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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
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Target rotation parameter estimation for ISAR imaging via frame processing

doi: 10.3788/IRLA201645.0302001
  • 1.

    School of Electrical and Computer Engineering,RMIT University,Australia;

  • 2.

    School of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China

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

  • Received Date: 2015-07-16
  • Rev Recd Date: 2015-08-18
  • Publish Date: 2016-03-25
  • 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.
  • [1] Yeh C M, Xu J, Peng Y N, et al. Rotational motion estimation for ISAR via triangle pose difference on two range-Doppler images[J]. IET Radar, Sonar and Navigation, 2010, 4(4):528-536.
    [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.
    [4] She Z, Liu Y. Autofocus for ISAR imaging using higher order statistics[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(2):299-303.
    [5] Peng S B, Xu J, Peng Y N, et al. Inverse synthetic aperture radar rotation velocity estimation based on phase slope difference of two prominent scatterers[J]. Radar, Sonar Navigation, IET, 2011, 5(9):1002-1009.
    [6] Mao Yeh C, Xu J, Peng Y N, et al. Cross-range scaling for isar via optical flow analysis[J]. Aerospace and Electronic Systems Magazine, IEEE, 2012, 27(2):14-22.
    [7] Huang Y, Wang X, Li X, et al. Inverse synthetic aperture radar imaging using frame theory[J]. IEEE Trans Signal Processing, 2012, 60(10):5191-5200.
    [8] Huang Y, Wang X, Li X, et al. Target rotation rate estimation via isar frame processing[J]. Electronics Letters, 2013, 49(6):424-425.
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    [12] Huang Y, Wang X, Li X, et al. Tomographic radar imaging using frame theory[C]//15th International Conference on Information Fusion, 2012(S):1421-1426, 9-12.
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    [17] Raj R, Farshchian M. Isar imaging in sea clutter via compressive sensing[C]//Waveform Diversity and Design Conference(WDD), 2010 International, 2010:200-205.
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Target rotation parameter estimation for ISAR imaging via frame processing

doi: 10.3788/IRLA201645.0302001
  • 1. School of Electrical and Computer Engineering,RMIT University,Australia;
  • 2. School of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China
  • Author Bio:

  • Received Date: 2015-07-16
  • Rev Recd Date: 2015-08-18
  • Publish Date: 2016-03-25
Fund Project:

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

Abstract: 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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