202 research outputs found
A Downward-looking Three-dimensional Imaging Method for Airborne FMCW SAR Based on Array Antennas
AbstractWith regard to problems in conventional synthetic aperture radar (SAR), such as imaging distortion, beam limitation and failure in acquiring three-dimensional (3-D) information, a downward-looking 3-D imaging method based on frequency modulated continuous wave (FMCW) and digital beamforming (DBF) technology for airborne SAR is presented in this study. Downward-looking 3-D SAR signal model is established first, followed by introduction of virtual antenna optimization factor and discussion of equivalent-phase-center compensation. Then, compensation method is provided according to reside video phase (RVP) and slope term for FMCW SAR. As multiple receiving antennas are applied to downward-looking 3-D imaging SAR, range cell migration correction (RCMC) turns to be more complex, and corrective measures are proposed. In addition, DBF technology is applied in realizing cross-track resolution. Finally, to validate the proposed method, magnitude of slice, peak sidelobe ratio (PSLR), integrated sidelobe ratio (ISLR) and two-dimensional (2-D) contour plot of impulse response function (IRF) of point target in three dimensions are demonstrated. Satisfactory performances are shown by simulation results
On the Capabilities of the Italian Airborne FMCW AXIS InSAR System
Airborne Synthetic Aperture Radar (SAR) systems are gaining increasing interest within the remote sensing community due to their operational flexibility and observation capabilities. Among these systems, those exploiting the Frequency-Modulated Continuous-Wave (FMCW) technology are compact, lightweight, and comparatively low cost. For these reasons, they are becoming very attractive, since they can be easily mounted onboard ever-smaller and highly flexible aerial platforms, like helicopters or unmanned aerial vehicles (UAVs). In this work, we present the imaging and topographic capabilities of a novel Italian airborne SAR system developed in the frame of cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave S.r.l.). The system, which is named AXIS (standing for Airborne X-band Interferometric SAR), is based on FMCW technology and is equipped with a single-pass interferometric layout. In the work we first provide a description of the AXIS system. Then, we describe the acquisition campaign carried out in April 2018, just after the system completion. Finally, we perform an analysis of the radar data acquired during the campaign, by presenting a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system. The overall analysis aims at providing first reference values for future research and operational activities that will be conducted with this sensor
Motion Estimation and Compensation in Automotive MIMO SAR
With the advent of self-driving vehicles, autonomous driving systems will
have to rely on a vast number of heterogeneous sensors to perform dynamic
perception of the surrounding environment. Synthetic Aperture Radar (SAR)
systems increase the resolution of conventional mass-market radars by
exploiting the vehicle's ego-motion, requiring a very accurate knowledge of the
trajectory, usually not compatible with automotive-grade navigation systems. In
this regard, this paper deals with the analysis, estimation and compensation of
trajectory estimation errors in automotive SAR systems, proposing a complete
residual motion estimation and compensation workflow. We start by defining the
geometry of the acquisition and the basic processing steps of Multiple-Input
Multiple-Output (MIMO) SAR systems. Then, we analytically derive the effects of
typical motion errors in automotive SAR imaging. Based on the derived models,
the procedure is detailed, outlining the guidelines for its practical
implementation. We show the effectiveness of the proposed technique by means of
experimental data gathered by a 77 GHz radar mounted in a forward looking
configuration.Comment: 14 page
Motion Compensation for Near-Range Synthetic Aperture Radar Applications
The work focuses on the analysis of influences of motion errors on near-range SAR applications and design of specific motion measuring and compensation algorithms. First, a novel metric to determine the optimum antenna beamwidth is proposed. Then, a comprehensive investigation of influences of motion errors on the SAR image is provided. On this ground, new algorithms for motion measuring and compensation using low cost inertial measurement units (IMU) are developed and successfully demonstrated
Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems
Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300
GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including
security sensing, industrial packaging, medical imaging, and non-destructive
testing. Traditional methods for perception and imaging are challenged by novel
data-driven algorithms that offer improved resolution, localization, and
detection rates. Over the past decade, deep learning technology has garnered
substantial popularity, particularly in perception and computer vision
applications. Whereas conventional signal processing techniques are more easily
generalized to various applications, hybrid approaches where signal processing
and learning-based algorithms are interleaved pose a promising compromise
between performance and generalizability. Furthermore, such hybrid algorithms
improve model training by leveraging the known characteristics of radio
frequency (RF) waveforms, thus yielding more efficiently trained deep learning
algorithms and offering higher performance than conventional methods. This
dissertation introduces novel hybrid-learning algorithms for improved mmWave
imaging systems applicable to a host of problems in perception and sensing.
