Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-var...Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler （RD） algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal （PPS） after the motion compensation, and a new approach of time-frequency represen- tation, generalized polynomial Wigner-Ville distribution （GPWVD）, is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase （EMP） principle. Compared with the conventional polynomial Wigner-Ville distribution （PWVD）, the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution （WVD） and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.展开更多
Cross-range scaling plays an important role in the inverse synthetic aperture radar(ISAR) imaging. Many of the published cross-range scaling algorithms are based on the fast Fourier transformation(FFT). However, the F...Cross-range scaling plays an important role in the inverse synthetic aperture radar(ISAR) imaging. Many of the published cross-range scaling algorithms are based on the fast Fourier transformation(FFT). However, the FFT technique is resolution limited, so that the FFT-based algorithms will fail in the rotation velocity(RV) estimation of the slow rotation target. In this paper,we propose an accurate cross-range scaling algorithm based on the multiple signal classification(MUSIC) method. We first select some range bins with the mono-component linear frequency modulated(LFM) signal model. Then, we dechirp the signal of each selected range bin into the form of sinusoidal signal, and utilize the super-resolution MUSIC technique to accurately estimate the frequency. After processing all the range bins, a linear relationship related to the RV can be obtained. Eventually, the ISAR image can be scaled. The proposal can precisely estimate the small RV of the slow rotation target with low computational complexity. Furthermore, the proposal can also be used in the case of cross-range scaling for the sparse aperture data. Experimental results with the simulated and raw data validate the superiority of the novel method.展开更多
基金supported by the National Natural Science Foundation of China (61001166)the Specialized Research Fund for the Doctoral Program of Higher Education (20092302120002)+3 种基金the Aerospace Support Fund (2011-HT-HGD-16)the Fundamental Research Funds for the Central Universities (HIT.BRETIII.201207)the Postdoctoral ScienceResearch Developmental Foundation of Heilongjiang Province (LBHQ11092)the Heilongjiang Postdoctoral Specialized Research Fund
文摘Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler （RD） algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal （PPS） after the motion compensation, and a new approach of time-frequency represen- tation, generalized polynomial Wigner-Ville distribution （GPWVD）, is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase （EMP） principle. Compared with the conventional polynomial Wigner-Ville distribution （PWVD）, the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution （WVD） and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.
基金supported by the National Natural Science Foundation of China (61871146,61622107)the China Scholarship Council(201906120113)。
文摘Cross-range scaling plays an important role in the inverse synthetic aperture radar(ISAR) imaging. Many of the published cross-range scaling algorithms are based on the fast Fourier transformation(FFT). However, the FFT technique is resolution limited, so that the FFT-based algorithms will fail in the rotation velocity(RV) estimation of the slow rotation target. In this paper,we propose an accurate cross-range scaling algorithm based on the multiple signal classification(MUSIC) method. We first select some range bins with the mono-component linear frequency modulated(LFM) signal model. Then, we dechirp the signal of each selected range bin into the form of sinusoidal signal, and utilize the super-resolution MUSIC technique to accurately estimate the frequency. After processing all the range bins, a linear relationship related to the RV can be obtained. Eventually, the ISAR image can be scaled. The proposal can precisely estimate the small RV of the slow rotation target with low computational complexity. Furthermore, the proposal can also be used in the case of cross-range scaling for the sparse aperture data. Experimental results with the simulated and raw data validate the superiority of the novel method.
