Multi-Target Joint Collaborative Sensing for Distributed MIMO-OTFS Radar Systems

The Orthogonal Time Frequency Space (OTFS) modulation, operating in the delay- Doppler (DD) domain, possesses notable advantages in Doppler robustness, multipath suppression and power efficiency, making it a compelling candidate for future sensing applications in highly dynamic environments. However, existing single-site or co-located Multiple-Input Multiple-Output (MIMO)-OTFS radar systems face limitations in wide-area surveillance, including insufficient detection performance under low signal-to-noise ratio (SNR) conditions, limited weak target detection capability, and constrained parameter estimation accuracy. To address these challenges, this paper proposes a distributed MIMO-OTFS radar architecture based on DD-domain collaborative sensing. We construct a multi-station collaborative topology using orthogonal waveforms and establish the end-to-end signal transmission model. Subsequently, we design a comprehensive collaborative sensing process, where each site first performs low-complexity coarse target detection via two-dimensional matched filtering, followed by multi-target registration and matching using the minimum distance error criterion. Based on this, a golden-section iterative off-grid refinement algorithm achieves fractional-level range-velocity estimation accuracy. Simulation results validate the effectiveness of the proposed framework, successfully achieving collaborative joint parameter estimation and registration for multiple targets. In the simulated 2× 2 distributed configuration, the proposed system achieves an average peak SNR gain of 1.43 dB compared to single-station systems, and the off-grid estimation accuracy approaches the Cramér-Rao lower bound. This study provides a feasible solution for practical distributed OTFS sensing.