Principle Of Synthetic Aperture Radar Research Articles

Long-baseline multistatic and bistatic SAR products: Application to the RODiO mission

In-Orbit Demonstration (IOD) missions represent flight opportunities to acquire data on spacecraft and space environment and to demonstrate new techniques at system, subsystem, and payload level. Realizing this type of mission means accepting a greater level of risk. However, when very compact and relatively simple platforms like CubeSats are adopted, this becomes admissible since costs can be kept low. Distributed Synthetic Aperture Radar (SAR) is a novel Earth Observation (EO) technique for microwave imaging. It uses multiple cooperating receivers and suitable processing to enable performance and products that exceed those of the single components of the system. RODiO (Radar for earth Observation by synthetic aperture Distributed on a cluster of CubeSats equipped with high-technology micro-propellers for new Operative services) is an IOD of the distributed SAR concept. The mission is based on four, 16 U, CubeSats, that embark a receiving-only X-band SAR instrument able to collect bistatic echoes exploiting a monostatic SAR as an opportunity illuminator, i.e PLATiNO-1 mission. Distributed SAR demonstration is thus pursued in RODiO combining the principles of both multistatic and bistatic SAR. The paper, moving from mission goals, individuates different families of EO products that RODiO can demonstrate, e.g. in the contest of ground motion, digital elevation models, and ship detection. The main result is the definition of the RODiO system requirements for product generation that drive satellites and payload design.

Optimal Sensing Principle of Synthetic Aperture Radar

Optimal Sensing Principle of Synthetic Aperture Radar

Study on processing synthetic aperture radar data based on an optical 4f system for fast imaging.

Due to the huge amount of collected echo data caused by the working principle of synthetic aperture radar (SAR), the use of digital processing relies heavily on the performance of digital chips. Because of the limitation of Moore's law, the technology of digital signal processing exposes the limitation of computing speed and power consumption in the face of SAR processing. Against this background, the optical processing method based on the optical 4f system is introduced into SAR imaging. A spatial light modulator (SLM) is placed on the input surface and spectrum surface of the 4f system to load the echo data of the SAR and the matched filter function of the SAR. Using optical Fourier transform to realize the core calculation of SAR data processing can solve the difficulty of processing time-consuming due to the large amount of calculation. In the process of Fourier transform, instead of using a solid glass lens, we use a phase-type Fresnel lens diagram in the SLM to realize the function of Fourier, which avoids the need for special design of Fourier lens. It also greatly reduces the volume and weight of the whole machine, which provides a reference method for real-time imaging of spaceborne SAR.

Radiometric Principle-Based Radiometric Normalization Method for SAR Images Mosaic

Radiometric normalization minimizes the radiometric inconsistencies between images in synthetic aperture radar (SAR) images mosaic. However, the radiometric principle of SAR have not been fully considered by the existing methods. To this issue, a radiometric principle-based radiometric normalization method is proposed. First, image areas with consistent coverage areas in object space and approximate rough ground surface between images are extracted as adjustment candidates based on imaging principle. Then, considering the radiometric characteristic of SAR image, all images are taken as a whole to solve the radiometric adjustment model, which transfers radiometric normalization into the least square optimization. Finally, a global quantization strategy is used to ensure radiometric consistency during orthorectification and mosaicking. The experimental results of Gaofen-3 SAR images demonstrate that the proposed method has the best performance, and can effectively and stably eliminate the radiometric differences between images.

A Panoramic Synthetic Aperture Radar

This paper proposes a new synthetic aperture radar (SAR), named as panoramic SAR, based on a combination of linear and rotational SARs, by which a large 360-degree panoramic view of the observed scene can be reconstructed. Firstly, the system geometry and its imaging process based on the back-projection algorithm (BPA) are presented. The combined movement constitutes a two-dimensional synthetic aperture and thus higher imaging resolutions can be obtained. The corresponding resolution analysis and the sampling criteria are discussed accordingly. Then, a novel dynamic piecewise compensation (DPC) algorithm, a recursive imaging process, is proposed to reduce the processing complexity significantly. The imaging implementation and the complexity are also studied respectively. Finally, a prototype of panoramic SAR is built based on an frequency modulated continuous wave (FMCW) radar and a moving platform, and the simulation and experimental results are provided to validate the proposed panoramic SAR principle and the DPC algorithm.

