ISAC Micro-Doppler Sensing of UAVs: Cramér-Rao Bound Analysis and Experiment Demonstration

Integrated sensing and communication (ISAC) offers a practical path to low-altitude unmanned aerial vehicle (UAV) detection using communication waveforms. This paper develops an OFDM-based ISAC framework for micro-Doppler sensing of UAV rotors. We present a system model that separates body motion and rotor-induced phase modulation and yields a within-frame rotor-only phase-modulation model after range focusing and body de-rotation. Building on this model, we derive the Cramér-Rao bound (CRB) for rotor spinning-frequency estimation and describe a multi-harmonic generalized likelihood ratio test (GLRT) for spinning-frequency estimation. To obtain time-consistent trajectories subject to low SNR and short time windows, we further design a Kalman filter with a nearly-constant-acceleration state model whose measurement variance is tied to the CRB. Numerical simulations and software defined radio (SDR) based experiments demonstrate that the GLRT approaches the CRB at moderate SNR and that CRB-informed Kalman smoothing significantly improves robustness to interference, validating the effectiveness of the proposed ISAC micro-Doppler feature estimation approach.