Various problem spaces are explored, including static and dynamic gesture
classification; precise hand localization for human computer interaction;
high-resolution near-field mmWave imaging using forward synthetic aperture
radar (SAR); SAR under irregular scanning geometries; mmWave image
super-resolution using deep neural network (DNN) and Vision Transformer (ViT)
architectures; and data-level multiband radar fusion using a novel
hybrid-learning architecture. Furthermore, we introduce several novel
approaches for deep learning model training and dataset synthesis.Comment: PhD Dissertation Submitted to UTD ECE Departmen
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Time Domain SAR Processing with GPUs for Airborne Platforms
A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusettsโ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed with NVIDIAโs CUDA language. An implementation of the Non-Equispaced Fast Fourier Transform (NERFFT) is used to enable efficient and accurate range interpolation as a critical step of the processing. The phase of time- domain processed imagery is dif erent than that of frequency-domain imagery, leading to a potentially different approach to interferometry. This general purpose SAR processor is designed to work with a novel, dual-frequency S- and Ka-band radar system developed at MIRSL as well as the UAVSAR instrument developed by NASAโs Jet Propulsion Laboratory. These instruments represent a wide range of SAR system parameters, ensuring the ability of the processor to work with most any airborne SAR. Results are presented from these two systems, showing good performance of the processor itself
์ค์๊ฐ ๊ทผ๊ฑฐ๋ฆฌ ์์ํ๋ฅผ ์ํ MIMO ์ญํฉ์ฑ ๊ฐ๊ตฌ ๋ ์ด๋ ์์คํ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ ๋ณด๊ณตํ๋ถ, 2022. 8. ๋จ์์ฑ.Microwave and millimeter wave (micro/mmW) imaging systems have advantages over other imaging systems in that they have penetration properties over non-metallic structures and non-ionization. However, these systems are commercially applicable in limited areas. Depending on the quality and size of the images, a system can be expensive and images cannot be provided in real-time. To overcome the challenges of the current micro/mmW imaging system, it is critical to suggest a new system concept and prove its potential benefits and hazards by demonstrating the testbed. This dissertation presents Ku1DMIC, a wide-band micro/mmW imaging system using Ku-band and 1D-MIMO array, which can overcome the challenges above. For cost-effective 3D imaging capabilities, Ku1DMIC uses 1D-MIMO array configuration and inverse synthetic aperture radar (ISAR) technique. At the same time, Ku1DMIC supports real-time data acquisition through a system-level design of a seamless interface with frequency modulated continuous wave (FMCW) radar. To show the feasibility of 3D imaging with Ku1DMIC and its real-time capabilities, an accelerated imaging algorithm, 1D-MIMO-ISAR RSA, is proposed and demonstrated. The detailed contributions of the dissertation are as follows.
First, this dissertation presents Ku1DMIC โ a Ku-band MIMO frequency-modulated continuous-wave (FMCW) radar experimental platform with real-time 2D near-field imaging capabilities. The proposed system uses Ku-band to cover the wider illumination area given the limited number of antennas and uses a fast ramp and wide-band FMCW waveform for rapid radar data acquisition while providing high-resolution images. The key design aspect behind the platform is stability, reconfigurability, and real-time capabilities, which allows investigating the exploration of the systemโs strengths and weaknesses. To satisfy the design aspect, a digitally assisted platform is proposed and realized based on an AMD-Xilinx UltraScale+ Radio Frequency System on Chip (RFSoC). The experimental investigation for real-time 2D imaging has proved the ability of video-rate imaging at around 60 frames per second.
Second, a waveform digital pre-distortion (DPD) method and calibration method are proposed to enhance the image quality. Even if a clean FMCW waveform is generated with the aid of the optimized waveform generator, the signal will inevitably suffer from distortion, especially in the RF subsystem of the platform. In near-field imaging applications, the waveform DPD is not effective at suppressing distortion in wide-band FMCW radar systems. To solve this issue, the LO-DPD architecture and binary search based DPD algorithm are proposed to make the waveform DPD effective in Ku1DMIC. Furthermore, an image-domain optimization correction method is proposed to compensate for the remaining errors that cannot be eliminated by the waveform DPD. For robustness to various unwanted signals such as noise and clutter signals, two regularized least squares problems are applied and compared: the generalized Tikhonov regularization and the total variation (TV) regularization. Through various 2D imaging experiments, it is confirmed that both methods can enhance the image quality by reducing the sidelobe level.
