When a target is in complex three-dimensional (3-D) motions, inverse synthetic aperture radar (ISAR) images cannot be obtained with any motion compensation algorithms. To address this problem, phase nonlinearity can be used to select imaging frames where target 2-D motion is dominant enough to obtain focused ISAR images. Conventionally, adaptive joint time frequency (AJTF) and particle swarm optimization (PSO) algorithms are performed to estimate the phase signals of prominent scatterers. These estimates are used to determine phase nonlinearity. However, such estimation algorithms undergo multi-dimensional optimizations, which yield significant increases in computational complexity for ISAR frame-selections. For more practical use of AJTF- and PSO-based frame-selections, we introduce a method to improve the computational efficiencies of the conventional methods. To this end, in the proposed method, a simple phase unwrapping-and-least square fitting method is used as an alternative to the AJTF and PSO methods. Because PU-LSM can provide reliable phase estimates quickly without complex optimization procedures, the proposed method is an improvement over AJTF- and PSO-based methods, especially in terms of computational efficiency. In simulations using ideal point scatterers, our proposed method performs well, in terms of frame-selection ability and computational efficiency. Furthermore, experimental results using real radar echoes validated the robustness and efficacy our proposed frame-selection method.

Detection of small-sized maritime targets is an important task for a marine surveillance radar. Recently, with the emergence of a marine surveillance radar system that has a narrow azimuth beamwidth and rapidly rotating antennas, the available dwell time for detecting a maritime target is usually very short. This short dwell time considerably degrades the performance of conventional detectors, especially those focusing on small-sized targets. In this paper, we propose an efficient detector for small-sized maritime targets to provide a reliable detection performance, even in short dwell times. The proposed scheme is based on a new joint metric, which results from the product of the magnitude and difference features in the Doppler spectra. We discriminate the target bins from sea clutter bins using a statistical discriminator based on the joint metric, whose probability density function follows the product distribution of standard gamma distributions. Compared to conventional detectors, the proposed scheme can provide a robust performance in terms of the average signal-to-clutter ratio as well as the detection rate, especially in shorter dwell times.

When a target undergoes complex three-dimensional (3D) motions, focused inverse synthetic aperture radar (ISAR) images cannot be obtained using any motion compensation algorithms. To address this problem, we propose a method to determine the suitable frame time and length for 2D ISAR imaging, which exploits phase nonlinearity and discrete polynomial phase transforms. In simulations and experiments, we observed that the proposed method can efficiently select proper frame times and lengths for 2D ISAR imaging.

When a target has 3-D rotation accompanying roll–pitch–yaw movement, it yields an additional phase component, which cannot be compensated for by any of the existing inverse synthetic aperture radar (ISAR) imaging methods. Under this condition, the resulting ISAR image will be severely distorted. Accordingly, selecting a proper imaging frame, where the target has only 2-D rotation, becomes the only solution, especially for range-Doppler (RD) algorithm. To do this, the conventional approach is to directly use the phase of the received signal, and however, this approach is vulnerable to noise and the cross-term interference of multiple scattering centers (SCs) in the range bin. To address these issues, we propose a new frame selection method using the range-instantaneous Doppler (RID) technique and Radon transform to detect the presence of 3-D rotation of the target within imaging frame. The proposed method comprises three steps: 1) obtain joint time–frequency distribution (JTFD) via the smoothed pseudo Wigner–Ville distribution (SPWVD); 2) estimate the orientation angle of the Radon image of the JTFD spectrum; and 3) select the suitable imaging frame using the estimated angle. Furthermore, to demonstrate the effectiveness of the proposed method, experimental results based on simulated and real measured data are provided.

To obtain exact size of non-cooperative target in ISAR images, an accurate cross-range scaling (CRS) should be performed. To do this, an image based approach, which exploits two sequential ISAR images based on the scale and rotational relationship between them, has been adopted in the existing ISAR CRS methods. However, they have two major problems: 1) unknown effective rotation center (ERC) of non-cooperative target, and 2) performance degradation owing to the scintillation of two ISAR images. To address these issues, in this paper, we propose a new CRS method, mainly consisting of two steps: 1) coarse estimation of rotation velocity (RV) in range-Doppler (RD) domain after feature extraction and matching, and 2) using the estimate in Step1, fine RV estimation via singular value decomposition (SVD) in range/cross-range (RC) domain. Furthermore, experimental results based on simulated and real measured data are provided to demonstrate the effectiveness of the proposed method.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)