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Snake-Hot-Eye-Assisted Multi-Process-Fusion Target Tracking Based on a Roll-Pitch Semi-strapdown Infrared Imaging Seeker

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Abstract

Aiming at intercepting large maneuvering targets precisely, the guidance law of advanced self-seeking missiles requires not only inertial line-of-sight (LOS) angular rate but also target maneuvering acceleration. Moreover, the semi-strapdown stabilization platform has lost the ability to measure the inertial LOS angular rate directly, which needs to be extracted by numerical calculation. The differential operation commonly used in traditional methods can magnify the measurement error of the sensor, resulting in insufficient calculation accuracy of the line-of-sight angular rate. By analyzing the mathematical relationship between the missile–target relative motion and the angle tracking system, a multi-process-fusion integrated filter model of relative motion and angle tracking is presented. To overcome the defect that the infrared seeker cannot directly measure the missile–target distance, following the snake-hot-eye visual mechanism, a visual bionic imaging guidance method of estimating the missile–target relative distance from the infrared images is proposed to improve the observability of the filter model. Finally, target-tracking simulations verify that the estimation accuracy of target acceleration is improved by four times.

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Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This work is sponsored by the National Natural Science Foundation of China under Grant No. 51979275, the Joint Open Research Fund Program of State Key Laboratory of Hydroscience and Engineering and Tsinghua—Ningxia Yinchuan Joint Institute of Internet of Waters on Digital Water Governance under Grant No. sklhse-2022-Iow08, the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources under Grant No. KF-2021-06-115, the National Key R&D Program of China under Grant No. 2018YFD0700603, and the 2115 Talent Development Program of China Agricultural University.

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Authors and Affiliations

  1. College of Engineering, China Agricultural University, Beijing, 100083, China

    Jian Chen & Zichao Zhang

  2. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen, 518000, China

    Zichao Zhang

  3. Systems Engineering Research Institute, China State Shipbuilding Corporation Limited, Beijing, 100094, China

    Ke Yi

  4. College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China

    Yu Han

  5. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Zhang Ren

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  1. Jian Chen
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  4. Yu Han
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  5. Zhang Ren
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Contributions

Conceptualization: JC, KY and ZR; methodology: JC, KY and ZR; software: ZZ and KY; validation: JC, ZZ and KY; formal analysis: ZZ, KY and YH; investigation: JC and YH; data curation: ZZ and KY; writing—original draft preparation: JC, ZZ and KY; writing—review and editing: YH; supervision: JC and YH; project administration: JC and YH; funding acquisition: JC and YH. All the authors have read and agreed to the published version of the manuscript.

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Correspondence to Yu Han.

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Chen, J., Zhang, Z., Yi, K. et al. Snake-Hot-Eye-Assisted Multi-Process-Fusion Target Tracking Based on a Roll-Pitch Semi-strapdown Infrared Imaging Seeker. J Bionic Eng 19, 1124–1139 (2022). https://doi.org/10.1007/s42235-022-00195-z

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