A Research on SAR Image Enhancement Method for Synthetic Wideband Waveforms and Non-Iterative Super Resolution Technique

DoctorThe main aim of this dissertation is to develop a new super-resolution technique for high quality Synthetic Aperture Radar (SAR) images. Generally, super-resolution techniques can be divided into two types: hardware-based, and image-based. This dissertation develops a super-resolution technique that uses both techniques.To present a comprehensive study of methods of increasing the resolution of SAR images, I first review the fundamentals of SAR that includes a simplified generic SAR system model, a measured echoed signal in various 2-D domains, and an image reconstruction algorithm.Synthetic wideband waveforms (SWWs) were developed due to an interest in alternative technologies for achieving high range resolution. SWWs represent one such technology. Radars that use SWW do not require costly wideband hardware. Instead, high range resolution is attained by transmitting a sequence of narrowband pulses (a "burst"). However, the quality of the SAR images obtained by the conventional SAR processing algorithm was lower than expected when using the synthetic wideband signal. This was because each narrowband subpulse has a different carrier frequency term and therefore needed azimuth compression and a different range cell migration correction (RCMC). As the bandwidth (BW) of the SWW was made wider to achieve higher resolution, the reduction in image quality became more serious. The conventional range Doppler algorithm (RDA) for SWW normally did not consider the effect of this carrier frequency factor when the subpulses were synthesized. Therefore, in this thesis I propose a modified RDA procedure in an attempt to improve the quality of SAR images obtained using SWW. This proposed procedure conducts the range compression with a partial window suitable for each subpulse and then performs azimuth compression and RCMC after considering the carrier frequencies individually. Finally, the spectra of each set of compressed data are combined using the stitching method. In experiments with an automobile-based SAR system, the proposed algorithm is quite accurate in processing the synthetic wideband signals, with a resolution improvement of 20 to 30% compared to the conventional SAR processing algorithm. Moreover, if parallel processing is possible, subpulses can be processed independently and merged to obtain a high quality SAR image much more efficiently than is possible using serial processing.The nonlinear synthetic wideband waveform (NL-SWW) is a variation of SWW that suppresses grating-lobes by varying the step frequency between the pulses and by allowing overlap in the frequency of successive pulses. By concentrating the energy near the center of the frequency band, the grating-lobes as well as the range sidelobes can be controlled by conventional spectral weighting. However, generating a desirable NL-SWW can require a complicated overall system design. Spatial Variant Apodization (SVA) is a variation of the apodization technique that uses different aperture functions depending on the spatial location, and is extremely simple computationally. Super-SVA is an iterative SVA procedureit is one of the most popular super resolution techniques due to its resolution improvement and sidelobe reduction capabilities. However, when this technique is applied to SAR images using a conventional SWW, sidelobes are controlled but the grating-lobes are not eliminated effectively. I proposed an alternate approach which reconstructs NL-SWW using super-SVA in the general SWW data. The approach involves NL-SWW implemented by reconstructing BW expanded subband spectra that is applied super-SVA. I show that the proposed algorithm has much better performance than conventional algorithms and to improve resolution slightly. Also, without recomposing the hardware, it can apply various NL-SWW methods which have been suggested previously.Spectral weighting is the easiest way to reduce the sidelobes in SAR images, but this is achieved at the expense of reducing the mainlobe width. To solve this problem apodization techniques have been suggested. Apodization significantly reduces the sidelobes while retaining a good mainlobe resolution, but has the disadvantage of an excessive computational burden. To overcome this shortcoming of the nonlinear techniques, various super-resolution techniques have been proposed. However these have high computational complexity because they entail iterative calculation. To improve image resolution without requiring iterative calculation, various inverse filtering techniques have been suggested. However, these have a serious problem in extending the BW beyond the chirp signal BW, and some methods have do not reduce sidelobes adequately, and work well only when SAR images have a sufficiently high signal-to-noise ratio (SNR). Therefore, I proposed a modified SVA method to improve SAR resolution. This method adds a modified GMF filter before SVA processing. The proposed filtering method expands the effective BW and improves the resolution while maintaining the sidelobe performance of SVA. This method has low computational complexity due to its non-iterative procedure, which differs from other super-resolution techniques. In the proposed technique, various parameters are flexibly determined based on the SNR. Thus, the proposed method can improve image resolution over a range of SNR, although this improvement decreases as SNR decreases. I tested the proposed method by simulation with point targets and in experiments with real SAR data. The proposed algorithm improved the resolution by about 40% while maintaining SVA’s ability to reduce sidelobes

