Signal tracking approach for simultaneous estimation of phase and instantaneous frequency
01 Feb 2015-pp 1-5
TL;DR: This paper addresses the problem of simultaneous phase and instantaneous frequency estimation from polynomial phase signals embedded in Gaussian noise by introducing the modified signal tracking approach which is then realized using unscented Kalman filter.
Abstract: Phase estimation plays an important role in various signal processing areas like Radar, Sonar, power systems, speech analysis, communications and many others. The phase of the analytic form of the non stationary signals can be used to find instantaneous frequency. This paper addresses the problem of simultaneous phase and instantaneous frequency estimation from polynomial phase signals embedded in Gaussian noise. Here we have introduced the modified signal tracking approach which is then realized using unscented Kalman filter. The state space model is derived using Taylor series expansion of the phase of polynomial phase signal as process model while Polar to Cartesian conversion as measurement model. Proposed method, compared with state-of-the-art, performs better for signals with higher order polynomial phase variations at lower Signal-to-Noise-Ratio (0-5dB). We also present the simulation results for phase estimation.
Citations
More filters
01 Aug 2002
TL;DR: The letter defines an IFR estimation algorithm and theoretically analyzes it and is seen to be asymptotically optimal at the center of the data record for high signal-to-noise ratios.
Abstract: This letter introduces a two-dimensional bilinear mapping operator referred to as the cubic phase (CP) function. For first-, second-, or third-order polynomial phase signals, the energy of the CP function is concentrated along the frequency rate law of the signal. The function, thus, has an interpretation as a time-frequency rate representation. The peaks of the CP function yield unbiased estimates of the instantaneous (angular) frequency rate (IFR) and, hence, can be used as the basis for an IFR estimation algorithm. The letter defines an IFR estimation algorithm and theoretically analyzes it. The estimation is seen to be asymptotically optimal at the center of the data record for high signal-to-noise ratios. Simulations are provided to verify the theoretical claims.
178 citations
01 Aug 2015
TL;DR: This paper discusses a Fourier transform based phase unwrapping method that is highly robust to noise and performs better even at lower SNR values (5-10dB) with a very less value of RMS error.
Abstract: Phase information recovered through interferometric techniques is mathematically wrapped in the interval (−π, π). Obtaining the original unwrapped phase is very important in numerous number of applications. This paper discusses a Fourier transform based phase unwrapping method. Kalman filter is proposed for denoising in post processing step to restore the unwrapped phase without any noise. The proposed method is highly robust to noise and performs better even at lower SNR values (5–10dB) with a very less value of RMS error. Also, the time taken for execution is very less compared to the many available methods in the literature.
10 citations
Additional excerpts
...The piecewise polynomial approximation approach [12] and signal tracking approach [15], [16] provides unwrapped phase directly, but the non-linear measurement model limits the performance of those methods....
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TL;DR: In this article , the toxic effect of two Zinc (Zn)-based MOFs; zeolitic imidazolate frameworks (ZIF-8) and leaf-like ZIF-L, was tested to investigate the impact of the postmortem period of mice carrions and arthropods which found in decomposing car rions.
Abstract: Metal-organic frameworks (MOFs) are promising materials for several applications. Thus, they have been intensively reported and commercialized by several international companies. However, little is known about the fate and risk of MOFs to living organisms. Here, the toxic effect of two Zinc (Zn)-based MOFs; zeolitic imidazolate frameworks (ZIF-8) and leaf-like ZIF (ZIF-L), was tested to investigate the impact of the postmortem period of mice carrions and arthropods which found in decomposing carrions. The data analysis revealed an increase in zinc content over time. Toxicology in forensics studies biological materials for the presence of poisons, such as pharmaceuticals. The toxicology report can provide important details about the types of chemicals present in a person and whether the amount of those substances is in line with a therapeutic dose or exceeds a dangerous level. These findings conclude the possible fate and impact after mortality. This study presents the first study of the toxic effect of ZIFs materials using mice carrions and arthropods (Sarcophaga sp. Larvae) via morphological and microscopic studies compared with control, providing important biological information could aid in the environmental impact of the toxic level of MOF materials.
7 citations
TL;DR: In this paper , the toxic effect of two Zinc (Zn)-based MOFs; zeolitic imidazolate frameworks (ZIF-8) and leaf-like ZIF-L, was tested to investigate the impact of the postmortem period of mice carrions and arthropods which found in decomposing car rions.
