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Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobes direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was -23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures.

Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobes direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was -23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures.

Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobes direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was -23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures.

Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobes direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was -23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures.

Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobes direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was -23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures.