# Hybrid Intelligent Nonlinear Optimization for FDA-MIMO Passive Microwave Arrays Radar on Static Platforms

## TL;DR

This paper introduces a new optimization method for improving radar performance in passive microwave arrays using a hybrid intelligent algorithm.

## Contribution

A novel nonlinear frequency-offset design using a Dingo–Gray Wolf hybrid optimizer for FDA-MIMO radar systems.

## Key findings

- The method achieves high-resolution two-dimensional focusing in static scenarios.
- It enhances interference suppression and maintains stability under spatial-spectral mismatches.
- The hybrid optimizer improves beamforming flexibility and robustness.

## Abstract

Microwave, millimeter-wave, and terahertz devices are fundamental to modern 5G/6G communications, automotive imaging radar, and sensing systems. As essential RF front-end elements, passive microwave array components on static platforms remain constrained by fixed geometry and single-frequency excitation, leading to limited spatial resolution and weak interference suppression. Phase-steered arrays offer angular control but lack range-dependent response, preventing true two-dimensional focusing. Frequency-Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) architectures introduce element-wise frequency offsets to enrich spatial–spectral degrees of freedom, yet conventional linear or predetermined nonlinear offsets cause range–angle coupling, periodic lobes, and restricted beamforming flexibility. Existing optimization strategies also tend to target single objectives and insufficiently address target- or scene-induced perturbations. This work proposes a nonlinear frequency-offset design for passive microwave arrays using a Dingo–Gray Wolf hybrid intelligent optimizer. A multi-metric fitness function simultaneously enforces sidelobe suppression, null shaping, and frequency-offset smoothness. Simulations in static scenarios show that the method achieves high-resolution two-dimensional focusing, enhanced interference suppression, and stable performance under realistic spatial–spectral mismatches. The results demonstrate an effective approach for improving the controllability and robustness of passive microwave array components on static platforms.