Joint resource optimization for a distributed MIMO radar when tracking multiple targets in the presence of deception jamming
Joint resource optimization for a distributed MIMO radar when tracking multiple targets in the presence of deception jamming
复制标题
DOI：
10.1016/j.sigpro.2022.108641
复制
发表时间：
2022-06
期刊：
影响因子：
--
通讯作者：
Hao-wei Zhang;Weijian Liu;Qiliang Zhang;Jun-wei Xie
中科院分区：
文献类型：
--
作者：
Hao-wei Zhang;Weijian Liu;Qiliang Zhang;Jun-wei Xie
在电子对抗背景下，如何利用有限的资源在分布式多输入多输出(MIMO)雷达中获得更高的跟踪精度是至关重要的。提出了一种联合资源优化方案(JROS)，用于抗欺骗性干扰场景中发射站和接收站的选择和功率分配。建立了最小误目标拒绝率(RPFT)与门限差的服务质量(QOS)模型，并基于预测的欺骗参数后验Cramér-Rao下界(PCRLB)设计了最优鉴别器。二元选择变量导致了目标函数的非凸性。为了克服这一困难，提出了一种基于三步优化循环(TSOC)的算法。仿真结果表明，与现有的资源分配策略相比，该方案具有一定的优越性。结果还表明，距离干扰机越近、归一化欺骗参数越低的站点，往往被激活并分配到更多的功率资源。
How to utilize the limited resource to achieve better tracking accuracy in a distributed multiple-input multiple-output (MIMO) radar plays a critical role under the electronic countermeasure (ECM) background. In this paper, a joint resource optimization scheme (JROS) is presented for transmit and receive station selection and power allocation in anti-deception jamming scenario. A quality-of-service (QoS) model of minimizing the gap between rejection probability of false target (RPFT) and the threshold is established, and the optimal discriminator is designed on the basis of predicted posterior Cramér–Rao lower bound (PCRLB) on the deception parameters. The binary selection variables lead to the nonconvexity of objective function. To overcome this difficulty, a three-step optimization cycle (TSOC)-based algorithm is proposed. Simulation results confirm the superiority of the proposed scheme, compared with state-of-the-art resource allocation strategies. The results also show that the stations closer to the jammer with lower normalized deception parameters are often activated and allocated to more power resource.