Constrained Optimization Of Planar Sparse Array For Polarized Phased Array Radar

Polarized phased array radar has great application potential in polarization matching reception and interference suppression because it can acquire the polarization information of space electromagnetic signals.Polarized beamforming is a key technology for polarized phased array radars,especially the optimal polarization beam with main lobe polarization matching,side lobe nulls and polarization matching,which has the function of matching reception and interference suppression.However,most of the current algorithms are based on one-dimensional linear arrays.They are not suitable for practical engineering.Considering the expensive design cost of planar arrays,the application prospects are limited.Therefore,the polarization array is sparse.An effective way to solve this problem.The paper studies the problem of planar sparse array constrained optimization for polar phased array radar.The specific research contents are as follows:(1)Aiming at the sparse optimization problem of planar array with fixed polarization,a hybrid evolution strategy differential evolution algorithm is proposed.Taking the peak side lobe level as the objective function,constraining the array aperture,the number of array elements and the minimum spacing,the planar array sparse optimization of fixed polarization is completed.The simulation results show that the proposed algorithm can effectively reduce the peak side lobe level of the planar sparse array,and adjust the mutation probability factor according to the demand to achieve a balance between the convergence speed and the global search ability.(2)Aiming at the problem of planar sparse array constrained optimization with fixed polarization,a differential evolution algorithm with mixed trigonometric mutation is proposed.The side-lobe nulls concave constraint matrix is introduced to construct an adaptive penalty function to complete the planar sparse array with side lobe nulls concave constraints.optimization.The simulation results show that the proposed algorithm can obtain a large nulls concave gain in the direction of the incoming signal of the interference signal while optimizing the peak side lobe level of the planar sparse array.(3)Aiming at the sparse optimization problem of planar array with optimal polarization constraint,a method based on convex optimization and multi-objective differential evolution algorithm is proposed.The polarization matching mean square error is introduced,and the peak side lobe level and the polarization matching mean square error are used as two objective functions to complete the optimal polarization beam constrained planar array sparse optimization.The simulation results show that the proposed method can achieve planar array sparse optimization while forming the main lobe polarization combined with the side lobe nulls concave surface and the polarization constrained optimal polarization beam.