Lightweight 2D Imaging for Integrated Imaging and Communication Applications

While integrated sensing and communication has attracted great attention, integrated imaging and communication is still largely open. Microwave, millimeter-wave, and tera-Hz imaging needs to sample a huge number of antenna positions and is thus too complex and costly to mobile communication devices. To address this challenge, we propose a Lightweight Imaging Algorithm (LIA) to reduce the complexity of both imaging hardware and computation. Based on the synthetic aperture radar principle, LIA uses the iterative matrix inversion lemma to estimate image pixels efficiently. Simulations with both simulated and real-world data verified that LIA had superior performance. The algorithm is promising to compact handheld and mobile devices in integrated imaging and communication applications.

A Blast Furnace Burden Surface Deeplearning Detection System Based on Radar Spectrum Restructured by Entropy Weight

Accurately capturing the burden surface information of a blast furnace (BF) is helpful to adjust the burden distribution matrix and improve the gas flow distribution, which is essential in the steel smelting industry. However, it is difficult to detect the burden surface because of the high temperature, high pressure, high dust and flame combustion environment condition inside the BF, in addition to the fluidization characteristics of the burden surface. With the fusion of high-temperature metallurgy, radar detection and image processing, a new BF surface deep-learning detection system based on energy weight was developed in this study to visualize the smelting status of a BF and digitize the information of the burden surface. First, the original burden surface echo spectrogram was captured using a frequency-modulated continuous wave radar with a high-temperature-resistant sensor. Second, the point cloud distribution map was constructed based on the principle of synthetic aperture radar (SAR) imaging. The coordinate transformation and matrix compensation were completed by the entropy weight method and Gamma correction to convert point cloud map to the burden surface grayscale image, constructing datasets for the network. Third, with a 3rd-order hourglass feature extraction network, a BF surface detection network based on the principle of YOLOv3 was designed and trained to predict the position of the burden surface in the grayscale image and track the changing trend of the burden line. The proposed method, which is tested on two steel plant datasets, achieved an average prediction precision of 99.74%. Finally, compared with the traditional burden line extraction algorithm, burden line oscillations and local outliers can be avoided by the proposed method. The continuous detection of the BF surface information was realized.

Extraction of Blast Furnace Burden Line Based on Radar Spectrum Restructured by Entropy Weight

Hostile environment inside blast furnace (BF) and nonuniform fluidization characteristics of burden surface bring challenges to the extraction of burden line, which is an important factor affecting the smelting efficiency. In this study, based on the imaging principle of Synthetic Aperture Radar (SAR), a mechanical swing radar was designed to capture the high-density radar echo signals. By analyzing the characteristics of radar spectrum, the entropy weight method was used to complete the coordinate transformation from the nonuniform coordinate point cloud map to the grayscale image in real space to visualize the smelting states. Then, the burden surface features were enhanced by gamma correction, and the adaptive threshold segmentation was used to extract the surface transitional belt in the image. Finally, the burden line points were extracted by the energy centrobaric correction method to fit the burden line. Compared with traditional algorithm, experiments on industrial data indicate its feasibility and effectiveness.

Synthetic Aperture Radar Image Speckle Noise Suppression and Mine Target Detection

Synthetic Aperture Radar (SAR) provides a comprehensive, all-weather target monitoring function and is widely used in the military and industrial fields of defense. This article mainly studies a landmine target detection technology based on synthetic aperture radar image processing, shallow buried mines. The detection and identification of military radar has important military significance, which can reduce the casualties caused by landmine explosions. This article first introduces the basic imaging principle of synthetic aperture radar, then introduces the noise processing of SAR images based on the Gamma filter, and finally targets the targets of mine SAR images Features were identified and analyzed.

