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

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

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.

Original language	English
Pages (from-to)	147-151
Number of pages	5
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	29
Issue number	2
Publication status	Published - Feb 2009

Keywords

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

Cite this

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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",

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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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M3 - Article

AN - SCOPUS:63749090958

SN - 1001-0645

VL - 29

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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

Abstract

Keywords

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