Lastly, the research is conducted to realize real-time 3D imaging by applying the ISAR technique to Ku1DMIC. The realization of real-time 3D imaging using 1D-MIMO array configuration is impactful in that this configuration can significantly reduce the costs of the 3D imaging system and enable imaging of moving objects. To this end, the signal model for the 1D-MIMO-ISAR configuration is presented, and then the 1D-MIMO-ISAR range stacking algorithm (RSA) is proposed to accelerate the imaging reconstruction process. The proposed 1D-MIMO-ISAR RSA can reconstruct images within hundreds of milliseconds while maintaining almost the same image quality as the back-projection algorithm, bringing potential use for real-time 3D imaging. It also describes strategies for setting ROI, considering the real-world situations in which objects enter and exit the field of view, and allocating GPU memory. Extensive simulations and experiments have demonstrated the feasibility and potential benefits of 1D-MIMO-IASR configuration and 1D-MIMO-ISAR RSA.๋ง์ดํฌ๋กํ ๋ฐ ๋ฐ๋ฆฌ๋ฏธํฐํ(micro/mmW) ์์ํ ์์คํ
์ ๋น๊ธ์ ๊ตฌ์กฐ ๋ฐ ๋น์ด์จํ์ ๋นํด ์นจํฌ ํน์ฑ์ด ์๋ค๋ ์ ์์ ๋ค๋ฅธ ์ด๋ฏธ์ง ์์คํ
์ ๋นํด ์ฅ์ ์ด ์๋ค.
๊ทธ๋ฌ๋ ์ด๋ฌํ ์์คํ
์ ์ ํ๋ ์์ญ์์๋ง ์์
์ ์ผ๋ก ์ ์ฉ๋๊ณ ์๋ค. ์ด๋ฏธ์ง์ ํ์ง๊ณผ ํฌ๊ธฐ์ ๋ฐ๋ผ ์์คํ
์ด ๋งค์ฐ ๊ณ ๊ฐ์ผ ์ ์์ผ๋ฉฐ ์ด๋ฏธ์ง๋ฅผ ์ค์๊ฐ์ผ๋ก ์ ๊ณตํ ์ ์๋ ํํฉ์ด๋ค.
ํ์ฌ์ micro/mmW ์ด๋ฏธ์ง ์์คํ
์ ๋ฌธ์ ๋ฅผ ๊ทน๋ณตํ๋ ค๋ฉด ์๋ก์ด ์์คํ
๊ฐ๋
์ ์ ์ํ๊ณ ํ
์คํธ๋ฒ ๋๋ฅผ ์์ฐํ์ฌ ์ ์ฌ์ ์ธ ์ด์ ๊ณผ ์ํ์ ์
์ฆํ๋ ๊ฒ์ด ์ค์ํ๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ Ku-band์ 1D-MIMO ์ด๋ ์ด๋ฅผ ์ด์ฉํ ๊ด๋์ญ micro/mmW ์ด๋ฏธ์ง ์์คํ
์ธ Ku1DMIC๋ฅผ ์ ์ํ์ฌ ์์ ๊ฐ์ ๋ฌธ์ ์ ์ ๊ทน๋ณตํ ์ ์๋ค.
๋น์ฉ ํจ์จ์ ์ธ 3์ฐจ์ ์์ํ ๊ธฐ๋ฅ์ ์ํด Ku1DMIC๋ 1D-MIMO ๋ฐฐ์ด ๊ธฐ์ ๊ณผ ISAR(Inverse Synthetic Aperture Radar) ๊ธฐ์ ์ ์ฌ์ฉํ๋ค.
๋์์ Ku1DMIC๋ ์ฃผํ์ ๋ณ์กฐ ์ฐ์ํ (FMCW) ๋ ์ด๋์์ ์ํํ ์ธํฐํ์ด์ค์ ์์คํ
์์ค ์ค๊ณ๋ฅผ ํตํด ์ค์๊ฐ ๋ฐ์ดํฐ ์์ง์ ์ง์ํ๋ค.
