Autonomous Trajectory Planning and Control of Anti-Radiation Loitering Munitions under Uncertain Conditions

As an autonomous system, an anti-radiation loitering munition (LM) experiences uncertainty in both a priori and sensed information during loitering because it is difficult to accurately know target radar information in advance, and the sensing performance of the seeker is affected by disturbance and errors. If, as it does in the state of the art, uncertainties are ignored and the LM travels its planned route, its battle effectiveness will be severely restricted. To tackle this problem, this paper studies the method of autonomous planning and control of loitering routes using limited a priori information of target radar and real-time sensing results. We establish a motion and sensing model based on the characteristics of anti-radiation LMs and use particle filtering to iteratively infer the target radar information. Based on model predictive control, we select a loitering path to minimize the uncertainty of the target information, so as to achieve trajectory planning control that is conducive to the acquisition of target radar information. Simulation results show that the proposed method can effectively complete the autonomous trajectory planning and control of anti-radiation LMs under uncertain conditions.