Revised Dingo Optimization Algorithm for Frequency Offset Design in
FDA-MIMO Radar
Abstract
The conventional Frequency Diverse Array (FDA) system, using linear
frequency offsets, forms periodic grating lobes and coupling, which may
increase interference for potential users and difficulty in controlling
parameters. To mitigate these issues and generate a dot-shaped
beampattern, nonlinear frequency offsets are introduced to decouple the
interdependence of parameters in the range and angle dimensions.
Furthermore, to obtain the optimal nonlinear frequency offsets, we
propose an algorithm based on the FDA Multiple-Input Multiple-output
(FDA-MIMO) structure that integrates the Revised Dingo Optimization
Algorithm (RDOA) with a Kaiser window function (referred to as the RDOAK
algorithm) to form a dot-shaped beampattern. Specifically, the RDOA is
used to optimize the nonlinear frequency offset coefficients, and the
Kaiser window function is applied to adjust the waveform. Simulation
results demonstrate the superior performance of our proposed RDOAK
approach in preventing the mainlobe shift of the beampattern,
eliminating grating lobes, suppressing jammings, and achieving narrower
mainlobe width in the range dimension compared to other widely used
algorithms.