基于服务质量的相控阵雷达网目标分配方法

针对目前相控阵雷达网目标分配模型中约束条件构建不合理以及求解算法性能不高的问题，该文构建了基于服务质量(QoS)的雷达网目标分配模型，并提出基于强凹曲线逼近的模型求解算法。通过QoS模型中资源空间、环境空间的建立准确描述雷达的资源限制以及雷达与目标的可见性约束；通过库恩-塔克(KKT)条件推导出QoS模型最优解存在的充分条件，利用2维快速遍历方法逼近得到强凹函数曲线，最后对每个目标强凹曲线中的操作设定点进行逐步迭代得出优化分配方案。仿真结果表明:模型能够有效完成雷达网任务分配，且所提模型求解算法相比典型的智能搜索算法有更好的性能。

Target Assignment Method for Phased Array Radar Network Based on Quality of Service

The constraint conditions of target assignment model for phased array radar network are unreasonable and the performance of model solving algorithms are not good enough. To solve these problems, a target assignment model for radar network based on Quality of Service (QoS) is constructed in this paper, and a model solving algorithm based on strong concave function approximation is proposed. Through the establishment of resource space and environment space in QoS model, radar resource constraints as well as the visibility constraints between radars and targets are described accurately. Then, sufficient conditions for the optimal solution of QoS model are derived by Karush-Kuhn-Tucker(KKT) condition, and a two-dimensional fast traversal method is used to approximate the strong concave function curve. Finally, the optimal assignment scheme is obtained by the stepwise iteration of operation setting points on the strong concave curve of each target. The simulation results show that the proposed model can effectively accomplish the target assignment of radar network, and model solving algorithm has better performance than the typical intelligent search algorithms.