Journal of Transportation Systems Engineering and Information Technology ›› 2012, Vol. 12 ›› Issue (增1): 13-19.

• Development and platform of intelligent transportation • Previous Articles     Next Articles

Power Spectrum Improve Method and Its Applications in Speed Measuring Radar

FANG Fei-fei 1,2, YU Wen 1,3   

  1. 1. Shanghai Institute of Microsystem and Information Technology Institute,Chinese Academy of Sciences, Shanghai 200050, China; 2. The Graduate School of Chinese Academy of Sciences, Beijing 100039, China; 3.Shanghai Huichang Intelligent Transportation system Co.LTD, Shanghai 200233, China
  • Received:2011-12-05 Revised:2012-01-31 Online:2012-12-28 Published:2012-06-06

新的功率谱修正技术及在测速雷达中的应用

方菲菲1,2,余稳*1,3   

  1. 1.中国科学院 上海微系统与信息技术研究所,上海 200050; 2.中国科学院 研究生院,北京 100039;3.上海慧昌智能交通系统有限公司,上海 200233
  • 作者简介:方菲菲(1987-),女,浙江上虞人,硕士生.
  • 基金资助:

    国家“863”计划基金(2008AA11Z203).

Abstract: In the spectrum analysis based on the Fourier transform, spectral resolution and spectral leakage are two key factors for power spectrum estimation. This paper analyzes the influence of non-integer-periodic truncation on the property of the two factors. It proposes the frequency spectrum refinement and frequency spectrum correction methods for intelligent transportation doppler radar signals. The algorithms such as Zoom-FFT, High-order FFT, all phase FFT (ApFFT) are realized on DSP (TMS320C5416). The simulations show the algorithms’ property respectively. The theoretical analysis and experimental results show that the high-order ApFFT and all phase ZFFT(Ap-ZFFT) can be effectively applied to different radar systems.

Key words: intelligent transportation, radar speed measurement, spectrum correction technology ;all phase ZFFT, high-order ApFFT

摘要: 在经典谱估计理论中,频谱能量泄漏和频谱分辨率是进行功率谱估计时需要考虑的两个重要因素.本文通过分析非周期截断情况下这两个因素的关系,针对智能交通中广泛应用的多普勒雷达,提出了一种对其信号进行频谱细化的同时减小频谱能量泄漏的方法.其中放大镜傅里叶变换(ZFFT),高阶傅里叶变换和全相位傅里叶变换(ApFFT)等方法已成功地在DSP(TMS320C5416)上实现,并通过一系列雷达数据的仿真表现了这些方法各自的频谱特性.理论分析和实验结果表明,全相位ZFFT和高阶全相位FFT可有效地应用于不同的交通雷达系统.

关键词: 智能交通, 雷达测速, 功率谱修正, 全相位傅里叶变换, 高阶傅里叶变换

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