Abstract
When inverse synthetic aperture radar (ISAR) imaging maneuvers targets, the azimuth echo of the target scattering point causes a Doppler frequency time-varying problem, which leads to the blurring and defocusing of the imaging results. Traditional imaging methods struggle to meet the imaging requirements for maneuvering targets due to a poor imaging effect or low efficiency. Given these challenges, a modified chirp Fourier transform (MCFT) imaging method is proposed in this paper, based on the specific relationship between the target rotation parameters and the radar echo signal parameters. Firstly, discrete chirp Fourier transform is used to quickly estimate the target’s coarse rotation ratio. Then, the minimum entropy function and gradient descent method are used to calculate the target’s accurate rotation ratio. Finally, the azimuth focusing image is accomplished by performing MCFT once on the azimuth echo signal using the accurate rotation ratio. This method avoids estimating and separating the sub-echo components one-by-one, considerably improves the imaging speed, and guarantees the best imaging quality by applying the global minimum entropy principle. The experimental results show that the proposed method effectively achieves the two-dimensional, high-quality, and fast imaging of maneuvering targets.
Highlights
An inverse synthetic aperture radar (ISAR) can achieve long-range and high-resolution imaging of non-cooperative targets in all weather and at all times, so it has an important application value in both military and civilian fields [1,2,3]
For the matrix form shown in Equation (17), if the length of the data and the rotation ratio KΩω of the target are known, the phase function WFN can be stored in advance, similar to the phase factor function in fast Fourier transform (FFT) calculation, so that fast modified chirp Fourier transform (MCFT) calculation can be realized
Input the radar echo signal; Generate reference signal by measured reference range; Perform dechirping processing for the echo signal and reference signal; Range compression and translational compensation for the signal after dechirping; Coarse rotation ratio estimation based on discrete chirp Fourier transform (DCFT) in Section 3.2; Accurate rotation ratio estimation based on minimum entropy in Section 3.3; Azimuth compression based on MCFT in Section 3.1; Output the two-dimensional (2D) ISAR image
Summary
An inverse synthetic aperture radar (ISAR) can achieve long-range and high-resolution imaging of non-cooperative targets in all weather and at all times, so it has an important application value in both military and civilian fields [1,2,3]. The ratio of the quadratic phase term (chirp rate) to the first-order phase term (central frequency) of the scattering point echo signal is approximately a fixed value and equal to the ratio of the target rotational angular acceleration to the rotational angular velocity [19,20]. Given this feature, an imaging algorithm based on matched Fourier transform (MFT) [21] is proposed in this study, but this algorithm only uses a single sub-echo signal for parameter estimation and the estimation error is large. Simulation and experimental results show that the proposed method can realize two-dimensional, high-resolution, and fast imaging of maneuvering targets
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