Substation is one of the essential infrastructures in smart grid, and the safety and reliability are crucial for substation operation. However, the rapid advancements and high proliferation rates of drone technology have significantly lowered the barriers of drone’s entry to the commercial market, posing significant threats to the national infrastructures, including the substation. Therefore, developing drone detection technique tailored for the substation areas is an urgent task in the current stage. Different from the traditional drone detection tasks, there exist a series of interferes and noise signals around the substation, whose power could be quite strong. In this regard, we propose a Pearson correlation coefficient-based method to address this critical issue, where the drones flying around the substation areas can be effectively detected in a real-time manner. We construct the signal time-frequency spectrum by a specially designed window function, denosing and reshaping the spectrum, and complete drone detection with Pearson correlation coefficient. The performance of the proposed method is validated via simulation experiments.