Multi-sensor management based on joint risk prediction under aerial electronic jamming

Traditional multi-sensor management methods based on risk assessment face difficulties such as difficulty in risk evaluation and poor tracking accuracy under electromagnetic interference scenarios, making it challenging to effectively ensure the overall safety and accuracy of target tracking systems. To address this problem, 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. First, by taking into account the radiation risk of the sensor side, the detection loss risk, and the target threat risk from the enemy, and by introducing adaptive weights based on the Signal to Interference plus Noise Ratio (SINR), a variable-weighted bidirectional joint risk model is constructed. Then, with the objective of minimizing sensor power, a multi-step prediction multi-sensor allocation problem based on bidirectional joint risk is formulated within a time-series prediction framework. Finally, the multi-sensor allocation problem with non-convex constraints is relaxed into a convex optimization problem for efficient 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.