深空大规模天线阵布局优化方法研究

由大量廉价的小型反射面天线组成阵列对航天器进行跟踪通信是未来深空测控网发展 的一条新思路。提出一种改进的遗传算法对大规模小天线阵列地理布局进行优化，提高天线 阵列的测控性能。首先分析了布局优化的约束条件,然后以最小化旁瓣电平为目标，建立了 优化模型。分析了Kogan梯度算法和常规遗传算法的局限性，最后给出了改进遗传算法的优 化流程。仿真结果表明，改进的遗传算法不但具有高的优化效率，还可应用于阵列布局的多 目标优化。

Research of Optimizing Algorithm for Deep Space Large Arrays Geometric Configuration

Spacecraft tracking and telemetry reception using large arrays composed of numerous small inexpensive reflector antennas is becoming a new choice in future deep-space network development. An improved genetic algorithm for large array geometric configurations optimization is proposed to improve array performance. Firstly, constraints of array configuration are analyzed, and then an optimization model minimizing sidelobe of array for a given tracking direction is build. After discussing the limitation of Kogan gradient algorithm and conventional genetic algorithms, improved genetic algorithm programming framework is given. The simulation results show that improved genetic algorithm not only got higher optimization efficiency, but also suitable for multi-objective array configurations optimization.