实时高精度位置服务是社会发展的必然需求，但其依托的精密单点定位（PPP）性能却常受复杂动态观测环境、初始化时间长、重收敛速度慢、实时周跳探测成功率低等因素影响，难以满足高精度高时效的应用，如无人驾驶、室内外无缝定位等。本课题拟着眼于北斗/多系统多频率GNSS快速发展的契机，以实时PPP和惯性导航（INS）理论为基础，开展顾及电离层和码间偏差时空约束的多系统多频GNSS PPP与INS实时紧组合理论及方法研究，突破系统间偏差/频率间偏差/码间偏差、非线性耦合误差、实时非差周跳探测等难点，利用电离层和码间偏差短期稳定性和INS短期高精度优势，融合多系统多频GNSS实时观测、抗差-自适应理论、非线性卡尔曼滤波、INS辅助GNSS周跳探测等理论，实现高精度实时定位。预期研究成果将能显著改善复杂动态环境下GNSS/INS定位的连续性、可靠性、收敛速度和定位精度，拓展其在实时精密位置服务中的应用前景。

Real-time high-accuracy positioning service is becoming a basic need along with human social development. However, the current used method, Precise Point Positioning (PPP), is influenced seriously by the users’ challenging environments (especially in dynamic applications), long initialization time, slow re-convergence speed, and low success rate of cycle slip detection in real-time, respectively. Therefore, it is hard to meet the time/accuracy-critical requirements in automatic driving, navigation indoor and outdoor, etc. We will study the theory of the real-time tight integration between PPP and Inertial Navigation System (INS) by using the multi-constellations and multi-frequencies GNSS observations, in which the spatial-temporal constraint modes of ionospheric delays and differential code biases are established. Meanwhile, the inter-system bias, inter-frequency bias, and differential code bias in multi-GNSS PPP will be modeled and estimated to improve the accuracy and convergence of PPP. We also will study the theories of nonlinear Kalman filter, robust-adaptive filtering, and INS aided undifferenced GNSS cycle slip detection to solve the problems of nonlinear coupled errors in GNSS/INS system, gross errors and low-quality observations, and low success rate of cycle slip detection in real-time. Based on these effects, we expect to reach our goal of providing high-accuracy positioning solutions by GNSS PPP/INS tight integration in real-time challenging dynamic conditions with rapid speed of initialization and re-convergence and high continuity and reliability. The final outcome of this project will make a significant improvement for the applications and services of multi-GNSS PPP/INS tight integration in real-time.