Frequency diverse array (FDA) has a distance‐angle–dependent beam direction map, which has a greater application advantage than phased array. However, due to the distance‐angle coupling and periodicity of its beam direction map, it makes the parameter information of the target obtained through FDA have ambiguous phenomena. Currently, researchers mostly use different types of frequency offsets, array element arrangement, and optimized parameters to eliminate the coupling and periodicity, but the effect is poor and does not consider the balance between the main flap width, side flaps, and gate flaps. We introduce an improved distributed array with two ends transmitting and middle receiving into the FDA‐MIMO radar and propose a new distance‐angle decoupled beam formation method to eliminate the coupling and periodicity of the FDA beam. The method utilizes the NSGA‐II algorithm to jointly optimize the frequency offset increment and array element layout to achieve complete decoupling of the distance‐angle dimension and spot beam focusing and significantly suppresses the sidelobes and eliminates the grating flaps, providing flexible and adjustable beam characteristics. Simulation results demonstrate the effectiveness of this scheme.

Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar offers significant advantages in mainlobe deceptive interference suppression, as its transmit steering vector contains both angle and range information, providing additional degrees of freedom beyond the angular dimension. However, conventional FDA-MIMO radar suffers from insufficient angle-range resolution, which limits its ability to suppress interferences located close to the target. Moreover, it lacks robustness under limited snapshots and parameter mismatch conditions. To address these issues, this paper proposes a robust beamforming method based on the FDA-MIMO radar model. A collocated sparse array with a sinusoidal element spacing offset and a logarithmic frequency offset is adopted to enhance beam resolution and resolve the periodic angle-range ambiguity problem. Based on this model, the interference-plus-noise covariance matrix is reconstructed using two-dimensional Capon spatial spectrum, and the steering vector is corrected via a joint objective function that combines MUSIC orthogonality and the flatness of the covariance residual spectrum. Simulation results demonstrate that, under conditions of near-target interferences, random range-angle errors, and frequency offset errors, the proposed method achieves a signal-to-interference-plus-noise ratio (SINR) close to the ideal value, exhibiting excellent mainlobe interference suppression performance and robustness.