Research On Muilti-beamforming Technique Of Opportunistic Array Radar

Opportunistic Array Radar is a new type of high-performance radar system.This radar system is based on digital array technology and can simultaneously integrate multiple functions and multiple modes.Unlike the array distribution of traditional radars,the opportunistic array radar array unit can be placed at any position as required.Multi-beamforming technology is an important step to realize opportunistic array radar.This article focuses on the digital multi-beamforming technology of opportunistic array radar.The main work is as follows:1.Based on the study of the principle of opportunistic array radar and its beamforming technology,this paper introduces the time modulated line arrays technology to the uniform linear opportunistic array for the design and processing complexity of conventional array antenna multi-beamforming technology.The time modulated line arrays are based on the phased array,which increase the time dimension.With the same number of array elements,it can form more beams than the phased array.Then,the differential evolution algorithm is used to optimize the peak side lobe levels of the multi-beam antenna pattern formed by a uniform linear opportunistic array.In order to solve the problem of early maturity of differential evolution algorithms,an improved method that introduces adaptive mutation operator with extended aggregation degree is proposed and compared with other algorithms.Simulation results show that the improved differential evolution algorithm can further reduce the value of the peak side lobe level of the desired beams,and the performance of the algorithm is further improved.2.Based on the basis of uniform linear opportunistic array,this paper further studies the multi-beamforming algorithm of non-uniform linear opportunistic array.Firstly,the time modulated array technology is used for shared aperture multi-beamforming.A linear array is randomly and sparsely interleaved into two time modulated arrays,and the control time sequences of the two sub-arrays are calculated separately.In order to improve the diversity of the population,the scale factor and adaptive cross probability factor of the sinusoidal iterative chaotic system are introduced.Finally,the control time sequences of the two sub-arrays are optimized by reducing the maximum sidelobe levels of the two sub-arrays.Simulation results show that the value of the peak side lobe level of the desired beams can be lowered by the improved differential evolution algorithm in this paper,and the performance of the algorithm is further improved.3.In order to solve the shortcomings caused by the actual coverage of the linear array azimuth and the change in scanning angle,a circular beam array multi-beamforming algorithm is studied.Aiming at the problem of insufficient search depth of the differential evolution algorithm,the position update formula of the wind-driven algorithm is used to replace the selection of individuals in the mutation operation of the differential evolution algorithm.Based on this,the array factor of the array element is used as the optimization variable,that is,the optimal array element position distribution to reduce the peak side lobe levels of two desired beams as an optimization goal.An optimization model has been established to verify the effectiveness of the algorithm,and the algorithm has been compared with other algorithms under the same simulation conditions.Simulation results show that the effectiveness of the proposed algorithm in multi-beamforming of circular opportunity array.