Inverse Synthetic Aperture Radar Imaging of Nonuniformly Rotating Target Based on the Parameters Estimation of Multicomponent Quadratic Frequency-Modulated Signals

Inverse synthetic aperture radar (ISAR) is very useful in radar signature applications. In ISAR imaging of nonuniformly rotating target, the radar echo signal in a range cell can be modeled as multicomponent quadratic frequency-modulated (QFM) signals. The high-quality radar images can be obtained by the parameters estimation of QFM signals combined with the range-instantaneous-Doppler technique. In this paper, a novel algorithm for the parameters estimation of QFM signal via the modified cubic phase function (MCPF) is presented. This algorithm estimates the quadratic phase coefficient at first, and the other parameters can be estimated by the traditional CPF and the fast Fourier transform. The implementation of MCPF algorithm requires only 1-D maximizations, and the comparison with some existing algorithms is discussed. The ISAR imaging results of simulated and raw data validate the effectiveness of the novel algorithm proposed in this paper.

[1]  Daiyin Zhu,et al.  Robust ISAR Range Alignment via Minimizing the Entropy of the Average Range Profile , 2009, IEEE Geoscience and Remote Sensing Letters.

[2]  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.

[3]  P. O'Shea A new technique for instantaneous frequency rate estimation , 2002, IEEE Signal Processing Letters.

[4]  Yong Wang,et al.  ISAR Imaging of a Ship Target Using Product High-Order Matched-Phase Transform , 2009, IEEE Geoscience and Remote Sensing Letters.

[5]  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.

[6]  Yong Wang,et al.  ISAR Imaging of Ship Target with Complex Motion Based on New Approach of Parameters Estimation for Polynomial Phase Signal , 2011, EURASIP J. Adv. Signal Process..

[7]  Kyung-Tae Kim,et al.  Application of Subarray Averaging and Entropy Minimization Algorithm to Stepped-Frequency ISAR Autofocus , 2008, IEEE Transactions on Antennas and Propagation.

[8]  Mengdao Xing,et al.  Translational motion compensation and instantaneous imaging of ISAR maneuvering target , 2001, International Symposium on Multispectral Image Processing and Pattern Recognition.

[9]  Benjamin Friedlander,et al.  The discrete polynomial-phase transform , 1995, IEEE Trans. Signal Process..

[10]  Yong Wang,et al.  Inverse Synthetic Aperture Radar Imaging of Maneuvering Target Based on the Product Generalized Cubic Phase Function , 2011, IEEE Geoscience and Remote Sensing Letters.

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

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

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

[14]  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.

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

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

[17]  Genyuan Wang,et al.  Inverse synthetic aperture radar imaging of nonuniformly rotating targets , 1996 .

[18]  Yang,et al.  Modifications of the Cubic Phase Function , 2008 .

[19]  Mengdao Xing,et al.  Time-frequency approaches to ISAR imaging of maneuvering targets and their limitations , 2001 .

[20]  Hao Ling,et al.  Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts , 2003 .

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

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

[23]  Yong Wang,et al.  ISAR Imaging of Maneuvering Target Based on the Local Polynomial Wigner Distribution and Integrated High-Order Ambiguity Function for Cubic Phase Signal Model , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[24]  Xiang Li,et al.  ISAR Imaging of Targets With Complex Motion Based on Discrete Chirp Fourier Transform for Cubic Chirps , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[25]  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..

[26]  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..

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

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

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