Motion Characteristics-Based Target Maneuver Detection and Active Deception False Target Discrimination in Midcourse Defense

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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Publication Details

Journal
IEEE Sensors Journal
Published
2025-05-05
DOI
https://doi.org/10.1109/jsen.2025.3565531
Citations
1
Primary Topic
Guidance and Control Systems
Type
article
Field-Weighted Citation Impact
4.99
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article

Motion Characteristics-Based Target Maneuver Detection and Active Deception False Target Discrimination in Midcourse Defense

Shuo Zhang, Defeng Chen, Huawei Cao, Tuo Fu et al.
1 citations
IEEE Sensors Journal
Guidance and Control Systems
4.99
article

Motion Characteristics-Based Target Maneuver Detection and Active Deception False Target Discrimination in Midcourse Defense

Shuo Zhang, Defeng Chen, Huawei Cao, Tuo Fu, Dingli Lou
article en
1 citations

Abstract

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.

IEEE Sensors JournalVol. 25(12)
Beijing Institute of Technology (CN)
Gender equality
Openalex Percentile: Top 6%
Guidance and Control Systems
4.99
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Motion Characteristics-Based Target Maneuver Detection and Active Deception False Target Discrimination in Midcourse Defense — Shuo Zhang, Defeng Chen, et al. · IEEE Sensors Journal (2025) | TGRS Research Map | TGRS