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Signal processing for MIMO radar system : synchronization, detection and imaging

Signal processing for MIMO radar system : synchronization, detection and imaging

Material type
학위논문
Personal Author
여광구 呂光九
Title Statement
Signal processing for MIMO radar system : synchronization, detection and imaging / Kwanggoo Yeo
Publication, Distribution, etc
Seoul :   Graduate School, Korea Unversity,   2019  
Physical Medium
vii, 97장 : 천연색삽화, 도표 ; 26 cm
기타형태 저록
Signal Processing for MIMO Radar System: Synchronization, Detection and Imaging   (DCOLL211009)000000083185  
학위논문주기
학위논문(박사)-- 고려대학교 대학원: 컴퓨터·전파통신공학과, 2019. 2
학과코드
0510   6YD36   350  
General Note
지도교수: 정원주  
부록수록  
Bibliography, Etc. Note
참고문헌: 장 91-95
이용가능한 다른형태자료
PDF 파일로도 이용가능;   Requires PDF file reader(application/pdf)  
비통제주제어
레이다, 신호처리,,
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001 000045978866
005 20190531110310
007 ta
008 181227s2019 ulkad bmAC 000c eng
040 ▼a 211009 ▼c 211009 ▼d 211009
085 0 ▼a 0510 ▼2 KDCP
090 ▼a 0510 ▼b 6YD36 ▼c 350
100 1 ▼a 여광구 ▼g 呂光九
245 1 0 ▼a Signal processing for MIMO radar system : ▼b synchronization, detection and imaging / ▼d Kwanggoo Yeo
246 1 1 ▼a MIMO 레이다 시스템을 위한 신호처리 기법 연구 : ▼b 동기, 탐지 및 이미징
260 ▼a Seoul : ▼b Graduate School, Korea Unversity, ▼c 2019
300 ▼a vii, 97장 : ▼b 천연색삽화, 도표 ; ▼c 26 cm
500 ▼a 지도교수: 정원주
500 ▼a 부록수록
502 1 ▼a 학위논문(박사)-- ▼b 고려대학교 대학원: ▼c 컴퓨터·전파통신공학과, ▼d 2019. 2
504 ▼a 참고문헌: 장 91-95
530 ▼a PDF 파일로도 이용가능; ▼c Requires PDF file reader(application/pdf)
653 ▼a 레이다 ▼a 신호처리
776 0 ▼t Signal Processing for MIMO Radar System: Synchronization, Detection and Imaging ▼w (DCOLL211009)000000083185
900 1 0 ▼a Yeo, Kwang-goo, ▼e
900 1 0 ▼a 정원주 ▼g 鄭原周, ▼e 지도교수
945 ▼a KLPA

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Signal processing for MIMO radar system : synchronization, detection and imaging (68회 열람)
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No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Stacks(Thesis)/ Call Number 0510 6YD36 350 Accession No. 123060829 Availability Available Due Date Make a Reservation Service B M
No. 2 Location Science & Engineering Library/Stacks(Thesis)/ Call Number 0510 6YD36 350 Accession No. 123060830 Availability Available Due Date Make a Reservation Service B M
No. 3 Location Sejong Academic Information Center/Thesis(5F)/ Call Number 0510 6YD36 350 Accession No. 153081454 Availability Available Due Date Make a Reservation Service M
No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Stacks(Thesis)/ Call Number 0510 6YD36 350 Accession No. 123060829 Availability Available Due Date Make a Reservation Service B M
No. 2 Location Science & Engineering Library/Stacks(Thesis)/ Call Number 0510 6YD36 350 Accession No. 123060830 Availability Available Due Date Make a Reservation Service B M
No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Sejong Academic Information Center/Thesis(5F)/ Call Number 0510 6YD36 350 Accession No. 153081454 Availability Available Due Date Make a Reservation Service M

Contents information

Abstract

Multiple-input multiple-output (MIMO) radar system uses multiple antennas to transmit and receive signals. MIMO radar system has two kinds of diversities: One is waveform diversity achieved by transmitting orthogonal or incoherent waveforms and the other is spatial diversity obtained by multistatic structure, in which multiple well-separated antenna arrays are presented as the transmitter or the receiver. Provided that synchronization for all antenna arrays is established, MIMO radar enables to achieve enhanced performance in detection, parameter identifiability, image resolution, and jamming suppression. In this dissertation, we consider signal processing issues of synchronization, detection, and imaging in MIMO radar systems.
In the first part of this dissertation, we propose a novel phase synchronization algorithm for coherent MIMO radar system (chapter 2). By exchanging two kinds of phase information which are the phase change in the forward and reverse direction between radar elements and the compensated sync phase for the phase change, the proposed algorithm is able to synchronize local oscillator phases among radar elements even if line-of-sight communication links are not possible. In the second part of this dissertation, we introduce a computationally efficient algorithm for estimating the DOD and DOA of targets in the presence of jamming signals for bistatic MIMO radar system (chapter 3). By exploiting properly designed projection filter, exhaustive two-dimensional angle search is replaced with several one-dimensional angle search algorithms and the jamming signals are discriminated regardless of its strength. Finally, we present a novel method to reconstruct the azimuth Doppler spectrum for the multichannel SAR system at highly nonuniform sampling (chapter 4). Averaging time samples and (weighted) least norm principle enable to mitigate large noise enhancement and exhibit low ambiguity power in the reconstructed azimuth spectrum.

Table of Contents

1 Introduction 1
 1.1 Brief review of MIMO radar 1
  1.1.1 MIMO radar: Colocated / Widely Separated 2
  1.1.2 Monostatic, Bistatic and Multistatic  3
 1.2 DOA Estimation 5
  1.2.1 Signal Model 5
  1.2.2 DOA Estimation Algorithms 8
 1.3 Synthetic Aperture Radar 11
  1.3.1 Geometry of SAR 11
  1.3.2 SAR Signal Model 13
  1.3.3 Ambiguity Issue for PRF 14
  1.3.4 Multichannel SAR 16
 1.4 Dissertation Outline 18
2 Phase Synchronization for coherent MIMO radar 20
 2.1 Introduction 21
 2.2 Signal Model and Previous Work on Phase Synchronization 23
  2.2.1 System Model 23
  2.2.2 Previous Work  25
 2.3 Proposed Algorithm 29
  2.3.1 Analysis of the phase synchronization error 33
 2.4 Simulation Results 35
 2.5 Conclusion 39
3 DOD-DOA Estimation in Bistatic MIMO radar 40
 3.1 Introduction  41
 3.2 Signal Model and Problem Setting 43
 3.3 Proposed Method 50
  3.3.1 Estimation of DOAs 51
  3.3.2 Projection Filtering 52
  3.3.3 Estimation of DOD 55
  3.3.4 Targets with common 1-D angles 57
 3.4 Computational Complexity 58
 3.5 Simulation Results 60
 3.6 Conclusion 68
4 Azimuth Spectrum Reconstruction for Multichannel SAR system 69
 4.1 Introduction 70
 4.2 Signal Model and Problem Settings 72
 4.3 Proposed Method 75
  4.3.1 Averaging highly nonuniform samples 75
  4.3.2 Least norm Approach 77
  4.3.3 Weighted least norm Approach 79
 4.4 Simulation Results 81
 4.5 Conclusion 84
 4.6 Appendix 85
  4.6.1 Solution for weighted least norm 85
  4.6.2 Weighting setting for the proposed method 86
  4.6.3 Analysis for pseudo inversion method 87
5 Conclusion 89
 5.1 Summary 89
Bibliography 91