scholarly journals On the Frequency Sweep Rate Estimation in Airborne FMCW SAR Systems

2020 ◽  
Vol 12 (20) ◽  
pp. 3448
Author(s):  
Carmen Esposito ◽  
Paolo Berardino ◽  
Antonio Natale ◽  
Stefano Perna
Keyword(s):  
Synthetic Aperture Radar ◽  
Experimental Analysis ◽  
Continuous Wave ◽  
Sweep Rate ◽  
Accurate Estimate ◽  
Synthetic Aperture ◽  
Time Interval ◽  
Sar Image ◽  
Frequency Sweep ◽  
Electronic Parameters

Use of Frequency Modulated Continuous Wave (FMCW) Synthetic Aperture Radar (SAR) systems requires to accurately know the electronic parameters of the system. In particular, the use of an incorrect value of the Frequency Sweep Rate (FSR) introduces geometric distortions in the focused images. Recently, a method, that we name FSR Estimate Through Corner reflectors (FSRETC), has been proposed to estimate the FSR value actually employed by the radar. The method is based on the use of the SAR image focused with the available erroneous FSR. Moreover, it exploits a number of Corner Reflectors (CRs) deployed over the illuminated area. In this work, we provide an assessment of the capabilities of the FSRETC algorithm. The overall analysis is performed through the use of a real dataset consisting of 10 acquisitions carried out in 2018 (5 acquisitions) and 2019 (5 acquisitions) with an airborne FMCW SAR system. The presented experimental analysis shows that even with a single acquisition, use of two CRs sufficiently far from each other in the range direction, allows achieving an accurate estimate of the searched FSR. Moreover, it is shown that the obtained estimate is very stable over the time. Therefore, the overall procedure can be applied only once, since the estimated values can be safely used for the subsequent missions, at least for the time interval considered in the work, that is, 14 months. In addition, the presented results pose the basis for an enhanced measurement strategy that allows effective application of the FSRETC algorithm through the use of only one CR.

scholarly journals Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1643
Author(s):  
Ming Liu ◽  
Shichao Chen ◽  
Fugang Lu ◽  
Mengdao Xing ◽  
Jingbiao Wei
Keyword(s):  
Synthetic Aperture Radar ◽  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Sar Image ◽  
Constant False Alarm Rate ◽  
Sar Images ◽  
Complex Scenes

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

scholarly journals Micro-Motion Estimation of Maritime Targets Using Pixel Tracking in Cosmo-Skymed Synthetic Aperture Radar Data—An Operative Assessment

2019 ◽  
Vol 11 (14) ◽  
pp. 1637 ◽  
Author(s):  
Filippo Biondi ◽  
Pia Addabbo ◽  
Danilo Orlando ◽  
Carmine Clemente
Keyword(s):  
Synthetic Aperture Radar ◽  
Wide Band ◽  
Radar Data ◽  
Satellite System ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Synthetic Aperture Radar Data ◽  
Micro Motion ◽  
Novel Strategy ◽  
Aperture Radar

In this paper, we propose a novel strategy to estimate the micro-motion (m-m) of ships from synthetic aperture radar (SAR) images. To this end, observe that the problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry through two radars spatially separated by a baseline along the azimuth direction. The approach proposed in this paper for m-m estimation of ships, occupying thousands of pixels, processes the information generated during the coregistration of several re-synthesized time-domain and not overlapped Doppler sub-apertures. Specifically, the SAR products are generated by splitting the raw data according to a temporally small baseline using one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are then estimated. The performance analysis is conducted on one ST SAR image recorded by COSMO-SkyMed satellite system. Finally, the newly proposed approach paves the way for application to the surveillance of land-based industry activities.

Speckle Noise Filtering Using Back-Propagation Multi-Layer Perceptron Network in Synthetic Aperture Radar Image

2020 ◽  
pp. 489-510
Author(s):  
Khwairakpam Amitab ◽  
Debdatta Kandar ◽  
Arnab K. Maji
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Synthetic Aperture Radar ◽  
Back Propagation ◽  
Speckle Noise ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Multi Layer Perceptron ◽  
Sar Images ◽  
Artificial Neural

Synthetic Aperture Radar (SAR) are imaging Radar, it uses electromagnetic radiation to illuminate the scanned surface and produce high resolution images in all-weather condition, day and night. Interference of signals causes noise and degrades the quality of the image, it causes serious difficulty in analyzing the images. Speckle is multiplicative noise that inherently exist in SAR images. Artificial Neural Network (ANN) have the capability of learning and is gaining popularity in SAR image processing. Multi-Layer Perceptron (MLP) is a feed forward artificial neural network model that consists of an input layer, several hidden layers, and an output layer. We have simulated MLP with two hidden layer in Matlab. Speckle noises were added to the target SAR image and applied MLP for speckle noise reduction. It is found that speckle noise in SAR images can be reduced by using MLP. We have considered Log-sigmoid, Tan-Sigmoid and Linear Transfer Function for the hidden layers. The MLP network are trained using Gradient descent with momentum back propagation, Resilient back propagation and Levenberg-Marquardt back propagation and comparatively evaluated the performance.

scholarly journals Design of an antenna array for a LFM-CW synthetic aperture radar prototype

DYNA ◽  
2020 ◽  
Vol 87 (212) ◽  
pp. 96-101
Author(s):  
Alfonso José Zozaya ◽  
Paulino Jesús Del Pino Pettinare
Keyword(s):  
Synthetic Aperture Radar ◽  
Antenna Arrays ◽  
Patch Antenna ◽  
Continuous Wave ◽  
Horizontal Resolution ◽  
Synthetic Aperture ◽  
Empirical Equations ◽  
Full Wave ◽  
Theoretical Design ◽  
Aperture Radar

This paper deals with the design of two identical 1 × 4 patch antenna arrays for a linear frequency modulated (LFM) continuous wave (CW) synthetic aperture radar (SAR) prototype. The theoretical design is carried out by using the empirical equations available in the literature, while the design optimization is performed by numerical methods using two commercial full wave simulators. Once the antennas are built they are experimentally characterized and incorporated into a radar prototype implemented at the Ecuadorian Space Institute. The radar is tested in a probing polygon and the horizontal resolution is estimated. A measured azimuthal resolution value very close to the theoretical one is achieved

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