UAV tracking moving target scene using on-board ISAR sensor

Liren Zhang, Ahmed Karam

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Compressive sensing (CS) based Inverse Synthetic Aperture Radar (ISAR) imaging exploits the sparsity of the target scene to achieve high resolution and effective denoising with limited measurements. This paper extends the CS based ISAR imaging to further include the continuity structure of the target scene within a Bayesian framework. A correlated prior is imposed to statistically encourage the continuity structures in both the cross-range and range domains of the target region and the Gibbs sampling strategy is used for Bayesian inference. Because the resulted method requires to recover the whole target scene at a time with heavy computational complexity, an approximate strategy is proposed to alleviate the computational burden. Experimental results demonstrate that the proposed algorithm can achieve substantial improvements in terms of preserving the weak scatterers and removing noise over other reported CS based ISAR imaging algorithms.

    Original languageEnglish
    Title of host publication2014 10th International Conference on Innovations in Information Technology, IIT 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages88-92
    Number of pages5
    ISBN (Electronic)9781479972128
    DOIs
    Publication statusPublished - Dec 16 2014
    Event2014 10th International Conference on Innovations in Information Technology, IIT 2014 - Abu Dhabi, Al-Ain, United Arab Emirates
    Duration: Nov 9 2014Nov 11 2014

    Publication series

    Name2014 10th International Conference on Innovations in Information Technology, IIT 2014

    Other

    Other2014 10th International Conference on Innovations in Information Technology, IIT 2014
    Country/TerritoryUnited Arab Emirates
    CityAbu Dhabi, Al-Ain
    Period11/9/1411/11/14

    Keywords

    • ISAR imaging
    • continuity structures
    • model-based compressive sensing

    ASJC Scopus subject areas

    • Computer Science Applications
    • Information Systems
    • Software

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