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Target rotation parameter estimation for ISAR imaging via frame processing

Xuezhi Wang Yajing Huang Weiping Yang Bill Moran

Xuezhi Wang, Yajing Huang, Weiping Yang, Bill Moran. Target rotation parameter estimation for ISAR imaging via frame processing[J]. 红外与激光工程, 2016, 45(3): 302001-0302001(11). doi: 10.3788/IRLA201645.0302001
引用本文: Xuezhi Wang, Yajing Huang, Weiping Yang, Bill Moran. Target rotation parameter estimation for ISAR imaging via frame processing[J]. 红外与激光工程, 2016, 45(3): 302001-0302001(11). doi: 10.3788/IRLA201645.0302001
Xuezhi Wang, Yajing Huang, Weiping Yang, Bill Moran. Target rotation parameter estimation for ISAR imaging via frame processing[J]. Infrared and Laser Engineering, 2016, 45(3): 302001-0302001(11). doi: 10.3788/IRLA201645.0302001
Citation: Xuezhi Wang, Yajing Huang, Weiping Yang, Bill Moran. Target rotation parameter estimation for ISAR imaging via frame processing[J]. Infrared and Laser Engineering, 2016, 45(3): 302001-0302001(11). doi: 10.3788/IRLA201645.0302001

Target rotation parameter estimation for ISAR imaging via frame processing

doi: 10.3788/IRLA201645.0302001
基金项目: 

Partially supported by Australian Air Force Office of Scientific Research (AFOSR) Grant(FA2386-13-1-4080)

详细信息
    作者简介:

    Xuezhi Wang, Senior research fellow and PhD supervisor, his research interests are in radar signal processing, information geometry, Bayesian estimation and target tracking. Email:xuezhi.wang@rmit.edu.au

  • 中图分类号: TN95

Target rotation parameter estimation for ISAR imaging via frame processing

Funds: 

Partially supported by Australian Air Force Office of Scientific Research (AFOSR) Grant(FA2386-13-1-4080)

More Information
    Author Bio:

    Xuezhi Wang, Senior research fellow and PhD supervisor, his research interests are in radar signal processing, information geometry, Bayesian estimation and target tracking. Email:xuezhi.wang@rmit.edu.au

  • 摘要: Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar (ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error. Effectiveness of the proposed method is also confirmed from real ISAR data experiments.
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    [2] Martorella M. Novel approach for ISAR image cross-range scaling[J]. IEEE Trans Aerospace and Electronic Systems, 2008, 44(1):281-294.
    [3] Yeh C, Yang J, Peng Y, et al. Rotation estimation for ISAR targets with a space time analysis technique[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(5):899-903.
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出版历程
  • 收稿日期:  2015-07-16
  • 修回日期:  2015-08-18
  • 刊出日期:  2016-03-25

Target rotation parameter estimation for ISAR imaging via frame processing

doi: 10.3788/IRLA201645.0302001
    作者简介:

    Xuezhi Wang, Senior research fellow and PhD supervisor, his research interests are in radar signal processing, information geometry, Bayesian estimation and target tracking. Email:xuezhi.wang@rmit.edu.au

基金项目:

Partially supported by Australian Air Force Office of Scientific Research (AFOSR) Grant(FA2386-13-1-4080)

  • 中图分类号: TN95

摘要: Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar (ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error. Effectiveness of the proposed method is also confirmed from real ISAR data experiments.

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