Abstract
To solve the problem of ISAR imaging cross-range scaling of complex motion of target, this paper analyzes kinetic mechanism of complex motion of the target. The motion forms will produce different Doppler frequency if the target is different. For 2D rotation target, the proportion of azimuth angle and pitch angle keeps constant, and the synthetic rotation vector is polynomial function of time. This paper takes “Matching Fourier Transform Algorithm” as the processing method to estimate the motion parameters of target. Additionally, the simulated result indicates the effectiveness of algorithm. For 3D rotation target, the paper adopts “Target Observation Matrix Decomposition method” to obtain European calibrated viewing angle vector matrix, and further get azimuth angle as well as pitch angle sequences of the target. Moreover, LS method is used for parameter estimation and the result is effective.














Similar content being viewed by others
References
Cumming IG, Wong FH (2007) Digital processing of synthetic aperture radar data: algorithm and implementation. Artech House, Norwood
Sullivan RJ (2009) Radar foundations for imaging and advanced concepts. SciTech Publishing, New York
Soumekh M (1999) Synthetic aperture radar signal processing with MATLAB algorithms. Wiley, London
Lazarov AD, Minchev CN (2004) Complementary code ISAR technique for stealth target detection and identification. Digit Avion Syst Conf 1:1–11
Stuff M, Sanchez P, Biancala M (2003) Extraction of three-dimensional motion and geometric invariants. Multidimens Syst Signal Proces 14:161–181
Ferrara M, Arnold G, Stuff M (2009) Shape and motion reconstruction from 3D-to-1D orthographically projected data via object-image relations. IEEE 7Fransactions Pattern Anal Mach Intell 31(10):1906–1912
Whitaker R, Gregor J (2002) A maximum-likelihood surface estimator for dense range data. IEEE Trans Pattern Anal Mach Intell 24(10):1372–1387
Arnold G, Stiller PF, Sturtz K (2006) Object-image metrics for generalized weak perspective projection. In: Krim H, Yezzi A (eds) Statistics and analysis of shapes. Modeling and simulation in science, engineering and technology. Birkhäuser, Boston, pp 253–279. https://doi.org/10.1007/0-8176-4481-4_10
Zhang Q, Yeo TS, Tan HS et al (2008) Imaging of a moving target with rotating pans based on the Hough transform. IEEE Trans Geosci Remote Sens 46(1):291–299
Savy L, Gaie C (2007) Model-based classification of aircraft ranges profiles using data association algorithms. In: IEEE Radar Conference, 2007, pp 822–827
Zhang L (2012) High resolution SAR/ISAR imaging and error compensation technology. Xidian University, Xidian, pp 49–56
Wang L, Zhu D, Zhu Z (2008) Image-based scaling for ship top-view ISAR images. J Electron 25(1):76–83
Huang Y, Wang X, Li X et al (2013) Target rotation rate estimation via ISAR frame processing. Electron Lett 49(6):424–425
Wang Y, Jiang Y (2008) A novel algorithm for estimating the rotation angle in ISAR imaging. IEEE Geosci Remote Sens Lett 5(4):608–609
Kang M-S, Kim K-T (2015) ISAR cross-range scaling using principal component analysis and exhaustive search algorithm . In: 2015 IEEE Radar Conference, Arlington, VA, pp 0386–0389
Zhang R, Shen J, Wei F et al (2017) Medical image classification based on multi-scale non-negative sparse coding. Artif Intell Med. https://doi.org/10.1016/j.artmed.2017.05.006
Samuel OW, Arun GMA, Sangaiahc K et al (2017) Multi-technique object tracking approach-A reinforcement paradigm. Comput Electr Eng. https://doi.org/10.1016/j.artmed.2017.05.006
Li A, Chen D, Lin K et al (2016) Nonlocal joint regularizations framework with application to image denoising. Circuits Syst Signal Process 35(8):2932–3942
Li A, Chen D, Sun G et al (2016) Sparse representation-based image restoration via nonlocal supervised coding. Opt Rev 23(5):776–783
Zhang H (2010) ISAR imaging transverse calibration problem. Harbin Institute of Technology, Harbin
Wang X (2012) Study on azimuth calibration method of ISAR image. Nanjing University of Aeronautics and Astronautics, Nanjing
Yeh C, Xu J, Peng Y et al (2009) Cross-range scaling for ISAR based on image rotation correlation. IEEE Geosci Remote Sens Lett 6(3):597–601
Loog M, Lauze F (2010) The improbability of harris interest points. IEEE Trans Pattern Anal Mach Intell 32(6):1141–1147
Corke P (2011) Robotics, vision and control: fundamental algorithms in MATLAB. Springer, Berlin
Patel VM, Easley GR, Healy DM, Chellappa R (2010) Compressed synthetic aperture radar. IEEE J Sel Top Signal Proces 4(2):244–254
Xu G, Bao M, Li Y-C, Xing M-D (2011) High precision ISAR imaging via Bayesian statistics. Syst Eng Electron 33(11):2382–2388
Wang C, Wang Y, Li SB (2013) Inverse synthetic aperture radar imaging of ship targets with complex motion based on match Fourier transform for cubic chirps model. IET Radar Sonar Navig 7(9):994–1003
Zhang Y-K, Xiao Y, Hu S-H (2011) 3D motion and geometric information system of single-antenna radar based oil incomplete 1D range data. J Syst Eng Electron 22(3):412–420
Wang Y, Jiang Y (2011) Inverse synthetic aperture radar imaging of maneuvering target based on the product generalized cubic phase function. IEEE Geosci Remote Sens Lett 8(5):958–962
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Di, G., Su, F. & Xu, X. Cross-range scaling of inverse synthetic aperture radar images with complex moving targets based on parameter estimation. J Supercomput 76, 4095–4116 (2020). https://doi.org/10.1007/s11227-017-2209-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11227-017-2209-1