基于改进种群算法的光学相控阵多目标栅瓣优化

Optical phased array multi-objective gate optimisation based on improved population algorithm

  • 摘要: 光学相控阵因宽视场、高精度、指向灵活特性在全固态激光雷达等研究中备受关注。栅瓣水平、扫描范围和主瓣强度等指标都会影响其性能的优劣。针对多指标同步优化问题,提出一种基于改进种群算法的优化方案。该方案以哈里斯鹰种群算法为基础,通过改进迭代过程并引入二代非支配遗传算法(NSGA-Ⅱ)中快速非支配排序与拥挤度距离实现多目标优化。以一维64阵列光学相控阵光场优化进行模拟实验,边模抑制比在双目标和三目标分别达到−16.11 dB和−14.29 dB,并且主瓣强度和扫描范围指标数值均维持在较高的状态,实现了多个指标同时优化,对光学相控阵激光雷达的整体优化具有深刻意义。

     

    Abstract:
    Objective Optical phased arrays have attracted much attention in the research of all-solid-state lidar systems due to their wide field of view, high accuracy, and flexible pointing characteristics. The simultaneous optimisation of metrics such as gate level, scanning range and main flap intensity is a guarantee for its high performance. In the existing research methods, the use of non-equally spaced arrays to inhibit the grating is a common means, scholars commonly used algorithms to achieve this process, as well as other performance indicators, some scholars are also in the research. However, most of their studies are independent and do not consider the overall needs. And the relationship between the indicators is more complex, it is difficult to optimise multiple indicators at the same time to the ultimate situation. In order to meet the overall needs of multi-indicator optimisation, a multi-objective optimisation scheme based on improved population algorithm is proposed.
    Methods The scheme of this paper is based on the Harris Hawk population algorithm awakening improvement. In terms of algorithm iteration, the use of good point set initialization to generate more ephemeral first generation, using Levy flight to speed up the exploration process, nonlinear function for search transformation, double perturbation strategy to jump out of the local solution; in the direction of multi-objective optimization, the use of fast non-dominated sorting as well as congestion distance strategy to achieve the sorting of multiple indexes in the algorithm, coupled with the elite strategy to retain the good individuals of the previous generation, to complete the overall algorithmic scheme design(Fig.4). Finally, simulation software is used to simulate the experiment and get the results.
    Results and Discussions The optimisation of the three schemes at a deflection angle of 0° was found to achieve multi-objective optimisation for all schemes, with an improved level of gate flap suppression of up to −16.11 dB, a reduction of 80.3%, and a scanning range of 37.4° (Fig.5). The scheme was then compared with the results for different deflection angles, different array ranges and different array spacings, and it was found that the gate flap could be suppressed, the main flap could be strengthened and the scanning range could be extended. The comparison of this scheme with other multi-objective optimisation methods (Fig.7, Tab.2) proved the superiority of the multi-objective optimisation scheme in this paper.
    Conclusions An optical phased array alignment scheme based on an improved multi-objective Harris Hawk algorithm is proposed for non-equally spaced multi-directional array optimisation. The algorithmic scheme obtained −16.11 dB side-mode rejection ratio of the side flap and more than 4000 main flap intensity in the two-objective optimisation, respectively, and the gate flap decreased by 80.3%; and the three-objective optimisation obtained −14.29 dB side-mode rejection ratio of the side flap, which is decreased by 59.9%, and there was 37.4° scanning range and more than 4000 main flap intensity, which successfully achieved the suppression of the gate flap and the enhancement of the optical beam. It helps the subsequent simulation and practice to improve the overall performance of optical phased array lidar.

     

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