Parameter Estimation of Multi-Component LFM Signals Based on STFT+Hough Transform and Fractional Fourier Transform

Xu, Fenfei; Bao, Qing; Chen, Zengping; Pan, Shengsen; Lin, Caiyong

doi:10.1109/imcec.2018.8469427

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…The expression of LVD is obtained by making a two-dimensional Fourier transformation of t n and τ based on Equation (9).…”

Section: The Lv's Distribution Algorithmmentioning

confidence: 99%

“…Many methods have been proposed to estimate the LFM signal's parameters, such as maximum likelihood estimator (MLE) [6][7][8] and time-frequency (TF) analysis methods [9][10][11][12][13][14][15][16][17]. Among the proposed methods, MLE exhibits the best estimation of the parameters theoretically, and its performance approximates the Cramer-Rao Lower Bound (CRLB).…”

Section: Introductionmentioning

confidence: 99%

“…When processing non-stationary signals, particularly when estimating the parameters of the LFM signal, the T-F analysis method is quite effective. The short-time Fourier transform (STFT) [9,10] is the earliest time-frequency analysis method. The T-F distribution established by this method is simple and intuitive, but the time-frequency resolution of this method cannot be flexibly changed when analyzing non-stationary signals.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Parameter Estimation Method Based on Piecewise Nonlinear Amplitude Transform for the LFM Signal in Impulsive Noise

et al. 2023

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In a complex electromagnetic environment, any noise present generally exhibits strong impulsive characteristics. The performance of existing parameter estimation methods carried out in Gaussian white noise for the linear frequency modulation (LFM) signal degrades or even fails under impulsive noise. This paper proposes a novel parameter estimation method to address this problem. Firstly, the properties of the piecewise nonlinear amplitude transform (PNAT) are derived. This manuscript verifies that the PNAT can retain phase information of the LFM signal while suppressing the impulsive noise. Subsequently, a new concept known as piecewise nonlinear amplitude transform parametric symmetric instantaneous autocorrelation function (PNAT-PSIAF) is proposed. Based on this concept, a novel method called piecewise nonlinear amplitude transform Lv’s distribution (PNAT-LVD) is proposed to estimate the centroid frequency and chirp rate of the LFM signal. The simulations show that the proposed algorithm can effectively suppress the impulsive noise without prior knowledge of the noise for both the single-component and double-component LFM signal. In addition, two parameters of the LFM signal can be precisely estimated by the proposed method under low generalized signal-to-noise ratios (GSNR). The stronger the impulsive characteristics of the noise, the better the performance of the algorithm.

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“…The expression of LVD is obtained by making a two-dimensional Fourier transformation of t n and τ based on Equation (9).…”

Section: The Lv's Distribution Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Parameter Estimation Method Based on Piecewise Nonlinear Amplitude Transform for the LFM Signal in Impulsive Noise

et al. 2023

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“…Substantial literature is available on parameter estimation of multi-component chirp models with distinct chirp rates (e.g., see [23], [24], [29], [10], [14], [27] and the references cited therein). On the other hand, a few works in the literature are dedicated for multi-component chirp models with equal chirp rates (e.g., see [2] and [22]).…”

Section: Introductionmentioning

confidence: 99%

On estimating parameters of a multi-component Chirp Model with equal chirp rates

Shukla¹,

Kundu²,

Mitra³

et al. 2023

Preprint

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Multi-component chirp signal models with equal chirp rates appear in various radar applications, e.g., synthetic aperture radar, echo signal of a rapid mobile target, etc. Many sub-optimal estimators have been developed for such models, however, these suffer from the problem of either identifiability or error propagation effect. In this paper, we have developed theoretical properties of the least squares estimators (LSEs) of the parameters of multi-component chirp model with equal chirp rates, where the model is contaminated with linear stationary errors. We also propose two computationally efficient estimators as alternative to LSEs, namely sequential combined estimators and sequential plugin estimators. Strong consistency and asymptotic normality of these estimators have been derived. Interestingly, it is observed that sequential combined estimator of the chirp rate parameter is asymptotically efficient. Extensive numerical simulations have been performed, which validate satisfactory computational and theoretical performance of all three estimators. We have also analysed a simulated radar data with the help of our proposed estimators of multi-component chirp model with equal chirp rates, which performs efficiently in recovery of inverse synthetic aperture radar (ISAR) image of a target from a noisy data.

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“…One well-known method is the Wigner-Hough transform (WHT) [21], which combines WVD and Hough transform to detect and estimate chirp signals and is equivalent to fractional Fourier transform [22]. Other types of TFR methods can also achieve the same function by combining HT, such as short time Fourier-Hough transform (STFHT) [23], wavelet-Hough transform [24], chirplet-Hough transform (CHT) [25], Teager-Huang-Hough transform (THHT) [26]. In general, the choice of TFR combined with HT depends on the specific characteristics of the scenario to achieve the best output SNR [15,21,27].…”

Section: Introductionmentioning

confidence: 99%

Signal extraction method in electromagnetic coupling system based on LM-ABC algorithm

Guo

Lin

et al. 2017

2017 IEEE International Conference on Information and Automation (ICIA)

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Chirp signals have established diverse applications caused by the capable of producing time-dependent linear frequencies. Most feature extraction transformation methods for chirp signals focus on enhancing the performance of transform methods but neglecting the information derived from the transformation process. Consequently, they may fail to fully exploit the information from observations, resulting in decreased performance under conditions of low signal-to-noise ratio (SNR) and limited observations. In this work, we develop a novel postprocessing method called "mapping information model" to addressing this challenge. The model establishes a link between the observation space and feature space in feature extraction transform, enabling interference suppression and obtain more accurate information by iteratively resampling and assigning weights in both spaces. Analysis of the iteration process reveals a continual increase in weight of signal samples and a gradual stability in weight of noise samples. The demonstration of the noise suppression in the iteration process and feature enhancement supports the effectiveness of the mapping information model. Furthermore, numerical simulations also affirm the high efficiency of the proposed model by showcasing enhanced signal detection and estimation performances without requiring additional observations. This superior model allows amplifying performance within feature extraction transformation for chirp signal processing under low SNR and limited observation conditions, and opens up new opportunities for areas such as communication, biomedicine, and remote sensing.

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Parameter Estimation of Multi-Component LFM Signals Based on STFT+Hough Transform and Fractional Fourier Transform

Cited by 13 publications

References 4 publications

A Novel Parameter Estimation Method Based on Piecewise Nonlinear Amplitude Transform for the LFM Signal in Impulsive Noise

A Novel Parameter Estimation Method Based on Piecewise Nonlinear Amplitude Transform for the LFM Signal in Impulsive Noise

On estimating parameters of a multi-component Chirp Model with equal chirp rates

Signal extraction method in electromagnetic coupling system based on LM-ABC algorithm

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