频谱共存下机载组网雷达辐射资源与航迹规划联合优化算法

Joint Radiation Resource Allocation and Trajectory Planning in Airborne Radar Network under Spectral Coexistence

为了提升频谱共存环境下机载组网雷达多目标跟踪性能,提出了一种雷达辐射资源与航迹规划联合优化算法。首先,推导了包含雷达辐射资源以及载机飞行参数的贝叶斯克拉美-罗下界表达式,以此作为多目标跟踪精度的衡量指标;在此基础上,以最小化机载组网雷达多目标跟踪误差为优化目标,以雷达辐射资源总量、载机机动性能、通信基站可容忍干扰能量和跟踪各目标节点数为约束条件,建立频谱共存下机载组网雷达辐射资源与航迹规划联合优化模型;然后,将上述优化模型分解为多个子问题,并结合循环最小化算法、半正定规划算法和粒子群算法进行分步求解。最终仿真结果表明,所提算法能够在保证通信基站正常工作的条件下,充分利用各平台运动优势,与现有算法相比,能够有效提升机载组网雷达的多目标跟踪性能。

In order to improve the multi-target tracking performance of airborne radar network in spectral coexistence environment,a joint radiation resource and trajectory planning algorithm for multi-target tracking under spectral coexistence is proposed.Firstly,the Bayesian Cramér-Rao Lower Bound expression including the radar radiation resource and carrier flight parameter is derived,which is used as a measure of the multi-target tracking accuracy of airborne radar network.On this basis,the joint optimization model of radio frequency radiation resource control and trajectory planning of airborne radar network for multi-target tracking under spectral coexistence is established with the objective of minimizing the multi-target tracking error of airborne radar network as the optimization goal,and the constraint conditions of meeting the total radar radiation resources,carrier mobility,the allowable interference energy threshold of the communication base station and tracking the number of target nodes.Then,the above optimization model is decomposed into multiple sub problems,and combines with cyclic minimization algorithm,the Semi-definite Programming algorithm,and particle swarm optimization algorithm for step-by-step solution.Finally,the simulation results show that,compared with the existing algorithm,the proposed algorithm can effectively improve the multi-target tracking performance of airborne radar network by making full use of the motion advantages of each platform under the condition of ensuring the normal operation of the communication base station.