Clutter-Aided CFO Estimation for Integrated Sensing and Communication Systems

Abstract

Carrier frequency offset (CFO) severely degrades parameter estimation in orthogonal frequency-division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems because it is coupled with target Doppler shifts. In this letter, we propose a clutter-aided (CA)-space-alternating generalized expectation-maximization (SAGE) algorithm that exploits dominant scattering components to decouple the common frequency offset from target Doppler shifts and jointly estimate target ranges and velocities. The CFO is inferred from the frequency group supported by multiple scattering clusters and refined via maximum likelihood optimization. A closed-form Cramér-Rao lower bound (CRLB) is derived to characterize the performance limits. Simulations show that the proposed method resolves the CFO–Doppler coupling, achieves near-CRLB performance, and outperforms baseline schemes.