A fast algorithm on parameter estimation of LFM signals under low SNR

Meng Fei Han; Yong Qing Wang; Si Liang Wu; Wei Cui

A fast algorithm on parameter estimation of LFM signals under low SNR

Meng Fei Han^*, Yong Qing Wang, Si Liang Wu, Wei Cui

^*此作品的通讯作者

信息与电子学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

13 引用（Scopus）

摘要

To attain fast and accurate estimation under low signal and noise ratio (SNR) conditions, a novel algorithm is presented. On the basis that when linear frequency modulation (LFM) signals possess the same energy and duration, their squares of spectrum amplitude are inversely proportional to their respective frequency rates, the algorithm can give estimations of initial frequency and frequency rate together only by means of searching the maximum among several groups of fast Fourier transform (FFT) maximum amplitudes. Simulation results showed that through setting proper algorithm parameters, the algorithm can be applied to LFM signals when the SNR as low as -38 dB.

源语言	英语
页（从-至）	147-151
页数	5
期刊	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
卷	29
期	2
出版状态	已出版 - 2月 2009

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title = "A fast algorithm on parameter estimation of LFM signals under low SNR",

abstract = "To attain fast and accurate estimation under low signal and noise ratio (SNR) conditions, a novel algorithm is presented. On the basis that when linear frequency modulation (LFM) signals possess the same energy and duration, their squares of spectrum amplitude are inversely proportional to their respective frequency rates, the algorithm can give estimations of initial frequency and frequency rate together only by means of searching the maximum among several groups of fast Fourier transform (FFT) maximum amplitudes. Simulation results showed that through setting proper algorithm parameters, the algorithm can be applied to LFM signals when the SNR as low as -38 dB.",

keywords = "FFT comput-ation, Low signal and noise ratio, Parameter estimation of LFM signals, Signal and noise ratio loss",

author = "Han, {Meng Fei} and Wang, {Yong Qing} and Wu, {Si Liang} and Wei Cui",

year = "2009",

month = feb,

language = "English",

volume = "29",

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T1 - A fast algorithm on parameter estimation of LFM signals under low SNR

AU - Han, Meng Fei

AU - Wang, Yong Qing

AU - Wu, Si Liang

AU - Cui, Wei

PY - 2009/2

Y1 - 2009/2

N2 - To attain fast and accurate estimation under low signal and noise ratio (SNR) conditions, a novel algorithm is presented. On the basis that when linear frequency modulation (LFM) signals possess the same energy and duration, their squares of spectrum amplitude are inversely proportional to their respective frequency rates, the algorithm can give estimations of initial frequency and frequency rate together only by means of searching the maximum among several groups of fast Fourier transform (FFT) maximum amplitudes. Simulation results showed that through setting proper algorithm parameters, the algorithm can be applied to LFM signals when the SNR as low as -38 dB.

AB - To attain fast and accurate estimation under low signal and noise ratio (SNR) conditions, a novel algorithm is presented. On the basis that when linear frequency modulation (LFM) signals possess the same energy and duration, their squares of spectrum amplitude are inversely proportional to their respective frequency rates, the algorithm can give estimations of initial frequency and frequency rate together only by means of searching the maximum among several groups of fast Fourier transform (FFT) maximum amplitudes. Simulation results showed that through setting proper algorithm parameters, the algorithm can be applied to LFM signals when the SNR as low as -38 dB.

KW - FFT comput-ation

KW - Low signal and noise ratio

KW - Parameter estimation of LFM signals

KW - Signal and noise ratio loss

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JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 2

ER -

A fast algorithm on parameter estimation of LFM signals under low SNR

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