针对跨域无人飞行器探测跟踪误差较大导致的中末制导交接班难题，本文提出一种基于目标轨迹预测误差管道建模的多拦截器异构视场协同覆盖优化方法。首先，通过分析目标轨迹预测误差来源，基于误差传播理论采用参数化建模方式构建目标轨迹预测误差管道模型，并计算中末制导交接班时刻目标高概率区域；其次，将中末制导交接班目标捕获问题转化为多个异构视场对目标高概率区域的几何覆盖优化问题，建立了完全覆盖约束条件下的拦截器组合成本最低目标函数；最后，采用遗传算法求解最优拦截器组合配置及最优覆盖点。仿真实验结果表明，本文提出参数化建模方法相比传统蒙特卡洛统计方法在目标高概率区域估算方面具有显著的计算效率优势，所提覆盖优化方法能够有效处理多拦截器异构视场配置及最佳覆盖点的联合优化问题，为针对高空跨域无人飞行器的辅助防御决策和提高中末制导交接班成功率提供了理论支撑。
The substantial detection and tracking errors of cross-domain unmanned aerial vehicles(CDUAVs) pose significant challenges to the handover between mid-terminal guidance. This paper proposes an optimisation method for coopera-tive coverage across multi-interceptors with heterogeneous field-of-view based on target trajectory prediction error pipeline modelling. First, the target trajectory prediction error pipeline model is constructed through parametric model-ling based on error propagation theory, following an analysis of error sources. This model calculates the high-probability target regions at the handover between mid-terminal guidance. Second, the target acquisition problem dur-ing handover is transformed into a geometric coverage optimisation problem for multi-interceptor with heterogeneous field-of-view over these high-probability regions. A minimised objective function for interceptor combinations is estab-lished under full coverage constraints. Finally, a genetic algorithm is employed to determine the optimal interceptor combination configuration and optimal coverage points. Simulation results demonstrate that the proposed parametric modelling approach exhibits significant computational efficiency advantages over traditional Monte Carlo statistical methods in estimating high-probability target regions. The coverage optimisation method effectively addresses the joint optimisation of multi-interceptor heterogeneous field-of-view configurations and optimal coverage points, provid-ing theoretical support for assisting defence decision-making against CDUAVs and enhancing the success rate of the handover between mid-terminal guidance.
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