An ANN-Based Model and Design of Single-Feed Cross-Slot Loaded Compact Circularly Polarized Microstrip Antenna

ABSTRACT An artificial neural network (ANN) based model and design is proposed for single-feed compact sized circularly polarized microstrip antenna (CPMA). The training data sets for ANN-based model are collected from Ansoft HFSS v.14 for varying the dimensions of slots and slits with the size of antenna at different relative permittivity and loss tangent with best axial ratio. To achieve an accurate ANN model, Levenberg-Marquardt (LM) algorithm and three hidden layered MLP network is trained. The design antenna consists of eight slits introduced at the boundary and corners of the radiating square patch with a cross-slot in the centre. The proposed antenna shows a compactness of 42% from conventional circularly polarised antenna with 3-dB axial ratio bandwidth of 1.9%. At last, the ANN model is validated by comparing its result with the electromagnetic simulation and measurement, which shows good agreement among them. The design model may be a good choice for small antenna requirement with circular polarization for indoor WLAN application and ANN model is enormously useful to design engineers for CAD models.