To address the issue of multiple sensor requirements in current blade tip timing (BTT) techniques, which limit their practicality, this study proposes a strategy for identifying the blade natural frequency using a single sensor without prior knowledge by investigating the aliasing pattern in single-sensor BTT signals. The strategy involves time-frequency analysis of variable-speed BTT signals, projecting the time-frequency diagram onto the frequency axis, and performing peak searching on the projected diagram to identify the blade’s natural frequency using a single sensor without prior knowledge. Simulation and experimental results demonstrate the feasibility and effectiveness of the proposed identification strategy. Compared with traditional identification methods, this approach has the ability to filter out synchronous components and offers a new solution for the application of low-intrusion BTT techniques.