPP-NS is achieved through three levels of integration, namely: a loosely coupled integration between PPP and SADDCP to produce E-PPP, a loosely coupled integration between SADDCP and MEMS-INS to generate R-NS, and an uncoupled integration between E-PPP and R-NS to form the final EPPP-NS solution. The performance of E-PPP, R-NS, and EPPP-NS was evaluated under various GNSS environments, including open-sky conditions, limited GNSS coverage, high-multipath scenarios, and complete GNSS outages. A pre-surveyed trajectory was used as a reference to ensure accurate performance assessment. Experimental results indicate that under open-sky conditions, the performance of E-PPP is comparable to that of raw PPP, with slight improvements observed in the height component. In partially obscured environments, E-PPP provides improved continuity and enhanced positioning quality compared to raw PPP. However, in heavily obscured or high-multipath environments, E-PPP performance deteriorates and is eventually lost when the number of connected satellites falls below two for planar positioning and below three for full 3D positioning. Regarding R-NS, as a relative positioning technique, it requires initialization from a known point, which represents its primary limitation. Nevertheless, experimental results demonstrate that R-NS can provide a smooth and acceptable navigation solution for short durations under open-sky conditions before experiencing gradual drift over time, without effective bounding, monitoring, or correction mechanisms. In partially and heavily obscured environments, R-NS maintains solution continuity and successfully mitigates the impact of cycle slips in SADDCP by utilizing smoothed INS observations. However, it still suffers from significant time-dependent drift. The results confirm that EPPP-NS delivers the most stable and smoothed navigation solution compared to both E-PPP and R-NS across all tested scenarios. In open-sky environments, EPPP-NS achieves performance equivalent to E-PPP. Under partially obscured conditions, it demonstrates excellent robustness, where short interruptions in E-PPP are effectively bridged using the smoothed INS solution, ensuring continuous and stable navigation output. In high multipath areas, EPPP-NS has provided continues, precise, and smooth solution as long as the GNSS signals are available. Magna Scientia Advanced Research and Reviews, 2026, 16(02), 018-034 19 However, when GNSS signals are lost due to high multipath effect, the performance of EPPP-NS starts degrading until the connection with satellites returns back. During complete GNSS outages, EPPP-NS maintains acceptable performance as long as the influence of previously reliable SADDCP updates on the MEMS-INS, through the Kalman filter, remains effective. Beyond this period, the solution accuracy degrades over time, depending on the quality of the employed IMU sensor. Given this level of performance and robustness, EPPP-NS can be effectively applied in a wide range of engineering applications, including UAV surveying, mobile mapping systems, GIS data collection, and vehicle navigation in urban environments characterized by limited GNSS coverage and severe high-multipath effects.