Optimization Of Sparse Planar Arrays Antenna For Foreign Object Debris Detection On Runways

Foreign object debris on runways are the foreign objects scattered on the runway. This thesis pays attention to optimize sparse planar arrays antenna system of the millimeter-wave radar monitoring system, in order to that the antenna beam scanning system can be implemented, can reduce costs of the antenna system and the antenna system has better performance. In optimizing sparse planar arrays antenna system, under conditions of number of array elements, the array element spacing and aperture, optimize the distribution of array elements to obtain a lower peak sidelobe level (PSLL).In this thesis, modified genetic algorithms (MGA) and improved particle swarm optimization (PSO) are used to optimize sparse planar array antenna, the main work and innovations are:1. The superiority of the millimeter-wave radar monitoring system is introduced, then the needs of the millimeter-wave radar monitoring system to antenna system are detailedly analysed, and feasibility and advantages of using sparse planar antenna array are given.2. The basic theory of the array antenna is introduced, then the various forms linear array and planar array are detailedly analysed, and the corresponding pattern function and optimization design model are given.3. On the basis of MGA, dimensionality reduction algorithm is used to optimize sparse ring array antenna. The method transforms two-dimensional planar array into one-dimensional linear array, and greatly reduces the computation time and the complexity of the model. Comparison with the existing research results, the simulated results prove effectiveness; On the basis of MGA, the optimizing radii method used to optimize sparse ring array antenna, indirectly optimizes array element position, and reduces optimal amounts and optimal time. And comparison with the existing research results, the simulated results confirm the efficiency and the robustness of the algorithm.4. On the basis of PSO, adjusting speeds particle swarm algorithm and increasing disturbance particle swarm algorithm are used to optimize sparse planar array, so that the particles can dynamically adjust the direction of the study in an iterative process, and avoid the phenomenon of local optimum. Comparison with the PSO research results, the simulated results show its effectiveness.