High-Resolution Joint Range-Velocity-Azimuth Estimation for OFDM-Based Integrated Sensing and Communication

Integrated sensing and communication (ISAC) utilizing orthogonal frequency division multiplexing (OFDM) wave-forms is emerging as a critical technology for forthcoming sixth-generation mobile communication networks. The joint sensing of target range, velocity and azimuth is essential for OFDM-based ISAC systems. When the targets are highly correlated with similar range, velocity and azimuth, it is challenging for the conventional three dimensional subspace-based sensing methods to achieve accurate joint range-velocity-azimuth estimation (JRVAE), particularly in the low signal-to-noise ratio (SNR) region. Thus, this paper focuses on high-resolution JRVAE for highly correlated targets. First, a signal model is established, and the Cramér–Rao bounds for JRVAE are derived, considering communication symbols belonging to an arbitrary-order quadrature amplitude modulation constellation. Then, a high-resolution JRVAE method is proposed. Specifically, it first performs equal interval sampling smoothing on the observation signal, resulting in ambiguity in range-velocity-azimuth-induced phases, then uses the translation invariance of the signal subspace to extract the ambiguous phases, finally utilizes the orthogonality between the constructed steering vector pair and the corresponding noise subspaces to resolve ambiguity and obtaining accurate estimation. With 5G New Radio parameters setup, simulation results shows that the proposed method achieves higher resolution and accuracy compared to the conventional methods. At an SNR of -10 dB, the proposed method reduces the root mean square error in range, velocity, and azimuth by 76.0%, 82.7%, and 73.2%, respectively, compared to the benchmark scheme, while its computation cost is less than 1/3 of that of the benchmark.