Future Point Estimation Method for Unpowered Gliding Targets

In modern warfare, unpowered glide munitions, represented by JDAM, are widely used. Accurately predicting the future trajectory of such targets is crucial for intercepting them. This paper proposes a future point prediction method for unpowered gliding targets based on attitude computation. By estimating the current state of the target, we derive the target’s attitude coordinate system. Subsequently, the paper analyzes the forces acting on the target and updates the state transition matrix, ultimately calculating the future position of the target. Experimental results show that, compared to traditional methods, this approach improves the accuracy of future point predictions by 9% to 45%.

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Publication Details

Journal
Journal of Electronic Research and Application
Published
2024-11-29
DOI
https://doi.org/10.26689/jera.v8i6.8992
Citations
1
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
1.30
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article

Future Point Estimation Method for Unpowered Gliding Targets

Shoufeng Wang
1 citations
Journal of Electronic Research and Application
Inertial Sensor and Navigation
1.30
article

Future Point Estimation Method for Unpowered Gliding Targets

Shoufeng Wang
article en
1 citations

Abstract

In modern warfare, unpowered glide munitions, represented by JDAM, are widely used. Accurately predicting the future trajectory of such targets is crucial for intercepting them. This paper proposes a future point prediction method for unpowered gliding targets based on attitude computation. By estimating the current state of the target, we derive the target’s attitude coordinate system. Subsequently, the paper analyzes the forces acting on the target and updates the state transition matrix, ultimately calculating the future position of the target. Experimental results show that, compared to traditional methods, this approach improves the accuracy of future point predictions by 9% to 45%.

Journal of Electronic Research and ApplicationVol. 8(6)
NARI Group (China) (CN)
Openalex Percentile: Top 12%
Inertial Sensor and Navigation
1.30
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