Search Results (10)

While the wavenumber-domain approach enables large-angle inverse synthetic aperture radar (ISAR) cross-range scaling, its practical application remains constrained by the target’s non-uniform rotation and scene center offset (SCO). In response to this issue, this paper introduces a novel large-angle ISAR cross-range scaling method through a joint estimation method based on the wavenumber domain. A non-uniform rotational wavenumber-domain signal model with SCO is developed. Utilizing this model and the sensitivity of wavenumber-domain imaging to SCO, a joint estimation algorithm that combines particle swarm optimization (PSO) and image entropy evaluation is proposed, achieving accurate parameter estimation. Leveraging the estimated parameters, the range and cross-range scaling factors in the wavenumber-domain imaging are derived, facilitating ISAR cross-range scaling with higher accuracy than the traditional method. The effectiveness and robustness of the proposed method are validated under various conditions, through scattering point and electromagnetic computing simulation. Full article

In inverse synthetic aperture radar (ISAR) systems, image quality often suffers from the non-uniform rotation of non-cooperative targets. Rotational motion compensation (RMC) is necessary to perform refocused ISAR imaging via estimated rotational motion parameters. However, estimation errors tend to accumulate with the estimated processes, deteriorating the image quality. A novel RMC algorithm is proposed in this study to mitigate the impact of cumulative errors. The proposed method uses an iterative approach based on a novel criterion, i.e., the minimum residual norm of the signal phases, to estimate different rotational parameters independently to avoid the issue caused by cumulative errors. First, a refined inverse function combined with interpolation is proposed to perform the RMC procedure. Then, the rotation parameters are estimated using an iterative procedure designed to minimize the residual norm of the compensated signal phases. Finally, with the estimated parameters, RMC is performed on signals in all range bins, and focused images are obtained using the Fourier transform. Furthermore, this study utilizes simulated and real data to validate and evaluate the performance of the proposed algorithm. The experimental results demonstrate that the proposed algorithm shows dominance in the aspects of estimation accuracy, entropy values, and focusing characteristics. Full article

Imaging maritime targets requires a high resolution and wide swath (HWRS) in a synthetic aperture radar (SAR). When operated with a variable pulse repetition interval (PRI), a staggered SAR can realize HRWS imaging, which needs to be reconstructed due to echo pulse loss and a nonuniformly sampled signal along the azimuth. The existing reconstruction algorithms are designed for stationary scenes in a staggered SAR mode, and thus, produce evident image defocusing caused by complex target motion for moving targets. Typically, the nonuniform sampling and complex motion of maritime targets aggravate the spectrum aliasing in a staggered SAR mode, causing inevitable ambiguity and degradation in its reconstruction performance. To this end, this study analyzed the spectrum of maritime targets in a staggered SAR system through theoretical derivation. After this, a reconstruction method named MBLCFD (Modified Best Linear Unbaised and Complex-Lag Time-Frequency Distribution) is proposed to refocus the blurred maritime target. First, the signal model of the maritime target with 3D rotation accompanying roll–pitch–yaw movement was established under the curved orbit of the satellite. The best linear unbiased (BLU) method was modified to alleviate the coupling of nonuniform sampling and target motion. A precise SAR algorithm was performed based on the method of inverse reversion to counteract the effect of a curved orbit and wide swath. Based on the hybrid SAR/ISAR technique, the complex-lag time-frequency distribution was exploited to refocus the maritime target images. Simulations and experiments were carried out to verify the effectiveness of the proposed method, providing precise refocusing performance in staggered mode. Full article

Aiming at the failure of traditional visual slam localization caused by dynamic target interference and weak texture in underground complexes, an effective robot localization scheme was designed in this paper. Firstly, the Harris algorithm with stronger corner detection ability was used, which further improved the ORB (oriented FAST and rotated BRIEF) algorithm of traditional visual slam. Secondly, the non-uniform rational B-splines algorithm was used to transform the discrete data of inertial measurement unit (IMU) into second-order steerable continuous data, and the visual sensor data were fused with IMU data. Finally, the experimental results under the KITTI dataset, EUROC dataset, and a simulated real scene proved that the method used in this paper has the characteristics of stronger robustness, better localization accuracy, small size of hardware equipment, and low power consumption. Full article

Friction-spinning as an innovative incremental forming process enables high degrees of deformation in the field of tube and sheet metal forming due to self-induced heat generation in the forming area. The complex thermomechanical conditions generate non-uniform residual stress distributions. In order to specifically adjust these residual stress distributions, the influence of different process parameters on residual stress distributions in flanges formed by the friction-spinning of tubes is investigated using the design of experiments (DoE) method. The feed rate with an effect of −156 MPa/mm is the dominating control parameter for residual stress depth distribution in steel flange forming, whereas the rotation speed of the workpiece with an effect of 18 MPa/mm dominates the gradient of residual stress generation in the aluminium flange-forming process. A run-to-run predictive control system for the specific adjustment of residual stress distributions is proposed and validated. The predictive model provides an initial solution in the form of a parameter set, and the controlled feedback iteratively approaches the target value with new parameter sets recalculated on the basis of the deviation of the previous run. Residual stress measurements are carried out using the hole-drilling method and X-ray diffraction by the cosα-method. Full article