Ku1DMIC๋ฅผ ์ฌ์ฉํ 3์ฐจ์ ์์ํ์ ๊ตฌํ ๋ฐ ์ค์๊ฐ ๊ธฐ๋ฅ์ ๊ฐ๋ฅ์ฑ์ ๋ณด์ฌ์ฃผ๊ธฐ ์ํด, 2์ฐจ์ ์์ํ๋ฅผ ์ํ 1D-MIMO RSA๊ณผ 3์ฐจ์ ์์ํ๋ฅผ ์ํ 1D-MIMO-ISAR RSA๊ฐ ์ ์๋๊ณ Ku1DMIC์์ ๊ตฌํ๋๋ค.
๋ฐ๋ผ์, ๋ณธ ํ์ ๋
ผ๋ฌธ์ ์ฃผ์ ๊ธฐ์ฌ๋ Ku-band 1D-MIMO ๋ฐฐ์ด ๊ธฐ๋ฐ ์์ํ ์์คํ
ํ๋กํ ํ์
์ ๊ฐ๋ฐ ๋ฐ ํ
์คํธํ๊ณ , ISAR ๊ธฐ๋ฐ 3์ฐจ์ ์์ํ ๊ธฐ๋ฅ์ ๊ฒ์ฌํ๊ณ , ์ค์๊ฐ 3์ฐจ์ ์์ํ ๊ฐ๋ฅ์ฑ์ ์กฐ์ฌํ๋ ๊ฒ์ด๋ค.
์ด์ ๋ํ ์ธ๋ถ์ ์ธ ๊ธฐ์ฌ ํญ๋ชฉ์ ๋ค์๊ณผ ๊ฐ๋ค.
์ฒซ์งธ, ์ค์๊ฐ 2D ๊ทผ๊ฑฐ๋ฆฌ์ฅ ์ด๋ฏธ์ง ๊ธฐ๋ฅ์ ๊ฐ์ถ Ku ๋์ญ MIMO ์ฃผํ์ ๋ณ์กฐ ์ฐ์ํ(FMCW) ๋ ์ด๋ ์คํ ํ๋ซํผ์ธ Ku1DMIC๋ฅผ ์ ์ํ๋ค.
์ ์ํ๋ ์์คํ
์ ์ ํ๋ ์์ ์ํ
๋์์ ๋ ๋์ ์กฐ๋ช
์์ญ์ ์ปค๋ฒํ๊ธฐ ์ํด Ku ๋์ญ์ ์ฌ์ฉํ๊ณ ๊ณ ํด์๋ ์ด๋ฏธ์ง๋ฅผ ์ ๊ณตํ๋ฉด์ ๋น ๋ฅธ ๋ ์ด๋ ๋ฐ์ดํฐ ์์ง์ ์ํด ๊ณ ์ ๋จํ ๋ฐ ๊ด๋์ญ FMCW ํํ์ ์ฌ์ฉํ๋ค.
ํ๋ซํผ์ ํต์ฌ ์ค๊ณ ์์น์ ์์ ์ฑ, ์ฌ๊ตฌ์ฑ ๊ฐ๋ฅ์ฑ ๋ฐ ์ค์๊ฐ ๊ธฐ๋ฅ์ผ๋ก ์์คํ
์ ๊ฐ์ ๊ณผ ์ฝ์ ์ ๊ด๋ฒ์ํ๊ฒ ํ์ํ๋ค.
์ค๊ณ ์์น์ ๋ง์กฑ์ํค๊ธฐ ์ํด AMD-Xilinx UltraScale+ RFSoC(Radio Frequency System on Chip)๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋์งํธ ์ง์ ํ๋ซํผ์ ์ ์ํ๊ณ ๊ตฌํํ๋ค.
์ค์๊ฐ 2D ์ด๋ฏธ์ง์ ๋ํ ์คํ์ ์กฐ์ฌ๋ ์ด๋น ์ฝ 60ํ๋ ์์์ ๋น๋์ค ์๋ ์ด๋ฏธ์ง์ ๋ฅ๋ ฅ์ ์
์ฆํ๋ค.
๋์งธ, ์์ ํ์ง ํฅ์์ ์ํ ํํ ๋์งํธ ์ ์น์๊ณก(DPD) ๋ฐฉ๋ฒ๊ณผ ๋ณด์ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค.
