| The reflective array is widely known as a modern microstrip array structure because of its simple structure and easy manufacture.Compared with the parabolic antenna,the manufacturing process is simpler and the cost is lower.And compared to phased array antennas,there is no need for expensive phase shifters and complex feed networks.It is precisely due to the above advantages,this kind of reflection array antenna composed of periodic structure is gaining a wide range of attention and applications.In this paper,the design and optimization of the reflective array are studied.In the first part of this paper,a method of designing and optimizing a beamforming monolayer reflection array is proposed.In this method,a spatial mapping optimization algorithm is used to improve the matrix factor formula as a rough model to optimize the array distributions and the characteristic current numerical calculation method as a fine model to verify the correctness of the rough model optimization results.Every initial value of rough model optimization process is updated by constructing the mapping relationship between the rough and fine models for the next optimization,and then loops until finding the optimal solution that meets the conditions so as to optimize array quickly.The optimized reflection array obtains shaped beam with high gain in a specific area.The second part of this paper proposes an artificial intelligence method to optimize the reflection coefficient of the reflection array unit to find the broadband multi-bit reflection array unit.The connection between the cell surface pattern and the reflection phase was established by means of Deep learning.Finding a constant phase difference multi-bit unit by an optimization algorithm.And through the form of arrays to form a diffuse reflection front to achieve RCS reduction.Finally,the correctness and effectiveness of the proposed method for planar reflector antenna and Pixelated element diffuse reflection array are verified by numerical simulation. |
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