Antenna Array Synthesis Technology Based On Branch And Bound Algorith

Adaptive beamforming algorithm has always been an essential part of the wireless communication system.It can form nulls in the directions of the interference signals while maintaining sufficient gain in the direction of the desired signal.The performance of the spatial filter is not only related to the type of algorithm but also related to the array structure.Therefore,adaptive beamforming also needs to consider the positions of the array elements excited.The sparse beamforming algorithm can ensure superior beam performance and reduce the cost of the antenna array.There are problems of pointing deviation and high sidelobe level in the existing adaptive beamforming technology under multi-expected signals.In order to solve the above problems,this dissertation studies the array adaptive anti-jamming algorithm and sparse technology in a complex electromagnetic environment.The main research work can be divided into the following two aspects:(1)The sparse array adaptive beamforming technology under multi-expected signals is studied.Aiming at the problem of amplitude pointing error of existing spatial filtering algorithms in multi-expected signals environment,an array adaptive beamforming technology based on the branch-and-bound algorithm is proposed.The sidelobe constraint is added to the classical minimum variance distortionless response(MVDR)beamforming based on the maximum signal-to-interference-noise ratio criterion to reduce the sidelobe of the pattern and realize adaptive anti-interference.To minimize the pointing errors of multiple desired signals,auxiliary variables are employed to optimize the array response phases of the desired signals while keeping the response amplitudes unchanged.In addition,a sparse beamforming algorithm is explored to meet the needs of low-cost array antennas.Combined with the iterative reweighted l1 norm,the sparseness of the uniform array is realized under the premise of ensuring beam performance.(2)The joint sparse technique of the multiple-input multiple-output(MIMO)radar transceiver array under multi-expected signals is studied.At present,there is no effective beamforming algorithm that can simultaneously sparse the array and maintain good pattern performance under multiple waveforms.Therefore,on the basis of the algorithm proposed in the third chapter,a multiple-waveforms array sparse technique based on the branch-and-bound algorithm is proposed.The selection variable is introduced to punish the weight vectors of multiple waveforms at the same time so that multiple waveforms share a sparse array.Inspired by this,a sparse MIMO radar transceiver array technology is proposed based on the branchand-bound algorithm under multi-expectation signals.The two-dimensional group sparsity is promoted by iteratively minimizing the reweighted l2,1 norm.The spacing of the transceiver antenna is constrained to avoid the situation that an element is simultaneously used as the transmitting and receiving antenna.The joint sparseness of the transmitting and receiving array is realized.Finally,the influences of different iterative formulas on the algorithm results are compared.