์ต์ ํ๋ ํํ ๋ฐ์๊ธฐ์ ๋์์ผ๋ก ๊นจ๋ํ FMCW ํํ์ด ์์ฑ๋๋๋ผ๋ ํนํ ํ๋ซํผ์ RF ํ์ ์์คํ
์์ ์ ํธ๋ ํ์ฐ์ ์ผ๋ก ์๊ณก์ ๊ฒช๊ฒ๋๋ค.
๊ทผ๊ฑฐ๋ฆฌ ์์ํ ์์ฉ ๋ถ์ผ์์๋ ํํ DPD๋ ๊ด๋์ญ FMCW ๋ ์ด๋ ์์คํ
์ ์๊ณก์ ์ต์ ํ๋ ๋ฐ ํจ๊ณผ์ ์ด์ง ์๋ค.
์ด ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํด Ku1DMIC์์ ํํ DPD๊ฐ ์ ํจํ๋๋ก LO-DPD ์ํคํ
์ฒ์ ์ด์ง ํ์ ๊ธฐ๋ฐ DPD ์๊ณ ๋ฆฌ์ฆ์ ์ ์ํ๋ค.
๋ํ, ํํ DPD๋ก ์ ๊ฑฐํ ์ ์๋ ๋๋จธ์ง ์ค๋ฅ๋ฅผ ๋ณด์ํ๊ธฐ ์ํด ์ด๋ฏธ์ง ์์ญ ์ต์ ํ ๋ณด์ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค.
๋
ธ์ด์ฆ ๋ฐ ํด๋ฌํฐ ์ ํธ์ ๊ฐ์ ๋ค์ํ ์์น ์๋ ์ ํธ์ ๋ํ ๊ฒฌ๊ณ ์ฑ์ ์ํด ์ผ๋ฐํ๋ Tikhonov ์ ๊ทํ ๋ฐ ์ ์ฒด ๋ณ๋(TV) ์ ๊ทํ๋ผ๋ ๋ ๊ฐ์ง ์ ๊ทํ๋ ์ต์ ์์น ๋ฌธ์ ๋ฅผ ์ ์ฉ ํ ๋น๊ตํ๋ค.
๋ค์ํ 2์ฐจ์ ์์ํ ์คํ์ ํตํด ๋ ๋ฐฉ๋ฒ ๋ชจ๋ ๋ถ์ฝ ๋ ๋ฒจ์ ์ค์ฌ ํ์ง์ ํฅ์์ํฌ ์ ์์์ ํ์ธํ๋ค.
๋ง์ง๋ง์ผ๋ก, ISAR ๊ธฐ๋ฒ์ 2์ฐจ์ ์์ ํ๋ซํผ์ ์ ์ฉํ์ฌ ์ค์๊ฐ 3์ฐจ์ ์์์ ๊ตฌํํ๊ธฐ ์ํ ์ฐ๊ตฌ๋ฅผ ์งํํ๋ค.
1D-MIMO-ISAR ๊ตฌ์ฑ์์ ์ค์๊ฐ 3D ์ด๋ฏธ์ง์ ๊ตฌํ์ ์ด๋ฌํ ๊ตฌ์ฑ์ด 3D ์ด๋ฏธ์ง ์์คํ
์ ๋น์ฉ์ ํฌ๊ฒ ์ค์ผ ์ ์๋ค๋ ์ ์์ ์ํฅ๋ ฅ์ด ์๋ค.
๋ฐ๋ผ์ ์ด ๋
ผ๋ฌธ์์๋ 1D-MIMO-ISAR ๊ตฌ์ฑ์ ๋ํ ์ด๋ฏธ์ง ์ฌ๊ตฌ์ฑ์ ๊ฐ์ํํ๊ธฐ ์ํด 1D-MIMO-ISAR ๋ฒ์ ์คํํน ์๊ณ ๋ฆฌ์ฆ(RSA)์ ์ ์ํ๋ค.