In this study, the effect of different horizontal and vertical orientations of a model sample (cuboid gellan gel samples containing Maillard reactants) on microwave heat processing was investigated in the solid-state and magnetron microwave systems. To achieve this target, seven orientations inside both microwave cavities were defined. Two of the investigated sample orientations were in a vertical position with and without turntable rotation, and five in a horizontal position. Furthermore, samples at horizontal orientations were put at an angle position without turntable rotation. To analyze the microwave heating patterns, infrared (IR) pictures and photographs of the gellan gel samples were taken after processing to document IR-based thermal and Maillard color changes, respectively. Three main factors for improvement of the heating homogeneity were identified: first, processing samples in the solid-state microwave system; second, position variation of the sample by turntable activated; and third, horizontal orientation. In addition, it was observed that placing the gellan gel samples in a vertical position in the magnetron microwave system resulted in considerably more absorbed power and a more uniform microwave heat processing compared to other horizontal orientations in this system. This indicated a non-uniform microwave field distribution. The results of this study can also confirm the importance of designing suitable food packaging: a vertical shape for more microwave energy absorbance and thus, more energy efficiency, and a horizontal shape for more uniform microwave heat processing. Full article

When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data. Full article

In real applications, the image quality of the conventional monostatic Inverse Synthetic Aperture Radar (ISAR) for the maneuvering target is subject to the strong fluctuation of Radar Cross Section (RCS), as the target aspect varies enormously. Meanwhile, the maneuvering target introduces nonuniform rotation after translation motion compensation which degrades the imaging performance of the conventional Fourier Transform (FT)-based method in the cross-range dimension. In this paper, a method which combines the distributed ISAR technique and the Matching Fourier Transform (MFT) is proposed to overcome these problems. Firstly, according to the characteristics of the distributed ISAR, the multiple channel echoes of the nonuniform rotation target from different observation angles can be acquired. Then, by applying the MFT to the echo of each channel, the defocused problem of nonuniform rotation target which is inevitable by using the FT-based imaging method can be avoided. Finally, after preprocessing, scaling and rotation of all subimages, the noncoherent fusion image containing all the RCS information in all channels can be obtained. The accumulation coefficients of all subimages are calculated adaptively according to the their image qualities. Simulation and experimental data are used to validate the effectiveness of the proposed approach, and fusion image with improved recognizability can be obtained. Therefore, by using the distributed ISAR technique and MFT, subimages of high-maneuvering target from different observation angles can be obtained. Meanwhile, by employing the adaptive subimage fusion method, the RCS fluctuation can be alleviated and more recognizable final image can be obtained. Full article

Focusing on the inverse synthetic aperture radar (ISAR) imaging of targets with complex motion, this paper proposes a modified version of the Fourier transform, called non-uniform rotation transform, to achieve cross-range compression. After translational motion compensation, the target’s complex motion is converted into non-uniform rotation. We define two variables—relative angular acceleration (RAA) and relative angular jerk (RAJ)—to describe the rotational nonuniformity. With the estimated RAA and RAJ, rotational nonuniformity compensation is carried out in the non-uniform rotation transform matrix, after which, a focused ISAR image can be obtained. Moreover, considering the possible deviation of RAA and RAJ, we design an optimization scheme to obtain the optimal RAA and RAJ according to the optimal quality of the ISAR image. Consequently, the ISAR imaging of targets with complex motion is converted into a parameter optimization problem in which a stable and clear ISAR image is guaranteed. Compared to precedent imaging methods, the new method achieves better imaging results with a reasonable computational cost. Experimental results verify the effectiveness and advantages of the proposed algorithm. Full article

Major challenges for automatic ship detection in optical remote sensing (ORS) images include cloud, wave, island, wake clutters, and even the high variability of targets. This paper presents a practical ship detection scheme to resolve these existing issues. The scheme contains two main coarse-to-fine stages: prescreening and discrimination. In the prescreening stage, we construct a novel visual saliency detection method according to the difference of statistical characteristics between highly non-uniform regions which allude to regions of interest (ROIs) and homogeneous backgrounds. It can serve as a guide for locating candidate regions. In this way, not only can the targets be precisely detected, but false alarms are also significantly reduced. In the discrimination stage, to get a better representation of the target, both shape and texture features characterizing the ship target are extracted and concatenated as a feature vector for subsequent classification. Moreover, the combined feature is invariant to the rotation. Finally, a trainable Gaussian support vector machine (SVM) classifier is performed to validate real ships out of ship candidates. We demonstrate the superior performance of the proposed hierarchical detection method with detailed comparisons to existing efforts. Full article