Dark Spot Detection in SAR Images of Oil Spill Using Segnet

Damping Bragg scattering from the ocean surface is the basic underlying principle of synthetic aperture radar (SAR) oil slick detection, and they produce dark spots on SAR images. Dark spot detection is the first step in oil spill detection, which affects the accuracy of oil spill detection. However, some natural phenomena (such as waves, ocean currents, and low wind belts, as well as human factors) may change the backscatter intensity on the surface of the sea, resulting in uneven intensity, high noise, and blurred boundaries of oil slicks or lookalikes. In this paper, Segnet is used as a semantic segmentation model to detect dark spots in oil spill areas. The proposed method is applied to a data set of 4200 from five original SAR images of an oil spill. The effectiveness of the method is demonstrated through the comparison with fully convolutional networks (FCN), an initiator of semantic segmentation models, and some other segmentation methods. It is here observed that the proposed method can not only accurately identify the dark spots in SAR images, but also show a higher robustness under high noise and fuzzy boundary conditions.

Spatial Channel Sounding Based on Bistatic Synthetic Aperture Radar Principles

In this paper, we propose a simplified spatial channel sounding method by utilizing bistatic synthetic aperture radar (BiSAR) principles. Despite the different deployment geometries compared with a conventional BiSAR system, the feasibility of the approach is established by 1) the proposed method achieves a better spatial resolution than conventional directional channel sounders and 2) reconstruction algorithms based on time-domain back-projection in conjunction with a digital elevation model provide a good imaging performance and are suitable for reconstructing the spatial distribution of scatterers. Simulations of a high-speed rail (HSR) scenario demonstrate that the estimated power delay profiles (PDPs) and power angle profiles (PAPs) are close to the actual values.

Efficient Evaluation of Multichannel SAR Data Recombination Filters

Synthetic aperture radar (SAR) is a well-established technique for observing the Earth on a global scale. As applications become more demanding, it is desirable to overcome the limitations imposed by the SAR principle, one of which is the tradeoff between the swath width and the instantaneous azimuth bandwidth, determining the resolution. Recombination of multiple channels with displaced phase centers has been proposed as a convenient way to create high resolution wide-swath images. We analyze various approximations made in the channel transfer functions and their impact on the reconstruction result using examples inspired by current imaging modes of the TerraSAR-X and TanDEM-X missions. In order to do so, we introduce an efficient method to assess the quality of reconstruction filters for an arbitrary number of channels without the need of full time-domain simulations.

Indoor Operations by FMCW Millimeter Wave SAR Onboard Small UAS: A Simulation Approach

A dedicated system simulator is presented in this paper for indoor operations onboard small Unmanned Aerial Systems (UAS) by a novel millimeter wave radar sensor. The sensor relies on the principle of Synthetic Aperture Radar (SAR) applied to a Frequency Modulated Continuous Wave (FMCW) radar system. Input to the simulator are both design parameters for Synthetic Aperture Radar (SAR), which should be able to cope with the stringent requirements set by indoor operations, and information about platform navigation and observed scene. The scene generation task is described in detail. This is based on models for point target response on either a completely absorbing background or fluctuating background and ray tracing (RT) techniques. Results obtained from scene processing are finally discussed, giving further insights on expected results from high-resolution observation of an assigned control volume by this novel SAR sensor.

The Characteristics of the Multipath Scattering and the Application for Geometry Extraction in High-Resolution SAR Images

Due to the special principle of synthetic aperture radar (SAR), SAR images exhibit many special phenomena. This becomes more obvious on high-resolution (HR) SAR images, as much more details are contained. We firmly believe that these details are where the advantages of a SAR image lie on and they provide some key clues for building the framework to understand SAR images. It comes to our attention that many special details in SAR images are due to the mechanism of multipath (MP) scattering. Dominated by the synthetic aperture progress, MP scattering reveals many interesting properties in SAR images. In this paper, we first analyze the mechanism of MP scattering by using the ray perspective on typical structure units. The main characteristics of the MP scattering in the SAR image are presented, such as the offset, prolong, segment, and blurring. Then, the analysis is extended to typical structures with MP scattering, such as bridges, buildings, and oil tanks by using Terra-SAR images. Finally, we explore the utilization of characteristics of MP scattering on geometry extraction from HR SAR images. The results prove the validity and the precision of our analysis. Some advices are also provided on the applications of the characteristics of the MP scattering in the SAR image. It is expected that this paper is helpful for the SAR image understanding and application.

