Fluid Antenna Array-based MIMO Radar: Adaptive Sensing via Joint Waveform and Array Design

Fluid antennas (FAs) offer dynamic and flexible reconfiguration capabilities, including free positioning on a surface or array, surpassing the limitations of conventional solid-state antennas. Building upon this paradigm, fluid antenna arrays (FAAs) hold significant potential to enhance the performance of wireless communication and radar systems. This paper investigates the design of an FAA-based MIMO radar system aimed at improving target detection in complex interference environments. Specifically, we leverage the free positioning capability of FAA elements by introducing the antenna position vector (APV) as an additional degree of freedom, jointly optimized with transmit waveforms and receive filters. The design problem is formulated as the maximization of the signal-to-interference-plus-noise ratio (SINR), subject to practical constraints such as waveform unimodularity (for power amplifier efficiency) and minimum inter-element spacing (to mitigate mutual coupling). To solve the resulting nonconvex optimization problem, we develop an efficient iterative algorithm based on block majorization-minimization (B-MM). Simulation results demonstrate significant performance gains achieved through the joint optimization of antenna positions and waveforms. Notably, the proposed approach automatically balances angular resolution and sidelobe suppression via optimal antenna placement. Furthermore, the benefits of FAA optimization are particularly evident in resource-constrained scenarios, where optimizing antenna positions alone can yield SINR improvements comparable to those achieved through waveform design, highlighting the strong practical potential of FAAs in next-generation radar systems.