Dimensionality Reduction And Beamforming Technology For Large Scale Phased Array

In the field of phased array radar signal processing,compared to traditional mechanical radar,the all-digital phased array radar gets rid of carrier platform mobility limitations,can realise large aperture phased array radar.Large phased array has many advantages when beamforming,such as narrow beamwidth,high radiation gain,long detection range,large array degree of freedom,etc,these advantages allow the radar to detect long-range,fast,and multi-target signals efficiently.However,the multi-channel problem caused by multiple elements,not only increases the cost and difficulty of project implementation,but also increases the complexity of related algorithms.Based on the purpose of dimension reduction for large array,this thesis first studies several subarray division methods,and discusses the advantages and disadvantages of those methods,laid the foundation for the application of subsequent subarray division technology.In addition,different from traditional planar array,there are more and more irregular arrays generate to accommodate the diversity of practical conditions for phased array radar applications,such as conformal array,opportunistic array,combinatorial array,etc.For this question,this thesis abstracts out a subarray beamforming question basing on conformal array,conformal array means that each subarray is not in the same plane.Through analyzing algorithm simulations and results,the conformal array subarray beamforming algorithm has been shown to be effective.Based on the traditional monopulse tracking and direction technology,this thesis proposes a 4-channel monopulse angle measurement of sum and difference beams for dimension-reduced phased array,which adding double-difference channels to the traditional single-pulse 3-channel angle measurement of sum and difference beams,this technique improves the monopulse angle estimation and the improvement is significant for signals incident from the edge of the beam.This algorithm combines the advantages of 3-channel and 4-channel angle measurement,improves the efficiency of angle estimation.Due to different objective actual conditions,the requirements for phased array radar patterns are also different.This thesis first studies several traditional pattern synthesis methods,furthermore,the particle swarm optimization algorithm is used to optimize the subarray division and the phase weighting at the same time,so that the resultant pattern parameters meet the desired requirements.Among them,this thesis improves the particle swarm algorithm for weight optimization,using phase-only weighting techniques,which not only reduces the number of optimization parameters,but also has good robustness against errors caused by frequency jitter.In addition,the improvement of the selection of phase-weighted initial value effectives accelerates the convergence speed of the algorithm.Through simulation and comparison,it is proved that the algorithm can achieve the desired effect.