SAR 시스템 성능변수 최적화를 위한 안테나 빔 패턴 마스크 설계

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Study of Improvement of GMTI Performance Using DPCA and ATI

지상 이동표적 탐지(gorund moving target indicator: GMTI)는 지상의 교통 통제등을 목적으로 하며, 주로 합성 개구면레이다(synthetic aperture radar: SAR) 시스템을 이용하여 짧은 시간에 넓은 지형에 대하여 효율적인 이동표적 탐지를 수행한다. 특히 displaced phase center antenna(DPCA) 방법과 along track interferometry(ATI) 방법을 이용한 이동 표적 탐지는적은 계산량에 의해서 실시간 GMTI에 적합한 탐지방법으로 많이 사용되고 있으나 높은 오경보율을 갖는 한계가 있으며 이를 해결하기 위한 연구가 필요하다. 본 논문에서는 기존의 DPCA 및 ATI의 결합을 이용한 병렬 결합 및 직렬 결합이동 표적 탐지 방법을 제안하고, 제안하는 이동 표적 탐지 방법이 낮은 오경보율의 향상된 탐지성능을 가진 것을 시뮬레이션을 통해 확인하였다. 특히 직렬결합을 이용한 이동 표적 탐지는 기존 DPCA의 오경보율과 비교하여 1/5수준의 오경보율을 가지며, 탐지율도 향상된 것을 볼 수 있다.22Nkc

Efficient Motion Compensation Algorithm for Ground Moving Targets Based on SAR-ATI System

본 논문에서는 지상 이동 표적의 SAR(Synthetic Aperture Radar) 영상 형성 과정에서 표적의 움직임에 의해 발생하는SAR 영상의 왜곡 현상을 보상하는 알고리즘을 제안한다. 일반적인 SAR 영상 형성 알고리즘은 고정 표적과 레이다 플랫폼 사이의 거리 변화를 보상함으로써 왜곡 없는 SAR 영상을 형성하지만, 이동 표적의 경우, 표적의 움직임에 의해 야기된 추가적인 거리 변화가 왜곡된 SAR 영상을 형성한다. 본 논문에서는 지상 이동 표적의 기하학적 위치 및 움직임이SAR 영상에 야기하는 왜곡 현상을 분석하고, SAR-ATI(SAR-Along-Trck Interferometry)와 위상 정렬 기법을 이용해 기 왜곡 현상을 야기하는 표적의 모든 변수들을 추정하는 알고리즘을 제안한다. 최종적으로 본 논문에서는 잡음이 존재하는환경에서 모의시험을 수행해 제안된 기법의 효용성을 증명한다.22Nkc

SAR-ATI를 이용한 효율적인 지상 이동 표적 보상 알고리즘

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DPCA를 이용한 이동 표적 탐지에서 클러터 종류에 따른 성능 비교

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Comparison of GMTI Performance Using DPCA for Various Clutters

합성 개구면 레이다(synthetic aperture radar: SAR) 시스템을 이용한 지상 이동 표적 탐지(ground moving target indicator: GMTI)는 상대적으로 짧은 시간에 넓은 지상 지형에 존재하는 이동 표적을 탐지하여 교통통제 및 군사적 위협에 대한정보를 획득하는 기술이다. Displaced phase center antenna(DPCA) 방법은 실시간 GMTI에 적합한 탐지방법이지만, 측정지역에 따른 클러터 분포의 차이를 고려한 분석이 부족하다. 다양한 지상 클러터의 특징에 적합한 이동 표적 탐지기들의설계를 위해 지상 클러터 지역의 이동 표적 탐지 성능에 대한 분석이 필요하다. 본 논문에서는 기존의 연구된 DPCA 탐지기를 이용한 지상 이동 표적 탐지가 지형에 따라 서로 다른 탐지 성능을 갖는 것을 시뮬레이션을 통해 확인하였다. 특히 도심 지형의 특징을 갖는 이종 및 극성 이종 클러터 지형에서 기존 DPCA 탐지기는 높은 오경보율을 갖고, 자연지형의 동종 클러터 지형에서 낮은 오경보율을 갖는 것을 확인하였다.22Nkc

Improved Moving Target Detector using Sequential Combination of DPCA and ATI

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