Ship motions during long coherent processing interval (CPI) have six degrees of freedom, and the oscillatory motions are roughly periodical. The traditional ship imaging methods usually use a short time interval to form an image, while the image quality may suffer from low resolution, poor signal-to-noise ratio (SNR), and scatter scintillation. Using a longer CPI to generate an image may improve the quality but, however, largely increase the focusing difficulty. In this article, we investigate the focusing challenges of oscillatory ships with long CPI. Through analyzing the relative motion between the radar and the ship, the properties of wavenumber domain support (WDS) and point spreading function (PSF) of oscillatory ship imaging are studied. It is illustrated that the WDS is a 3-D sparse curved surface generated by the complex relative motion, with a time-variant energy density, nonparallel spectrum boundaries, and a complex structure. The PSF of an oscillatory ship may have a 3-D resolution but also multiple high-level sidelobes. The relationship between the WDS and the nonideal PSF is illustrated with the projection slice theorem (PST). Moreover, it is discussed that the scatterers distributed on a 3-D ship cannot be focused uniformly on a 2-D imaging plane (IP) due to the variation of the slant-range plane (SRP). The projection relationships of the resolutions and focusing positions between the SRP and the IP are also derived. Simulation results are presented to validate the analyses throughout this article.

Combining inverse projection and vote accumulation methods, we propose a novel 3D geometric reconstruction method based on inverse synthetic aperture radar (ISAR) image sequence for triaxially stabilized space targets. Considering that the translation of a triaxially stabilized space target results in a large angular rotation of the radar line of sight (LOS) and an attitude adjustment rotation of the target itself, the projection relationship between radar imaging plane and a triaxially stabilized space target is constructed first. Subsequently, we perform an inverse projection on the dominant points extracted from each imaging plane to determine the location of the 3D candidate scatterers and assign a voting value of 1 to each position. By accumulating these vote values, we can obtain the total number of votes for the candidate scatterer position. We treat candidate 3D scatterers with a large cumulative number of votes as actual scatterers. Thus, the target 3D geometry can be obtained. Compared to traditional matrix factorization based 3D reconstruction methods, this method is more accurate and ensures that the target pose is consistent with the actual pose. At the same time, compared with 3D reconstruction methods based on energy accumulation ideas, this method produces fewer false scatterers and has higher credibility. Experimental results based on the simulated point target and electromagnetic data are presented to validate the effectiveness and robustness of the proposed method.

In a low signal-to-noise ratio (SNR) environment, conventional range profiles-based motion compensation (MoCo) methods become inapplicable for inverse synthetic aperture radar (ISAR) imaging. In this article, a novel method for range profile alignment along with phase adjustment is proposed. The method is applied in the uncompressed phase history domain without the need for a prominent point. Motion errors are estimated from a phase map using only fast Fourier transform (FFT) and Hadamard multiplication operations, making the method suitable for real-time applications. The proposed method strives to aggregate the energy of all scatterers into a single peak by 2-D coherent accumulation incorporating the product of the radar pulse backscattering and its subsequent pulse, hence the reference to phase gradient processing (PGP). This process strengthens SNR and overcomes the problems associated with low signal power, even when the range profiles are submerged in noise. Experimental results are provided to demonstrate the performance of the proposed method compared with the state-of-the-art algorithms.

In the corner reflector jamming scenario, the ship target and the corner reflector array have different degrees of defocusing in the synthetic aperture radar (SAR) image due to their complex motions, which is unfavorable to the subsequent target recognition. In this manuscript, we propose an imaging method for marine targets based on time–frequency analysis with the modified Clean technique. Firstly, the motion models of the ship target and the corner reflector array are established, and the characteristics of their Doppler parameter distribution are analyzed. Then, the Chirp Rate–Quadratic Chirp Rate Distribution (CR-QCRD) algorithm is utilized to estimate the Doppler parameters. To address the challenges posed by the aggregated scattering points of the ship target and the overlapping Doppler histories of the corner reflector array, the Clean technique is modified by short-time Fourier transform (STFT) filtering and amplitude–phase distortion correction using fractional Fourier transform (FrFT) filtering. This modification aims to improve the accuracy and efficiency of extracting scattering point components. Thirdly, in response to the poor universality of the traditional Clean iterative termination condition, the kurtosis of the residual signal spectrum amplitude is adopted as the new iterative termination condition. Compared with the existing imaging methods, the proposed method can adapt to the different Doppler distribution characteristics of the ship target and the corner reflector array, thus realizing better robustness in obtaining a well-focused target image. Finally, simulation experiments verify the effectiveness of the algorithm.

Spectrum analysis (SA) plays an important role in radar signal processing, especially in radar imaging algorithm design. Because it is usually hard to obtain the analytical expression of spectrum by the Fourier integral directly, principle of stationary phase (POSP)-based SA is applied to approximate this integral. However, POSP requires the phase of the signal to vary rapidly, which is not the case in circular synthetic aperture radar (SAR) and turntable inverse SAR (ISAR). To solve this problem, a new SA method based on time-frequency reversion (TFRSA) is proposed, which utilizes the relationship of the Fourier transform pairs and their corresponding signal phases. In addition, the connection between the imaging geometry and time-frequency relationship is also analyzed and utilized to help solve the time-frequency reversion. When the TFRSA is applied to the linear trajectory SAR, the obtained spectrum expression is the same as the result of POSP. When it is applied to ISAR, the spectrum expressions of near-field and far-field are derived and their difference is found to be position-independent. Based on this finding, an extended polar format algorithm (EPFA) for near-field ISAR imaging is proposed, which can solve the distortion and defocusing problems caused by traditional ISAR imaging algorithms. When it is applied to the circular SAR (CSAR), a new and efficient imaging method based on EPFA is proposed, which can solve the low efficiency problem of conventional BP-based CSAR imaging algorithms. The simulations and real data processing results are provided to validate the effectiveness of proposed method.

Background: A retinal prosthesis is designed to help the blind to obtain some sight. It consists of an external part and an internal part. The external part is made up of a camera, an image processor and an RF transmitter. The internal part is made up of an RF receiver, implant chip and microelectrode.Methods: Currently, the number of microelectrodes is in the hundreds, and we do not know the mechanism for using an electrode to stimulate the optic nerve. A simple hypothesis is that the pixels in an image correspond to the electrode. The images captured by the camera should be processed by suitable strategies to correspond to stimulation from the electrode. Thus, it is a question of how to obtain the important information from the image captured in the picture. Here, we use the region of interest (ROI), a useful algorithm for extracting the ROI, to retain the important information, and to remove the redundant information.Results: This paper explains the details of the principles and functions of the ROI. Because we are investigating a real-time system, we need a fast processing ROI as a useful algorithm to extract the ROI. Thus, we simplified the ROI algorithm and used it in an outside image-processing digital signal processing (DSP) system of the retinal prosthesis.Conclusion: The results show that our image-processing strategies are suitable for a real-time retinal prosthesis and can eliminate redundant information and provide useful information for expression in a low-size image.