์ ์๋ 1D-MIMO-ISAR RSA๋ ๋๋ฆฌ ์๋ ค์ง Back-Projection ์๊ณ ๋ฆฌ์ฆ๊ณผ ๊ฑฐ์ ๋์ผํ ์ด๋ฏธ์ง ํ์ง์ ์ ์งํ๋ฉด์๋ ์๋ฐฑ ๋ฐ๋ฆฌ์ด ์ด๋ด์ ์ด๋ฏธ์ง๋ฅผ ์ฌ๊ตฌ์ฑํจ์ผ๋ก์จ ์ค์๊ฐ ์์ํ์ ๋ํ ๊ฐ๋ฅ์ฑ์ ๋ณด์ฌ์ค๋ค.
๋ํ ๋ฌผ์ฒด๊ฐ ์์ผ์ ๋ค์ด์ค๊ณ ๋๊ฐ๋ ์ค์ ์ํฉ์ ๊ณ ๋ คํ๊ธฐ ์ํ ROI ์ค์ , ๊ทธ๋ฆฌ๊ณ ๋ฉ๋ชจ๋ฆฌ ํ ๋น์ ๋ํ ์ ๋ต์ ์ค๋ช
ํ๋ค.
๊ด๋ฒ์ํ ์๋ฎฌ๋ ์ด์
๊ณผ ์คํ์ ํตํด 1D-MIMO-IASR ๊ตฌ์ฑ ๋ฐ 1D-MIMO-ISAR RSA์ ๊ฐ๋ฅ์ฑ๊ณผ ์ ์ฌ์ ์ด์ ์ ํ์ธํ๋ค.1 INTRODUCTION 1
1.1 Microwave and millimeter-wave imaging 1
1.2 Imaging with radar system 2
1.3 Challenges and motivation 5
1.4 Outline of the dissertation 8
2 FUNDAMENTAL OF TWO-DIMENSIONAL IMAGING USING A MIMO RADAR 9
2.1 Signal model 9
2.2 Consideration of waveform 12
2.3 Image reconstruction algorithm 16
2.3.1 Back-projection algorithm 16
2.3.2 1D-MIMO range-migration algorithm 20
2.3.3 1D-MIMO range stacking algorithm 27
2.4 Sampling criteria and resolution 31
2.5 Simulation results 36
3 MIMO-FMCW RADAR IMPLEMENTATION WITH 16 TX - 16 RX ONE- DIMENSIONAL ARRAYS 46
3.1 Wide-band FMCW waveform generator architecture 46
3.2 Overall system architecture 48
3.3 Antenna and RF transceiver module 53
3.4 Wide-band FMCW waveform generator 55
3.5 FPGA-based digital hardware design 63
3.6 System integration and software design 71
3.7 Testing and measurement 75
3.7.1 Chirp waveform measurement 75
3.7.2 Range profile measurement 77
3.7.3 2-D imaging test 79
4 METHODS OF IMAGE QUALITY ENHANCEMENT 84
4.1 Signal model 84
4.2 Digital pre-distortion of chirp signal 86
4.2.1 Proposed DPD hardware system 86
4.2.2 Proposed DPD algorithm 88
4.2.3 Measurement results 90
4.3 Robust calibration method for signal distortion 97
4.3.1 Signal model 98
4.3.2 Problem formulation 99
4.3.3 Measurement results 105
5 THREE-DIMENSIONAL IMAGING USING 1-D ARRAY SYSTEM AND ISAR TECHNIQUE 110
5.1 Formulation for 1D-MIMO-ISAR RSA 111
5.2 Algorithm implementation 114
5.3 Simulation results 120
5.4 Experimental results 122
6 CONCLUSIONS AND FUTURE WORK 127
6.1 Conclusions 127
6.2 Future work 129
6.2.1 Effects of antenna polarization in the Ku-band 129
6.2.2 Forward-looking near-field ISAR configuration 130
6.2.3 Estimation of the movement errors in ISAR configuration 131
Abstract (In Korean) 145
Acknowlegement 148๋ฐ
An analysis of chosen image formation algorithms for synthetic aperture radar with FMCW
The modelling of FMCW SAR systems, due to long signal duration time, commonly used start-stop approximation for pulsed radars causes errors in the image. Continuous motion of the radar platform results in additional range-azimuth couplings and range walk term that should be considered in processing of signal from this type of radar. The paper presents an analysis of the following algorithms: Time Domain Correlation (TDC), Range Doppler Algorithm (RDA), and Range Migration Algorithm (RMA). The comparison of the algorithms is based on theoretical estimation of their computation complexity and the quality of images obtained on the basis of real signals of FMCW SAR systems
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