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面向自動駕駛的車輛精確實時定位算法

沈連豐,  張瑞,  朱亞萍,  吳怡

沈連豐, 張瑞, 朱亞萍, 吳怡. 面向自動駕駛的車輛精確實時定位算法[J]. 電子與信息學(xué)報, 2020, 42(1): 28-35. doi: 10.11999/JEIT190610
引用本文: 沈連豐, 張瑞, 朱亞萍, 吳怡. 面向自動駕駛的車輛精確實時定位算法[J]. 電子與信息學(xué)報, 2020, 42(1): 28-35. doi: 10.11999/JEIT190610
Lianfeng SHEN, Rui ZHANG, Yaping ZHU, Yi WU. High-precision and Real-time Localization Algorithm for Automatic Driving Vehicles[J]. Journal of Electronics & Information Technology, 2020, 42(1): 28-35. doi: 10.11999/JEIT190610
Citation: Lianfeng SHEN, Rui ZHANG, Yaping ZHU, Yi WU. High-precision and Real-time Localization Algorithm for Automatic Driving Vehicles[J]. Journal of Electronics & Information Technology, 2020, 42(1): 28-35. doi: 10.11999/JEIT190610

面向自動駕駛的車輛精確實時定位算法

doi: 10.11999/JEIT190610 cstr: 32379.14.JEIT190610
  • 1.

    東南大學(xué)移動通信國家重點(diǎn)實驗室 南京 210096

  • 2.

    福建師范大學(xué)光電與信息工程學(xué)院 福州 350007

基金項目: 國家自然科學(xué)基金(61601122, 61741102, U180526, 61571128)
詳細(xì)信息
    作者簡介:

    沈連豐：男，1952年生，教授，主要研究方向為寬帶移動通信、泛在網(wǎng)絡(luò)和車輛自組織網(wǎng)絡(luò)等

    張瑞：男，1986年生，博士生，研究方向為短距無線通信、車輛自組織網(wǎng)絡(luò)

    朱亞萍：女，1990年生，博士生，研究方向為短距無線通信、軟件定義傳感器網(wǎng)絡(luò)

    吳怡：女，1970年生，教授，主要研究方向為通信與信息系統(tǒng)，車輛自組織網(wǎng)絡(luò)等

    通訊作者:

    沈連豐　lfshen@seu.edu.cn

  • 中圖分類號: TN953; TP872

High-precision and Real-time Localization Algorithm for Automatic Driving Vehicles

  • 1.

    National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

  • 2.

    College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China

Funds: The National Natural Science Foundation of China (61601122, 61741102, U180526, 61571128)
  • 摘要: 針對車輛自組織網(wǎng)絡(luò)(VANETs)中的車輛定位問題，以提高定位精度和實時性為目標(biāo)，該文提出一種面向自動駕駛的車輛精確實時定位算法，包括基于矩陣束(MP)與非線性擬合(NLF)以及基于視覺感知兩種技術(shù)?；贛P-NLF的技術(shù)通過聯(lián)合TOA/AOA估計進(jìn)行車輛單站定位，并引入高分辨率估計以提高估計精度；基于視覺感知的技術(shù)通過提取定位范圍內(nèi)視覺感知圖像的特征信息來完成定位，并結(jié)合慣性信息進(jìn)行無跡卡爾曼濾波進(jìn)一步提高精度。仿真結(jié)果表明，與傳統(tǒng)多徑指紋算法相比，所提算法即使在低信噪比情況下也具有較好的定位性能。
    Abstract: For the problem of vehicle positioning in Vehicular Ad-hoc NETworks (VANETs), in order to improve the positioning accuracy and real-time performance, a high-precision and real-time localization algorithm for automatic driving vehicles is proposed, including two technologies based on Matrix Pencil (MP) and Non-Linear Fitting (NLF), and visual perception. The MP-NLF technology uses joint TOA/AOA estimation to locate vehicles with a single station, and introduces high resolution estimation technology to improve the estimation accuracy. The visual perception based technology completes the localization by extracting the feature information of visual perceptual images in positioning area, carries on the unscented Kalman filter combined with the inertial sensor information to further improve the positioning accuracy. The simulation results show that, compared with the traditional multipath fingerprinting algorithm, the proposed algorithm has better performance even in the case of low Signal-to-Noise Ratio (SNR).
    • HTML全文

  • 圖  1  VANETs車輛定位場景示意圖

    圖  2  車輛端ULA接收多徑信號示意圖

    圖  3  車輛端ULA接收示意圖

    圖  4  車輛視覺感知定位示意圖

    圖  5  VANETs車輛定位仿真場景圖

    圖  6  車輛行駛過程中所提算法與SP算法的均方根誤差比較

    圖  7  不同陣元數(shù)目下所提算法與SP算法定位誤差的CDF分布(Bw = 10 MHz)

    圖  8  不同信號帶寬下所提算法與SP算法定位誤差的CDF分布(M = 8)

    表  1  系統(tǒng)仿真參數(shù)設(shè)置

    仿真參數(shù)參數(shù)值
    OFDM子載波數(shù)目K = 16
    ULA陣元數(shù)目M4/6/8/10/12
    信號帶寬Bw (MHz)5/10/20
    SP算法中每次快拍的采樣數(shù)Ns = 8
    SP算法中數(shù)據(jù)點(diǎn)的快拍數(shù)Ld = 50
    SP算法中測試點(diǎn)的快拍數(shù)Lt = 20
    下載: 導(dǎo)出CSV
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出版歷程
  • 收稿日期:  2019-08-12
  • 修回日期:  2019-11-21
  • 網(wǎng)絡(luò)出版日期:  2019-12-04
  • 刊出日期:  2020-01-21

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