Silva Leonardo W T, Barros Vitor F, Silva Sandro G
Launching Center of Barreira do Inferno, Brazilian Air Force, RN-063 59140-970, Parnamirim RN, Brazil.
Department of Electrical Engineering, Federal University of Rio Grande do Norte, Campus Universitário 59078-900, Natal RN, Brazil.
Sensors (Basel). 2014 Aug 18;14(8):15113-41. doi: 10.3390/s140815113.
In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence.
在开展行动时，火箭跟踪系统（RTS）会处理雷达传感器获取的轨迹数据。为了提升功能和维护水平，雷达可以通过用相控阵（PA）取代抛物面反射器（PR）天线来进行升级。这些阵列能够通过调整提供给每个辐射元件的信号来实现对辐射方向图的电子控制。然而，在相控阵雷达（PAR）项目中，问题的建模会受到产生复杂优化问题的各种激励信号组合的影响。在这种情况下，可以使用遗传算法（GA）等优化方法来计算问题的解决方案。为此，开发了具有最大-最小交叉的遗传算法（GA-MMC）方法来控制相控阵的辐射方向图。GA-MMC使用一种具有多目标、差异化编码和新的交叉遗传算子的可重构算法。该算子与传统算子的方法不同，因为它将最适应的个体与最不适应的个体进行交叉，以增强遗传多样性。因此，GA-MMC在每个应用的90%以上的测试中取得了成功，使最终种群的适应度提高了20%以上，并减少了早熟收敛。
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