High-Accuracy Ranging Scheme for ISAC-OFDM Systems with Adaptive Chirp-Z Transform

Integrated sensing and communication (ISAC) is a key technology for autonomous navigation. It employs orthogonal frequency division multiplexing (OFDM) for high-precision ranging, yet its sensing performance remains constrained by the system's range resolution. To address these challenges, this paper presents a high-accuracy ranging algorithm for OFDM-ISAC that adaptively determines the Chirp Z-Transform (CZT)'s refinement region through spectral feature analysis. Our method begins with a coarse frequency estimate obtained via the complex periodogram. We then analyze the spectral characteristics to identify critical frequency subbands for refinement. Finally, an improved adaptive CZT is applied within the selected subband to generate refined frequency estimates. Our approach adaptively optimizes the analysis window based on local spectral features, effectively mitigating the picket-fence effect and noise sensitivity. Simulation results verify that our algorithm reduces the mean ranging error by approximately 40% compared to the baseline complex periodogram method, demonstrating significant accuracy improvement. The proposed approach exhibits strong robustness across diverse signal-tonoise ratio (SNR) conditions without introducing substantial computational overhead.