A Super-Resolution and High-Accuracy Range Estimation Algorithm for ISAC Systems

This paper proposes a search space-based range estimation algorithm with enhanced accuracy and super-resolution. The proposed algorithm first estimates the coarse range of the target and constructs a search space containing a collection of range candidates. Then, the algorithm subtracts the sinusoid induced by each range candidate from the normalized backscattered signals and applies inverse discrete Fourier transformation (IDFT) to the residual signals. The smaller the difference between a range candidate and the actual range, the more the effect of the target-induced sinusoid is mitigated. Therefore, the range candidate that most effectively mitigates the corresponding peak in the IDFT result is identified as the most accurate range. Compared to the conventional IDFT algorithm, simulations show that the proposed algorithm improves range accuracy from the decimeter level to the centimeter-level.