A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Adaptive local polynomial fourier transform in ISAR
EURASIP Journal on Applied Signal Processing
A quantitative analysis of SNR in the short-time Fourier transformdomain for multicomponent signals
IEEE Transactions on Signal Processing
Robust parameter estimation of a deterministic signal in impulsivenoise
IEEE Transactions on Signal Processing
Discrete chirp-Fourier transform and its application to chirp rateestimation
IEEE Transactions on Signal Processing
Robust Wigner distribution with application to the instantaneousfrequency estimation
IEEE Transactions on Signal Processing
The Cramer-Rao lower bound for signals with constant amplitude andpolynomial phase
IEEE Transactions on Signal Processing
Linear frequency-modulated signal detection using Radon-ambiguitytransform
IEEE Transactions on Signal Processing
Time-Frequency ARMA Models and Parameter Estimators for Underspread Nonstationary Random Processes
IEEE Transactions on Signal Processing
Analysis of multicomponent LFM signals by a combined Wigner-Houghtransform
IEEE Transactions on Signal Processing
Parameter Estimation for Locally Linear FM Signals Using a Time-Frequency Hough Transform
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Efficient estimation of Class A noise parameters via the EM algorithm
IEEE Transactions on Information Theory
Performance analysis on Lv distribution and its applications
Digital Signal Processing
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This paper presents a new method to detect linear frequency modulated (LFM) signals by jointly using the local polynomial periodogram (LPP) and the Hough transform. Theoretical comparison is made on the 3dB signal-to-noise ratios (SNRs), achieved by the pseudo-Wigner-Ville distribution (PWVD) and the LPP, to show that the latter is important to achieve significant increase of noise margins in the Hough transform domain. The results of computer simulations are presented for the detection of mono- and multi-component LFM signals corrupted by additive white Gaussian noise and impulsive noise. It is also found that by using the time-frequency filtering, the computational complexity of the detection can be substantially reduced. Both the theoretical analysis and the simulation results show that the proposed method achieves significant performance improvement on detecting the LFM signals in very low signal-to-noise ratio environments.