CAJ | 학술논문

微带天线易于产生谐波辐射，造成功率的损耗。加入DGS的微带天线可以抑制谐波，但是普通DGS会增加天线的背向功率漏射，且接地板利用率较低，分形DGS可以很好地克服这些缺点。为了缩短DGS的设计周期，采用BP神经网络对DGS进行进建模，在此基础上分析设计了一种分形DGS微带天线，并对制作的实物进行了测量，测量结果与仿真结果吻合较好，证明了该神经网络模型的正确性和分形DGS在微带天线谐波抑制中的有效性。
미대천선역우산생해파복사，조성공솔적손모。가입DGS적미대천선가이억제해파，단시보통DGS회증가천선적배향공솔루사，차접지판이용솔교저，분형DGS가이흔호지극복저사결점。위료축단DGS적설계주기，채용BP신경망락대DGS진행진건모，재차기출상분석설계료일충분형DGS미대천선，병대제작적실물진행료측량，측량결과여방진결과문합교호，증명료해신경망락모형적정학성화분형DGS재미대천선해파억제중적유효성。
The microstrip patch antenna is easier to produce harmonic radiation which waste the power. Harmonic power can be supressed by the microstrip patch antenna, but the back radiation power would be enforced. Now these problems would be overcome by the fractal DGS. The BP neural net- work of DGS is built to cut off the time used in DGS designing period. Based on the BP neural net- work model, a fractal DGS microstrip patch antenna is designed and measured, the measured results are in good agreement with the simulation ones, which prove the accuracy of the BP neural network model and the effectiveness of the fractal DGS in harmonic suppress of the microstrip patch antenna.