传统基于风险评估的多传感器管理方法在电子干扰场景下存在风险评估困难、跟踪精度差等问题，不能有效保证目标跟踪系统的整体安全性和准确性。因此本文综合考虑电子干扰场景下的传感器辐射风险、探测失根风险和目标威胁风险，提出电子干扰下基于双向联合风险多步预测的多传感器管理方法。首先，本文考虑我方的传感器辐射风险、探测失跟风险以及对方的目标威胁风险，并引入基于信号与干扰加噪声比的自适应权重，构建变加权双向联合风险模型；其次，以最小化传感器功率为目标，在时序预测框架下，构建双向联合风险多步预测的多传感器分配问题；最后，将带有非凸约束的多传感器分配问题松弛为凸优化问题进行求解，进而提高解算效率。仿真结果表明，所提方法能有效调度和分配有限的多传感器资源，在电子干扰场景下保证跟踪系统安全的同时，能有效提高目标跟踪的精度。

Traditional multi-sensor management methods based on risk assessment face issues such as difficulty in risk evaluation and poor tracking accuracy under electromagnetic interference scenarios, which fail to effectively ensure the overall safety and accuracy of target tracking systems. Therefore, this paper comprehensively considers the sensor radiation risk, detection loss risk, and target threat risk in electronic interference scenarios and proposes a multi-sensor management method based on bidirectional joint risk multi-step prediction under electronic interference (MM-BRP-EI). First, this paper considers the radiation risk of the sensor side, the detection loss risk, and the target threat risk from the enemy, introducing adaptive weights based on the Signal to Interference Plus Noise Ratio (SINR) to construct a variable-weighted bidirectional joint risk model. Then, with the objective of minimizing sensor power, a multi-step prediction multi-sensor allocation problem based on bidirectional joint risk is constructed within a time-series prediction framework. Finally, the multi-sensor allocation problem with non-convex constraints is relaxed into a convex optimization problem for solving, thereby improving computational efficiency. Simulation results show that the proposed method can effectively schedule and allocate limited multi-sensor resources, ensuring the safety of the tracking system while effectively improving the accuracy of target tracking under electronic interference scenarios.