分布式MIMO天波超视距雷达阵地配置

Sites Placement of Distributed MIMO Sky-wave Over the Horizon Radar

  • 摘要: 该文研究了基于目标位置估计克拉美罗界(Cramer-Rao Bound, CRB)的分布式多输入多输出(Multi-Input Multi-Output, MIMO)天波超视距雷达收发天线阵地配置问题。根据收发天线阵地、电离层信道和目标的几何位置,给出了分布式MIMO天波超视距雷达目标位置估计的CRB,以该CRB为目标函数,以收发阵地的位置、个数等为优化变量,建立了收发阵地配置优化方程。该优化方程为非线性混合整数规划问题,求解困难。为此,采用数字射线追踪方法将收发阵地的位置转化为关于电离层反射面的镜像位置,将其转化成一个非线性01规划问题。对二进制编码的量子行为粒子群优化(Binary Quantum-Behaved Particle Swarm Optimization, BQPSO)算法加以修改用于求解该问题。最后,对不同阵地个数、目标和信道条件下的阵地配置进行了仿真分析,给出了相应条件下的阵地配置策略,并对修正BQPSO算法的性能进行了简要分析。

     

    Abstract:  In this paper we study the site placement problem of distributed MIMO sky-wave over the horizon radar based on Cramer-Rao bound for target localization. Cramer-Rao bound (CRB) for target localization of distributed MIMO sky-wave over the horizon radar is derived according to the geometry of transmitter sites, ionospheric channel, target and receiver, sites. Let the CRB be the objective function, the sites, number of transmitters and receivers be constraints, optimization equation is established, which is a nonlinear mixed integer programming problem and complicated. Then, using numeric ray tracing, the sites of transmitters and receivers are transformed to the mirror symmetry counterpart respectively, the problem is transformed to a nonlinear 0-1 integer programming. The Binary quantum-behaved particle swarm optimization (BQSPO) algorithm is modified to solve this problem. Lastly, sites placement for different number of sites, different target and channel conditions is simulated, an optimized sites placement is given accordingly. The performance of the modified BQSPO algorithm is also analyzed concisely.

     

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