面向目标跟踪的机载组网雷达辐射参数与航迹规划联合优化算法

该文针对机载组网雷达，在单目标跟踪场景下，研究了雷达辐射参数与航迹规划联合优化问题。首先，推导了包含各雷达辐射功率、驻留时间、发射信号高斯脉冲长度和信号带宽等射频辐射参数以及各载机速度、朝向角等平台运动参数的贝叶斯克拉默-拉奥下界(BCRLB)表达式，以此作为表征目标跟踪精度的衡量指标；推导了含有各雷达辐射功率、驻留时间等射频辐射参数以及各载机速度、朝向角等平台运动参数的机载组网雷达被截获概率，以此作为表征机载组网雷达射频隐身性能的衡量指标。在此基础上，建立了面向目标跟踪的机载组网雷达辐射参数与航迹规划联合优化模型，以最小化机载组网雷达的目标估计误差BCRLB为优化目标，以满足给定的系统射频资源、载机机动能力和预先设定的被截获概率阈值为约束条件，对各载机飞行速度、朝向角以及各机载雷达辐射功率、驻留时间、发射信号高斯脉冲长度和信号带宽进行联合优化设计，以提升机载组网雷达的目标跟踪精度。最后，针对上述优化问题，结合粒子群算法，采用5步分解迭代算法进行求解。仿真结果表明，与现有算法相比，所提算法能够在满足一定射频隐身性能要求的条件下，有效提升机载组网雷达的目标跟踪精度。 

Joint Transmit Resources and Trajectory Planning for Target Tracking in Airborne Radar Networks

This paper investigates the joint optimization problem of transmit resources and trajectory planning for target tracking in airborne radar networks. First, the analytical expression for the Bayesian Cramér-Rao Lower Bound (BCRLB) with the variables of the radar transmit power, dwell time, transmit signal Gaussian pulse length and signal bandwidth, and speed and heading angle of airborne nodes is derived and adopted as the metric function to evaluate the target tracking accuracy. In addition, the analytical expression of intercept probability with the variables of the radar transmit power, dwell time, and speed and heading angle of airborne nodes is also derived and utilized as the metric function to gauge the radio frequency stealth performance of the overall system. On this basis, a joint optimization model of transmit resources and trajectory planning for target tracking in airborne radar networks is established to jointly optimize the radar transmit power, dwell time, transmit signal Gaussian pulse length and signal bandwidth, and speed and heading angle of airborne nodes. This is done to minimize the target estimation error BCRLB under the constraints of given system resources, aircraft maneuvering and intercept probability threshold, thereby improving the target tracking accuracy of airborne radar network. Subsequently, a five-step decomposition iterative algorithm incorporating the particle swarm algorithm is used to solve the underlying optimization problem. The simulation results demonstrate that the target tracking accuracy of the proposed algorithm outperforms other existing approaches.