Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) signals after motion compensation. Then, the modified version of Chirplet decomposition (MCD) based on the integrated high order ambiguity function (IHAF) is presented for the parameter estimation of AM-FM signals, and the corresponding high quality instantaneous ISAR images can be obtained from the estimated parameters. Compared with the MCD algorithm based on the generalized cubic phase function (GCPF) in the authors’ previous paper, the novel algorithm presented in this paper is more accurate and efficient, and the results with simulated and real data demonstrate the superiority of the proposed method.

[1]  Yang Yang,et al.  Multicomponent Signal Analysis Based on Polynomial Chirplet Transform , 2013, IEEE Transactions on Industrial Electronics.

[2]  G. Meng,et al.  Spline-Kernelled Chirplet Transform for the Analysis of Signals With Time-Varying Frequency and Its Application , 2012, IEEE Transactions on Industrial Electronics.

[3]  Humberto Henao,et al.  Diagnosis of Rotor and Stator Asymmetries in Wound-Rotor Induction Machines Under Nonstationary Operation Through the Instantaneous Frequency , 2014, IEEE Transactions on Industrial Electronics.

[4]  Jian Li,et al.  New Approaches for Chirplet Approximation , 2007, IEEE Transactions on Signal Processing.

[5]  Ljubisa Stankovic,et al.  L-class of time-frequency distributions , 1996, IEEE Signal Processing Letters.

[6]  Aykut Bultan,et al.  A four-parameter atomic decomposition of chirplets , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  H. S. Wolff,et al.  iRun: Horizontal and Vertical Shape of a Region-Based Graph Compression , 2022, Sensors.

[8]  Qing Huo Liu,et al.  ISAR Imaging of Targets With Complex Motions Based on the Keystone Time-Chirp Rate Distribution , 2014, IEEE Geoscience and Remote Sensing Letters.

[9]  Lin Luo,et al.  Inverse synthetic aperture radar imaging of maneuvering targets , 1998 .

[10]  Qing Huo Liu,et al.  ISAR Imaging of Targets With Complex Motion Based on the Chirp Rate–Quadratic Chirp Rate Distribution , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Marco Diani,et al.  High-resolution ISAR imaging of maneuvering targets by means of the range instantaneous Doppler technique: modeling and performance analysis , 2001, IEEE Trans. Image Process..

[12]  Yicheng Jiang,et al.  Inverse synthetic aperture radar imaging of three-dimensional rotation target based on two-order match Fourier transform , 2012, IET Signal Process..

[13]  V. C. Chen,et al.  Time-varying spectral analysis for radar imaging of manoeuvring targets , 1998 .

[14]  Sergio Barbarossa,et al.  Analysis of polynomial-phase signals by the integrated generalized ambiguity function , 1997, IEEE Trans. Signal Process..

[15]  Jose A. Antonino-Daviu,et al.  Instantaneous Frequency of the Left Sideband Harmonic During the Start-Up Transient: A New Method for Diagnosis of Broken Bars , 2009, IEEE Transactions on Industrial Electronics.

[16]  T. Thayaparan,et al.  Signal Decomposition by Using the S-Method With Application to the Analysis of HF Radar Signals in Sea-Clutter , 2006, IEEE Transactions on Signal Processing.

[17]  Peter T. Gough,et al.  A fast spectral estimation algorithm based on the FFT , 1994, IEEE Trans. Signal Process..

[18]  Yu Wang Inverse synthetic aperture radar imaging of manoeuvring target based on range-instantaneous- doppler and range-instantaneous-chirp-rate algorithms , 2012 .

[19]  Yong Wang,et al.  Inverse synthetic aperture radar imaging of targets with complex motion based on cubic Chirplet decomposition , 2015, IET Signal Process..

[20]  Leopoldo Angrisani,et al.  A measurement method based on a modified version of the chirplet transform for instantaneous frequency estimation , 2002, IEEE Trans. Instrum. Meas..

[21]  Yong Wang,et al.  Modified Adaptive Chirplet Decomposition with Application in ISAR Imaging of Maneuvering Targets , 2008, EURASIP J. Adv. Signal Process..

[22]  Yong Wang,et al.  ISAR imaging for three-dimensional rotation targets based on adaptive Chirplet decomposition , 2010, Multidimens. Syst. Signal Process..

[23]  Yong Wang,et al.  Approach for high-resolution inverse synthetic aperture radar imaging of ship target with complex motion , 2013, IET Signal Process..

[24]  Qinye Yin,et al.  A fast refinement for adaptive Gaussian chirplet decomposition , 2002, IEEE Trans. Signal Process..

[25]  Ram M. Narayanan,et al.  Manoeuvring target motion parameter estimation for ISAR image fusion , 2008 .

[26]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[27]  Gang Li,et al.  ISAR 2-D Imaging of Uniformly Rotating Targets via Matching Pursuit , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[28]  Junfeng Wang,et al.  Improved Global Range Alignment for ISAR , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[29]  Yong Wang,et al.  ISAR Imaging of Maneuvering Target Based on the L-Class of Fourth-Order Complex-Lag PWVD , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[30]  Qing Huo Liu,et al.  FAST PARAMETER ESTIMATION ALGORITHM FOR CUBIC PHASE SIGNAL BASED ON QUANTIFYING EFFECTS OF DOPPLER FREQUENCY SHIFT , 2013 .

[31]  I. Djurovic,et al.  Integrated Cubic Phase Function for Linear FM Signal Analysis , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[32]  Jack Walker,et al.  Range-Doppler Imaging of Rotating Objects , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[33]  Ran Tao,et al.  ISAR Imaging of a Ship Target Based on Parameter Estimation of Multicomponent Quadratic Frequency-Modulated Signals , 2014, IEEE Transactions on Geoscience and Remote Sensing.