An Advanced Future Point Prediction Approach for Gliding Targets Leveraging Pose Estimation

In modern warfare, glide-guided bomb targets have become one of the critical threats to terminal defense of key areas. Improving the future point prediction accuracy of fire control systems for these targets is a key challenge in modern air defense fire control calculations. This paper proposes an improved future point prediction method for glide-guided bomb targets based on attitude determination. By introducing the Interacting Multiple Model into the current position estimation phase of the method, the matching degree between the motion model and the maneuvering target trajectory is enhanced. Experimental results demonstrate that the proposed method achieves a 25.5%-57.4% improvement in future point prediction accuracy compared to traditional approaches. This study provides an effective solution approach for trajectory forecasting of gliding guided bomb targets.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/fasta65681.2025.11138500
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

An Advanced Future Point Prediction Approach for Gliding Targets Leveraging Pose Estimation

Baobao Wang, Zhao Yue, Panlong Wu, Shoufeng Wang
Target Tracking and Data Fusion in Sensor Networks
article

An Advanced Future Point Prediction Approach for Gliding Targets Leveraging Pose Estimation

Baobao Wang, Zhao Yue, Panlong Wu, Shoufeng Wang
article en

Abstract

In modern warfare, glide-guided bomb targets have become one of the critical threats to terminal defense of key areas. Improving the future point prediction accuracy of fire control systems for these targets is a key challenge in modern air defense fire control calculations. This paper proposes an improved future point prediction method for glide-guided bomb targets based on attitude determination. By introducing the Interacting Multiple Model into the current position estimation phase of the method, the matching degree between the motion model and the maneuvering target trajectory is enhanced. Experimental results demonstrate that the proposed method achieves a 25.5%-57.4% improvement in future point prediction accuracy compared to traditional approaches. This study provides an effective solution approach for trajectory forecasting of gliding guided bomb targets.

Nanjing University of Science and Technology (CN), NARI Group (China) (CN)
Openalex Percentile: Top 87%
Target Tracking and Data Fusion in Sensor Networks
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