車載雷達(dá)可全天時(shí)全天候工作,是自動(dòng)駕駛、智能無人系統(tǒng)的重要傳感器,然而車載雷達(dá)的距離和速度測量精度較低,成為制約其應(yīng)用效能的技術(shù)瓶頸。針對該問題,本論文分別從設(shè)計(jì)性能更優(yōu)的信號(hào)處理及參數(shù)估計(jì)算法,以及融合雷達(dá)和光學(xué)視頻測量結(jié)果兩個(gè)方面開展研究,具體工作包括:(1)考慮OFDM信號(hào)體制,通過分析OFDM多載波回波模型,提出了改進(jìn)的FFT算法和最大似然估計(jì)算法,通過充分利用多載頻測量結(jié)果提高速度測量精度,并進(jìn)?步給出了距離和速度估計(jì)的Cramer-Rao下界;(2)針對光學(xué)視頻圖像,研究了基于CNN模型的運(yùn)動(dòng)目標(biāo)檢測和位置速度估計(jì)算法,并在此基礎(chǔ)之上研究了視頻圖像測量結(jié)果與雷達(dá)測量結(jié)果的關(guān)聯(lián),為融合處理提升測量精度奠定基礎(chǔ)。論文方法經(jīng)過仿真和MR3003雷達(dá)實(shí)際同步采集的雷達(dá)和視頻數(shù)據(jù)進(jìn)行了驗(yàn)證。

【文章頁數(shù)】：80 頁

【學(xué)位級別】：碩士

【文章目錄】：
ABSTRACT
摘要
Abbreviations
Chapter 1:Introduction
    1.1 Motivation
    1.2 Background and Literature Review
    1.3 Thesis Organization
Chapter 2:Vehicle Radar
    2.1 Radar Signals
        2.1.1 Constant Frequency Pulses
        2.1.2 Linear Frequency Modulation Pulses
        2.1.3 FMCW Radar Signal
    2.2 FMCW Vehicle Radar(MR-3003-RD)
        2.2.1 Key Features
        2.2.2 Range neighbor delta(PRND)
        2.2.3 Speed neighbor delta(PSND)
    2.3 Application of MR3003-RD
    2.4 Problem Statement
    2.5 Summary
Chapter 3:Estimation methods for accurate Velocity Estimation
    3.1 OFDM Signal
    3.2 Conventional Algorithm for Parameter Estimation
        3.2.1 Range Resolution
        3.2.2 Doppler Resolution
    3.3 Improved Doppler estimation by Extended FFT method
        3.3.1 Symbol Constraints
    3.4 The real Data Experimentations with MR3003 radar
    3.5 Doppler Estimation by Maximum Likelihood Estimation
        3.5.1 Cramer Rao Lower Bound
    3.6 Summary
Chapter 4:Association of Radar Measurements and Video Tracking
    4.1 Vehicle Detection
        4.1.1 Data Set
        4.1.2 Convolutional Neural Network(CNN)
    4.2 Association of Radar Measurements and Optical Measurements
    4.3 Summary
Conclusion
    Future Work and Recommendations
References
Acknowledgement
Publications



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