Optimal Arraying Technique For Sparse Array Antennas Considering Side Flap Suppression

The antenna is an important part of the radar system and its design is directly related to the operational performance of the radar.Compared with a full array where all elements are placed,a sparse array with the same aperture restriction can not only reduce the complexity and cost of the system,but also effectively reduce the peak side flap level while ensuring the main beam width is basically the same,thus meeting the engineering index requirements.Therefore,the research of sparse array antennas has important application value.In practice,a low peak bypass level is an important indicator for verifying the performance of a sparse array,which can be achieved by applying different amplitude phase excitations to the array elements and varying their positions.However,giving different amplitude phase excitations to the array is a high requirement for the power division feeder network and the cost will increase.So,the aim of this study is to rationalize the position of the array elements in order to reduce the peak side flap level.The paper begins with a detailed introduction to the radiation characteristics of array antennas,the corresponding electromagnetic concepts and the principle of array directional map multiplication;an introduction to commonly used index parameters,such as main flap width,peak side flap level,gain and directionality coefficients;compare the study examples to obtain the advantages of sparse arrays.Secondly,considering that the problem of sparse array directional map synthesis cannot be separated from the flexible use of algorithms,two improvements are proposed for the commonly used genetic algorithms,and the research results show that the mutual integration of multiple algorithms can increase the merit-seeking ability,and the hybrid harmonic search genetic algorithm is proposed in combination with the advantages of the harmonic search algorithm,which reduces the peak side flap level while improving the iteration speed;considering the disadvantage that genetic algorithms are prone to premature maturity,a probabilistic learning genetic algorithm is proposed to record the optimal individual to guide the solution process of the subsequent algorithms,so that the performance of the algorithm can be improved.Finally,the factors influencing the paraflap level of the sparse array are investigated.Three common parameters,namely the number of cells of the array antenna,the array aperture and the minimum distance between array elements,are introduced to summarize the factors and laws affecting the partials level in various cases.The results of the study show that the number of actual array elements has a greater impact.