Abstract: The power system with high-proportion renewable energy has low inertia level and high uncertainty. The system inertia level is closely related to the dynamic frequency response process. Considering the spatio-temporal correlation of frequency response process between nodes within the system, dynamically quantifying the spatio-temporal correlation of frequency between nodes provides an effective technique for real-time inertia estimation in the new power system. Firstly, a calculation method for inertia of synchronous units and renewable energy generator units is proposed. Secondly, the Granger causality test algorithm is used to dynamically analyze the frequency correlation of different nodes in the system, thereby establishing a time-varying spatiotemporal causal correlation set of system frequency. Furthermore, based on the swing equation of frequency response processes of various nodes in the system, a system inertia-frequency state space model is constructed. Subsequently, a novel method for estimating the inertia of power system with high-proportion renewable energy is proposed using the unscented Kalman filter and fixed-lag smoother. Finally, the proposed method is validated using an improved IEEE 39-node system, demonstrating its effectiveness and applicability. Results show that the proposed method ensures consistent inertia estimation performance in different renewable energy penetration rates and frequency disturbance scenarios, which has engineering application potential.