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Range Doppler ISAR Imaging Using Chirp Pulse
Published in Anupama Namburu, Soubhagya Sankar Barpanda, Recent Advances in Computer Based Systems, Processes and Applications, 2020
G. V. Sai Swetha, P. Anjali Reddy, A. Naga Jyothi
Inverse Synthetic Aperture Radar (ISAR) is a dominant technique in signal processsing, which provides the electromagnetic image of the target in two dimensions. This radar imaging technique is used in any weather condition. The technique ISAR has been derived from the Synthetic Aperture Radar (SAR) technique. The radar is kept stationary as the target moves round as shown in figure 1. In SAR it increases the size of antenna so as to increase the resolution of the image. As the radar moves, at many positions pulses are being transmitted, and the returned signals (echoes) are increased in antenna aperture [1]. Likewise, the ISAR is employed to produce moving target’s images in Matlab simulation; the rest of the process is similar to the SAR. The techniques SAR and ISAR are being the highly interested platforms for the researches.
High-Resolution Step-Frequency Radar
Published in James D. Taylor, Ultra-wideband Radar Technology, 2018
Resolution in the cross range is obtained by resolving the Doppler frequency shift caused by the relative motion between the radar and the target in the azimuth (or cross-range) dimension. Different scatterers on target in the cross-range dimension have different line of sight velocities toward the radar and would give different Doppler frequency shifts. Thus, resolving the frequency shift will resolve the scatterers in the cross range. In synthetic aperture radar (SAR) imaging, it is the radar platform that provides relative motion whereas, in inverse synthetic aperture radar (ISAR), it is the target that provides the relative motion. However, in either case, relative motion should involve aspect angle changes between the radar and the target. Cross-range resolution is inversely proportional to the aspect angle change. Obviously, rotating the target will provide aspect angle change. Generally, translational motion between radar and target have some aspect angle change too, unless there is an unlikely situation in which their velocity vectors are pointed toward one another. In this section, discussion will be from the ISAR point of view, although the general principles are the same for both SAR and ISAR.
Applications of Windows
Published in K. M. M. Prabhu, Window Functions and Their Applications in Signal Processing, 2018
The basic principle of ISAR imaging is to coherently collect the scattered large bandwidth echoes produced due to the rotation of the object, which brings about a change in the viewing angle to the radar. By processing the echo signals collected, information of the individual point scatterers on the target object and their relative range can be derived. Therefore, the radar image can be assumed to consist of many energy points called scattering centers. ISAR signal processing consists of the following steps [18]: Range compression deconvolves the echoed signal from the transmitted signal, thereby forming the range profile.Motion compensation registers the moving targets with respect to the radar.Next, the image is constructed by arranging the received signal samples in a polar grid of different viewing angles and Doppler frequencies in frequency spatial domain.
A moving ISAR-object recognition using pi-sigma neural networks based on histogram of oriented gradient of edge
Published in International Journal of Image and Data Fusion, 2022
Asma Elyounsi, Hatem Tlijani, M.S. Bouhlel
Inverse synthetic aperture radar image target recognition is an important task in ISAR image interpretation and application. Due to the coherent imaging property of ISAR system, multiplicative speckle is an inherent phenomenon accompanying this kind of image, which leads to the degradation of image quality and makes an undesired effect on the ISAR image interpretation. In addition, these kinds of images are highly sensitive to image gradient variation caused by shadowing effects (Elyounsi , Tlijani and Bouhlel 2016a), interaction of the signature with the environment and other reasons related to the backscattering of target and background, which results in inconspicuous image contrast and makes the recognition a very difficult task to handle especially with traditional neural networks (Hao et al. 2013, Das et al.2015, Prasad et al.2015 and Kanungo et al. 2015) like the multilayer perceptron (MLP), back propagation neural networks and feed-forward network which show some drawbacks (Radhika and Shashi 2009, Ghazali et al. 2011, Widrow and Lehr, 1990) including slowness for both converge rate and training time, also the inability to deal with problem of size.
Integrated Transfer Learning Method for Image Recognition Based on Neural Network
Published in IETE Journal of Research, 2021
JingYuan He, BaiLong Yang, Yang Su
In [1, 2], the authors studied scanning electron microscopy (SEM). This method can solve specific tasks. In [3], the author proposed a method for automatically identifying ultrasound images of thyroid papillary carcinoma using convolutional neural networks. In [4, 5], the author discusses the ISAR (Inverse Synthetic Aperture Radar) image enhancement algorithm. In [6, 7], the author built a dataset of machine images of more than 100 machines, and designed a convolutional neural network (CNN). In [8, 9], the author optimized the convolutional neural network (CNN) and proposed a model that can effectively identify different types and levels of image noise. In [10, 11], the writer aimed sampling and model measurements for CNN image identification. The detection rate of the confirmed image is 82.5%, which proves the good performance of the model. In, the author proposed a method to identify digital images by processing the images and classifying them by back propagation neural networks. The method could identify the content of roasted coffee beans with a precision of 97.5%.
A review of microwave testing of glass fibre-reinforced polymer composites
Published in Nondestructive Testing and Evaluation, 2019
Zhen Li, Arthur Haigh, Constantinos Soutis, Andrew Gibson, Ping Wang
For SAR, a radar antenna is typically mounted on a moving platform, and the phase history of the scattered wavefront recorded varies with the vehicle position over a modest bandwidth obtained through pulsing or chirping the radar frequency [81]. For digital beam forming, radar phased-arrays are operated by creating a beam which can be electronically steered to point in different directions. However, the circuitry for phase shifting is complicated, and the system is currently not cost-effective. In microwave holography, the single-frequency 2D holography is combined with wideband 2D SAR to produce a three-dimensional (3D) representation of an object [82]. In addition, one can slice the 3D image at various depths (depending on the available signal bandwidth), creating image slices similar to those produced by X-ray computed tomography [83–85]. Inverse synthetic aperture radar (ISAR), analogous to SAR, is not discussed here, for in this method the radar is stationary and the targets are in motion [86]. This setup is not practical in many engineering applications.