Motion Characteristics-Based Target Maneuver Detection and Active Deception False Target Discrimination in Midcourse Defense
Dingli Lou, Defeng Chen, Huawei Cao, Shuo Zhang, Tuo Fu
Beijing Institute of Technology
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摘要与影响
Midcourse defense is essential for countering ballistic missile threats, and radar is a critical component of midcourse defense systems. However, the advanced maneuvering and deceptive electronic countermeasure (DECM) technologies employed during the midcourse flight of a ballistic missile significantly impair radar detection and tracking capabilities. In this work, a midcourse target maneuver detection and deception false target discrimination method is proposed that uses motion characteristics. By augmenting the state vector with deception and maneuvering parameters, motion and measurement models that are compatible with both false targets and maneuvering targets are developed. Based on these models, the deception parameters, maneuvering parameters, and target state are jointly estimated using radar measurements. The problem of target maneuver detection and false target discrimination is formulated as a target classification problem for which the generalized likelihood ratio test (GLRT) method is employed. The derived test statistics imply that different target classes can be distinguished on the basis of their unique feature spaces, which are specified by their projection matrices. A two-step GLRT scheme is then proposed for target classification, along with a strategy for controlling the false alarm probability. The numerical simulation results verify the effectiveness of the strategy and highlight the powerful detection and discrimination capabilities of the proposed scheme.
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学术脉络
学科主题
计算机 / AITarget Tracking and Data Fusion in Sensor Networks
Radar Systems and Signal Processing · Military Defense Systems Analysis
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