Objective To solve the problem of excessive sidelobe level in multi-constrained sparse linear arrays,the direction map synthesis method based on the improved artificial hummingbird algorithm was proposed.Methods The new algorithm dynamically adjusteds the transition probability to select the guided foraging and territorial for-aging methods through segmented inertia weights,balancing the local and global search capabilities of the algo-rithm.the Cauchy-Gaussian variation was introduced to enhance the anti-stagnation capability of the algorithm so that the algorithm was able to get rid of the tie of local optimum,which greatly improved the optimization capabili-ty.Finally,HFSS electromagnetic simulation was performed on a real array antenna and the excellent results were obtained.Results The new algorithm achieved the comprehensive optimization of sparse linear arrays for suppress-ing the peak sidelobe level of the array antenna under the constraints of the given array aperture,the number of array elements and the minimum spacing of the array elements.Conclusion Compared with the traditional method,the method here is able to obtain lower peak sidelobe levels under different constraints,and the new algorithm possesses better optimization ability and stability.
array antennassparse linear arrayartificial hummingbird algorithmpeak sidelobe levelHFSS electromagnetic simulation
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