Research On Beamforming And Sidelobe Suppression Techniques Of Distributed Frequency Diverse Array With Planar Subarrays

Different from the traditional phased array(PA)radar,the frequency diverse array(FDA)radar has the biggest characteristic that there is a certain deviation between the transmitting frequencies of different array elements,thus a spatial beam pattern with dual dependence characteristics of range dimension and angle dimension is formed.This feature makes FDA have broad application potential in radar transmit and receive beam energy control,range dimension-angle dimension joint positioning,and range dimension dependent interference suppression.In order to scan the target with high-dimensional beams and observe its beam energy state in the actual physical space,the relative beam theory of linear frequency diverse array(LFDA)is extended to the planar frequency diverse array(PFDA).At the same time,the distributed array(DA)has the advantages of strong battlefield survivability,flexible deployment and high positioning accuracy due to its unique array configuration.Therefore,this thesis introduces the FDA technology into the field of DA radar target detection,and constructs a distributed frequency diverse array with planar subarrays(DFDA-PS)model.The DFDA-PS model can achieve a range and angle-dependent beam pattern with higher gain and narrower main lobe width by increasing the physical aperture of the array.However,the subarrays of the DFDA-PS are sparsely distributed with a uniform large spacing in space,which generates high grating lobes in the range and the angle dimensions,and further leads to the misjudgment of target when performing the target detection task.It greatly increases military costs and reduces operational efficiency.Therefore,this thesis focus on the beamforming and sidelobe suppression techniques based on the DFDA-PS model and the main contributions of it include:1.For the PFDA model,a low sidelobe beam synthesis method based on the invasive weed optimization(IWO)algorithm is given.At the same time,the minimum variance distortionless response(MVDR)adaptive beamformer is designed.Firstly,an objective function is constructed by combining beam energy focusing and dual peak sidelobes level,and the IWO algorithm is used to optimize the low sidelobe beam synthesis.The simulation results show the excellent beam focusing ability and sidelobe suppression ability of the proposed method.Then the MVDR adaptive beamformer is theoretically deduced in PFDA high-dimensional scene,and further combined with the characteristics of PFDA array factor,an adaptive beamforming method based on frequency offset selection schem(FOSS)is proposed,which can dynamically adjust the frequency offset in different directions according to the target position and the interference position,so as to achieve a peak focused beam at the target source azimuth and a deep zero-notch beam at the interference source azimuth.Simulations show that the proposed beamforming method has better azimuth nulling effect and signal to interference plus noise power ratio(SINR)performance,which verifies the feasibility and accuracy of the proposed method.2.For the DFDA-PS model,the niche technology(NT)and tabu search(TS)strategies are integrated into the genetic algorithm(GA),and a method for range dimension-angle dimension dual high grating lobes suppression method is presented.In this method,the subarray position and the corresponding subarray frequency offset of the DFDA-PS model are taken as the target optimization objects,and the fitness function is constructed by minimizing the dual peak sidelobes level in the range dimension and the angle dimension.Unlike traditional GA,the pre-selection mechanism of NT means is firstly performed on the offspring individuals after GA operation to ensure the distribution characteristics of population diversity and avoid a large increase in other individuals in the group in the proposed method.The rule judgment of GA falling into stagnation is set and once the stagnation rule is satisfied,the TS algorithm with excellent mountain climbing ability can perform an iterative search to enhance the search ability of the global optimal solution in the feasible region of the spatial solution.Simulation results show that,compared with the traditional GA,the proposed improved GA can effectively suppress the dual high grating lobes in the range dimension and angle dimension,thus the low sidelobe beam synthesis of the DFDA-PS model is realized.