基于帕累托最优的雷达-通信共享孔径研究

石长安; 刘一民; 王希勤; 于鹏

doi:10.11999/JEIT151377

基于帕累托最优的雷达-通信共享孔径研究

doi: 10.11999/JEIT151377

2.
(清华大学电子工程系北京 100084) ②(中国洛阳电子装备试验中心洛阳 471003)

基金项目:

国家自然科学基金(61571260)

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- 文章访问数: 1755
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- 被引次数: 0
出版历程
- 收稿日期: 2015-12-08
- 修回日期: 2016-05-13
- 刊出日期: 2016-09-19

Optimal Allocation of Shared Aperture in Radar-communication Integrated System Based on Pareto Optimality

2.
(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China)

Funds:

The National Natural Science Foundation of China (61571260)

摘要

摘要: 针对雷达-通信综合射频系统，该文提出一种基于环境信息的共享孔径动态分配方法。首先基于帕累托最优理论将共享孔径分配建模为一个多目标优化问题，并建立了雷达阵列方向图的峰值旁瓣电平和多输入多输出(MIMO)通信系统的信道容量两个优化目标函数。然后提出一种基于整数编码的改进粒子群算法，通过迭代求解以帕累托前沿的形式给出一组最优解，供决策者根据任务需求从中选出一个最满意的解。最后，仿真结果验证了该方法的有效性。
- 共享孔径 /
- 综合射频系统 /
- 多目标优化 /
- 粒子群算法 /
- 帕累托最优
Abstract: In this work, considering a radar-communication integrated radio frequency system, a dynamic allocation method of shared aperture using relevant environmental information is proposed. Firstly, the shared aperture allocation task is formulated as a Multi-Objective Optimization (MOO) problem based on Pareto optimality, which uses the peak side-lobe level of radar array pattern and the channel capacity of Multiple Input Multiple Output (MIMO) communication system as its objective function. Then, an improved particle swarm optimization algorithm based on integer encoding is proposed to solve the MOO problem. The iterative algorithm can find out a set of optimal solutions in the form of Pareto front, one of which can be chosen by decision makers as the most satisfactory solution according to mission requirements. Finally, the simulation results verify the effectiveness of the proposed method.
- Shared aperture /
- Integrated radio frequency system /
- Multi-objective optimization /
- Particle swarm optimization /
- Pareto optimality

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