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Research on Target Recognition Technology based on HRRP

Published: 25 February 2022 Publication History
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    Abstract: Accurate identification of various types of targets in the battlefield is an important prerequisite for completing target locking and delivering accurate strikes. All-weather uninterrupted work is the main feature of radar system, and the identification of military targets by radar echo has become one of the most effective and commonly used means at present. High Resolution Range Profile (HRRP) of radar targets can effectively reflect the geometric feature information such as target structure and shape, which provides important feature support for detecting objects and realizing target identification, and HRRP has the advantages of easy acquisition, simple processing and strong real-time. The article firstly uses the HRRP features of the target obtained through the radar target echo and adopts the Dechirp processing imaging method; secondly, it adopts the Support Vector Machine (SVM) method to realize the target recognition based on the target HRRP, and on this basis, it proposes the voting judgment matrix strategy and uses the Boosting multi-classifier Based on this, a voting judgment matrix strategy and a Boosting multi-classifier fusion processing strategy are proposed to enhance the target recognition performance and thus improve the accuracy of the target recognition results; finally, the research method is experimentally verified to achieve the effective recognition of three types of vehicle targets.

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    cover image ACM Other conferences
    ACAI '21: Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence
    December 2021
    699 pages
    ISBN:9781450385053
    DOI:10.1145/3508546
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 February 2022

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    Author Tags

    1. High Resolution One-Dimensional Range Image
    2. Pulse Compression
    3. Support Vector Machine
    4. Target Recognition

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