MIMO SAR Using Orthogonal Coding: Design, Performance Analysis, and Verifications

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is a promising technology in radar imaging which provides a better balance of azimuth resolution and swath width compared with traditional single-input single-output (SISO) SAR. It has the potential to help scientists and engineers to design ambitious SAR system with higher resolution and wider swath. This paper studies the principle of MIMO SAR using orthogonal coding waveform and then provides the performance analysis in resolution and swath width. By using orthogonal coding waveform, lower channel interference is obtained, which makes MIMO SAR achieve wider unambiguous range swath and lower azimuth ambiguity. Simulations are carried out by means of the system parameters of real spaceborne SAR platform. A ground-based MIMO SAR imaging system with up and down chirp modulation is also designed. The performances of MIMO SAR and SISO SAR are compared, and the validity and advantage of MIMO SAR are verified.

A tutorial on synthetic aperture radar

Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring, 2-D and 3-D mapping, change detection, 4-D mapping (space and time), security-related applications up to planetary exploration. With the advances in radar technology and geo/bio-physical parameter inversion modeling in the 90s, using data from several airborne and spaceborne systems, a paradigm shift occurred from the development driven by the technology push to the user demand pull. Today, more than 15 spaceborne SAR systems are being operated for innumerous applications. This paper provides first a tutorial about the SAR principles and theory, followed by an overview of established techniques like polarimetry, interferometry and differential interferometry as well as of emerging techniques (e.g., polarimetric SAR interferometry, tomography and holographic tomography). Several application examples including the associated parameter inversion modeling are provided for each case. The paper also describes innovative technologies and concepts like digital beamforming, Multiple-Input Multiple-Output (MIMO) and bi- and multi-static configurations which are suitable means to fulfill the increasing user requirements. The paper concludes with a vision for SAR remote sensing.

Interferometric Synthetic Aperture Microscopy: Microscopic Laser Radar

Using instruments from optical coherence tomography and the principles of synthetic aperture radar, researchers have developed a new method for reconstructing 3-D optical images. Doctors may soon be able to use this approach as a noninvasive diagnostic tool in clinical settings.

GEOMETRIC ANALYSIS OF SINGLE SAR REMOTE SENSING IMAGE POSITIONING

The iterative positioning method(IPM) based on digital elevation model(DEM) is an important way in object positioning or map revision with single remote sensing image.The geometry principle of synthetic aperture radar(SAR)-IPM has not been clear so far.In this study,the iterative calculation process of SAR-IPM was analyzed by using geometry theory based on distant projection of SAR image.Two known variables,slope obliquity and incidence angle of initial position,were chosen to derive the approximate convergence criterion and the convergence speed function.It is found that slope obliquity and incidence angle are leading factors for the convergence and convergence speed of SAR-IPM.Experiment results with simulated data and real data have proved that the approximate convergence criterion is accurate and reasonable,and the convergence speed function is correct.The result will help to analyze the geometry relation between the SAR image point and the corresponding ground point.

AN INTRODUCTION TO SYNTHETIC APERTURE RADAR (SAR)

This paper outlines basic principle of Synthetic Aperture Radar (SAR). Matched filter approaches for processing the received data and pulse compression technique are presented. Besides the SAR radar equation, the linear frequency modulation (LFM) waveform and matched filter response are also discussed. Finally the system design consideration of various parameters and aspects are also highlighted.

The Synthetic Aperture Microscope

It is well known that the resolution of a microscope depends critically on the aperture of its objective lens. Achieving wide apertures requires the lens to be extremely close to the sample being imaged, which is often inconvenient. We describe an optical microscope, currently in breadboard form, that achieves a large aperture, and thus high resolution, with a large (theoretically unlimited) working distance, based on the principles of synthetic aperture radar (SAR).