Joint Multi-Target Estimation in ISAC-Enabled OFDM Systems

This paper introduces a novel multi-target parameter estimation algorithm designed for orthogonal frequency division multiplexing based integrated sensing and communication (ISAC) systems, focusing on enhancing target resolution while maintaining computational efficiency. The algorithm exploits the unique properties of Slepian sequences, which offer band-limiting and filtering characteristics across time, frequency, and spatial domains. By iteratively applying Slepian projection and cancellation techniques, the method improves the resolvability of targets and facilitates joint estimation of range, velocity, and angle for multiple targets. This approach addresses the limitations of conventional methods, such as the high computational complexity of subspace decomposition in multiple signal classification and the limited resolution of 3D-discrete Fourier transform based techniques. Simulation results validate the effectiveness of the approach, demonstrating its potential for real-world ISAC applications, where high-accuracy, low-complexity solutions are crucial for multi-target tracking and sensing.