Abstract
Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target’s maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables—the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target’s motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method.
Highlights
Inverse synthetic aperture radar (ISAR) imaging plays important roles in civil and military fields, and has attracted the attention of many researchers in the past decades [1,2,3,4,5,6,7,8]
We study the inverse synthetic aperture radar (ISAR) imaging of targets with not too severe maneuvering motion, and propose an adaptive imaging method based on modified Fourier transform
Due to the maneuvering of the target, the ISAR image is blurred in the cross-range direction
Summary
Inverse synthetic aperture radar (ISAR) imaging plays important roles in civil and military fields, and has attracted the attention of many researchers in the past decades [1,2,3,4,5,6,7,8]. In ISAR imaging scenarios, the motion of the target can be decomposed into translational motion and rotational motion. The rotational motion contributes to imaging and the translational motion induces the range misalignment and phase incoherence [10]. The translational motion compensation which consists of range alignment and phase compensation [11,12,13,14] is essential. The range-Doppler (RD) algorithm [15,16] is usually adopted to produce a 2D ISAR image. The RD algorithm assumes that the scatterer’s Doppler frequency is constant during the time period of aperture synthesis. This is suitable for ISAR imaging of targets with smooth motion. The RD algorithm fails and a Sensors 2018, 18, 1370; doi:10.3390/s18051370 www.mdpi.com/journal/sensors
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