基于无源传感器协同的机载雷达自适应辐射控制算法
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Adaptive Radiation Control Algorithm with Passive Sensor Cooperation in Airborne Radar System
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    摘要:

    随着现代战场中电子对抗的日益激烈,雷达的生存环境受到了严重威胁。射频隐身技术是一种提高雷达及其搭载平台战场生存能力的重要途径。文中采用一种基于交互式多模型(Interacting multiple model, IMM)和扩展卡尔曼滤波(Extended Kalman filter, EKF)的序贯滤波方法。该算法优先使用无源传感器进行目标跟踪,将滤波过程中的状态估计预测协方差与预先设定的协方差门限进行比较,当目标跟踪精度不满足要求时,开启雷达工作。同时根据目标运动状态自适应地调整雷达工作时的辐射能量,从而进一步减小目标跟踪过程中机载雷达的辐射总能量。仿真结果表明,本文算法可以有效地配置机载雷达工作参数,提升系统的射频隐身性能。

    Abstract:

    With the increasingly fierce struggle of electronic countermeasures in the modern battlefield, the environment of radar falls under serious threat. Radio frequency(RF) stealth technology is an important approach to improve the viabilities of radar and its platform in the battlefield. In this paper, the problem of RF stealth in airborne radar system is investigated, and a novel optimal resource management algorithm with passive sensor cooperation in airborne radar system is proposed. The sequential filtering algorithm based on interacting multiple model (IMM) and extended Kalman filter (EKF) is employed for target tracking, and the passive sensor is utilized in preference to radar. In the proposed algorithm, the comparison of the predicted state estimation covariance and the predefined threshold of covariance is used to control radar under an intermittent-working state. Furthermore, the radiation energy is adaptively adjusted to improve the RF stealth performance according to the target motion. Numerical simulation results demonstrate that the proposed algorithm can effectively configure radar working parameters and improve RF stealth performance.

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戴春亮时晨光周建江汪飞.基于无源传感器协同的机载雷达自适应辐射控制算法[J].数据采集与处理,2016,31(4):746-753

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  • 在线发布日期: 2018-04-09