A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

For parallel bistatic forward-looking synthetic aperture radar (SAR) imaging, the instantaneous slant range is a double-square-root expression due to the separate transmitter-receiver system form. The hyperbolic approximation provides a feasible solution to convert the dual square-root expression into a single-square-root expression. However, some high-order terms of the range Taylor expansion have not been considered during the slant range approximation procedure in existing methods, and therefore, inaccurate phase compensation occurs. To obtain a more accurate compensation result, an improved hyperbolic approximation range form with high-order terms is proposed. Then, a modified omega-K algorithm based on the new slant range form is adopted for parallel bistatic forward-looking SAR imaging. Several simulation results validate the effectiveness of the proposed imaging algorithm.

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Adaptive Synthetic Aperture Radar (SAR) Imaging for Optimal Cross-Range Resolution and Image Quality in NDE Applications

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2021.3118080 ◽

2021 ◽

Vol 70 ◽

pp. 1-7

Author(s):

Chao Liu ◽

Reza Zoughi

Keyword(s):

Image Quality ◽

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Range Resolution ◽

Sar Imaging ◽

Aperture Radar

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COMPRESSED SYNTHETIC APERTURE RADAR IMAGING BASED ON MAXWELL EQUATION

Jurnal Teknologi ◽

10.11113/jt.v78.8922 ◽

2016 ◽

Vol 78 (6-3) ◽

Author(s):

Rahmat Arief ◽

Dodi Sudiana ◽

Kalamullah Ramli

Keyword(s):

Synthetic Aperture Radar ◽

Imaging System ◽

Sampling Rate ◽

Large Data ◽

Synthetic Aperture ◽

Fast Time ◽

Match Filter ◽

Compressed Sampling ◽

Sar Imaging ◽

Aperture Radar

Within few years backward, researches had presented the ability of compressive sensing to handle the large data problem on high resolution synthetic aperture radar (SAR) imaging. The main issue on CS framework that should be dealt with the SAR imaging is on the requirement of linearization on the measurement system. This paper proposes a new approach on formulating the compressed SAR echo imaging system which is derived from the Maxwell’s equations with continuous signal along the SAR antenna movement. Born approximation is applied to approximate the linear form of the SAR echo imaging system. In addition, the compressed sampling is formed by reducing the sampling rate of received radar signals randomly simultaneously on both of low sampling of fast time and slow time signals and by reducing the pulse period interval of transmitted signals. The simulation’s result shows that a better focused reconstructed sparse target can be achieved compared with the conventional match filter based Range Doppler (RD) method.

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A New Synthetic Aperture Radar (SAR) Imaging Method Combining Match Filter Imaging and Image Edge Enhancement

Sensors ◽

10.3390/s18124133 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4133 ◽

Cited By ~ 2

Author(s):

Bing Sun ◽

Chuying Fang ◽

Hailun Xu ◽

Anqi Gao

Keyword(s):

Image Processing ◽

Image Segmentation ◽

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Imaging Method ◽

Sar Image ◽

Sar Images ◽

Gradient Operator ◽

Sar Imaging ◽

Aperture Radar

In general, synthetic aperture radar (SAR) imaging and image processing are two sequential steps in SAR image processing. Due to the large size of SAR images, most image processing algorithms require image segmentation before processing. However, the existence of speckle noise in SAR images, as well as poor contrast and the uneven distribution of gray values in the same target, make SAR images difficult to segment. In order to facilitate the subsequent processing of SAR images, this paper proposes a new method that combines the back-projection algorithm (BPA) and a first-order gradient operator to enhance the edges of SAR images to overcome image segmentation problems. For complex-valued signals, the gradient operator was applied directly to the imaging process. The experimental results of simulated images and real images validate our proposed method. For the simulated scene, the supervised image segmentation evaluation indexes of our method have more than 1.18%, 11.2% and 11.72% improvement on probabilistic Rand index (PRI), variability index (VI), and global consistency error (GCE). The proposed imaging method will make SAR image segmentation and related applications easier.

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Analysis on the Effects of SAR Imaging Parameters and Environmental Conditions on the Standard Deviation of the Co-Polarized Phase Difference Measured over Sea Surface

Remote Sensing ◽

10.3390/rs11010018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 18 ◽

Cited By ~ 3

Author(s):

Andrea Buono ◽

Carina Regina de Macedo ◽

Ferdinando Nunziata ◽

Domenico Velotto ◽

Maurizio Migliaccio

Keyword(s):

Standard Deviation ◽

Synthetic Aperture Radar ◽

Phase Difference ◽

Environmental Conditions ◽

Sea Surface ◽

Synthetic Aperture ◽

Imaging Parameters ◽

Sar Imaging ◽

Aperture Radar

This study aimed at analyzing the effect of Synthetic Aperture Radar (SAR) imaging parameters and environmental conditions on the standard deviation of the co-polarized phase difference (sjC ) evaluated over sea surface[...]

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Analysis and Simulation on Imaging Performance of Backward and Forward Bistatic Synthetic Aperture Radar

Remote Sensing ◽

10.3390/rs10111676 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1676 ◽

Cited By ~ 3

Author(s):

Tingting Li ◽

Kun-Shan Chen ◽

Ming Jin

Keyword(s):

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Forward Region ◽

Range Resolution ◽

Bistatic Sar ◽

Imaging Results ◽

Sar Imaging ◽

Bistatic Synthetic Aperture Radar ◽

Motion Parameters ◽

Aperture Radar

In recent years, bistatic synthetic aperture radar (SAR) technique has attracted considerable and increasing attention. Compared to monostatic SAR for which only the backscattering is measured, bistatic SAR expands the scattering measurements in aspects of angular region and polarization, and greatly enhances the capability of remote sensing over terrain and sea. It has been pointed out in recent theoretical researches that bistatic scattering measured in the forward region is preferable to that measured in the backward region in lines of surface parameters retrieval. In the forward region, both dynamic range and signal sensitivity increase to a great extent. For these reasons, bistatic SAR imaging is desirable. However, because of the separated positions of the transmitter and receiver, the degrees of freedom in the parameter space is increased and the forward bistatic imaging is more complicated than the backward bistatic SAR in the aspects of bistatic range history, Doppler parameter estimation and motion compensation, et, al. In this study, we analyze bistatic SAR in terms of ground range resolution, azimuth resolution, bistatic range history and signal to noise ratio (SNR) in different bistatic configurations. Effects of system motion parameters on bistatic SAR imaging are investigated through analytical modeling and numerical simulations. The results indicate that the range resolution is extremely degraded in some cases in forward bistatic SAR imaging. In addition, due to the different imaging projection rules between backward and forward bistatic SAR, the ghost point is produced in the forward imaging. To avoid the above problems, the forward bistatic imaging geometry must be carefully considered. For a given application requirement with the desired imaging performances, the design of the motion parameters can be considered as a question of solving the nonlinear equation system (NES). Then the improved chaos particle swarm optimization (CPSO) is introduced to solve the NES and obtain the optimal solutions. And the simulated imaging results are used to test and verify the effectiveness of CPSO. The results help to deepen understanding of the constraints and properties of bistatic SAR imaging and provide the reference to the optimal design of the motion parameters for a specific requirement, especially in forward bistatic configurations.

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