Abstract: Metal-organic frameworks (MOFs) are promising materials for several applications. Thus, they have been intensively reported and commercialized by several international companies. However, little is known about the fate and risk of MOFs to living organisms. Here, the toxic effect of two Zinc (Zn)-based MOFs; zeolitic imidazolate frameworks (ZIF-8) and leaf-like ZIF (ZIF-L), was tested to investigate the impact of the postmortem period of mice carrions and arthropods which found in decomposing carrions. The data analysis revealed an increase in zinc content over time. Toxicology in forensics studies biological materials for the presence of poisons, such as pharmaceuticals. The toxicology report can provide important details about the types of chemicals present in a person and whether the amount of those substances is in line with a therapeutic dose or exceeds a dangerous level. These findings conclude the possible fate and impact after mortality. This study presents the first study of the toxic effect of ZIFs materials using mice carrions and arthropods (Sarcophaga sp. Larvae) via morphological and microscopic studies compared with control, providing important biological information could aid in the environmental impact of the toxic level of MOF materials.
4 citations
References
More filters
TL;DR: It is shown that for a given PWVD order, the estimator performance can be improved by a proper choice of the kernel coefficients in the PWVD by evaluating the statistical performance of this estimator in the case of additive white Gaussian noise.
Abstract: The peak of the polynomial Wigner-Ville distribution (PWVD) has been previously proposed as an estimator of the instantaneous frequency (IF) for a monocomponent polynomial frequency modulated (FM) signal. In this paper, we evaluate the statistical performance of this estimator in the case of additive white Gaussian noise and provide an analytical expression for the variance. We show that for a given PWVD order, the estimator performance can be improved by a proper choice of the kernel coefficients in the PWVD. A performance comparison between the PWVD based IF estimator and another previously proposed one based on the high-order ambiguity function (HAF) is also provided, Simulation results show that for a signal-to-noise ratio larger than 3 dB, the proposed sixth-order PWVD outperforms the HAF in estimating the IF of a third- or fourth-order polynomial phase signal, evaluated at the central point of the observation interval.
112 citations
"Signal tracking approach for simult..." refers methods in this paper
...Former approach is realized using various methods such as Maximum Likelihood Estimation (MLE), High-order Ambiguity function (HAF) [7], Cubic polynomial phase function (CPF) [8], Discrete Chirp-Fourier Transform (DCFT) [9], Discrete Polynomial Phase Transform (DPT) [10], [11] and others [12], [13]....
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TL;DR: In this article, a nonlinear instantaneous least squares (NILS) estimator is proposed for signal parameter search. But the NILS estimator can be interpreted as an estimator based on the prediction error of a linear predictor.
Abstract: A novel method for signal parameter estimation is presented, termed the nonlinear instantaneous least squares (NILS) estimator. The basic idea is to use the observations in a sliding window to compute an instantaneous (short-term) estimate of the amplitude used in the separated nonlinear least squares (NLLS) criterion. The effect is a significant improvement of the numerical properties in the criterion function, which becomes well-suited for a signal parameter search. For small-sized sliding windows, the global minimum in the NLIS criterion function is wide and becomes easy to find. For maximum size windows, the NILS is equivalent to the NLLS estimator, which implies statistical efficiency for Gaussian noise. A "blind" signal parameter search algorithm that does not use any a priori information is proposed. The NILS estimator can be interpreted as a signal-subspace projection-based algorithm. Moreover, the NILS estimator can be interpreted as an estimator based on the prediction error of a (structured) linear predictor. Hereby, a link is established between NLLS, signal-subspace fitting, and linear prediction-based estimation approaches. The NILS approach is primarily applicable to deterministic signal models. Specifically, polynomial-phase signals are studied, and the NILS approach is evaluated and compared with other approaches. Simulations show that the signal-to-noise ratio (SNR) threshold is significantly lower than that of the other methods, and it is confirmed that the estimates are statistically efficient. Just as the NLLS approach, the NILS estimator can be applied to nonuniformly sampled data.
56 citations
"Signal tracking approach for simult..." refers background in this paper
...Non-stationary signals are common in many signal processing areas like Radar, Sonar [1], communications [2], speech analysis [3], power system [4]....
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TL;DR: The local polynomial approximation of time-varying phase is used in order to estimate the instantaneous frequency and its derivatives for a complex-valued harmonic signal given by discrete-time observations with a noise.
Abstract: The local polynomial approximation of time-varying phase is used in order to estimate the instantaneous frequency and its derivatives for a complex-valued harmonic signal given by discrete-time observations with a noise. The considered estimators are high-order nonparametric generalizations of the short-time Fourier transform and the Wigner-Ville distribution. The asymptotic variance and bias of the estimates are obtained.
45 citations
"Signal tracking approach for simult..." refers background or methods in this paper
...Keywords—Non-stationary phase signals, Signal tracking approach, Phase estimation, Kalman filters I. INTRODUCTION Non-stationary signals are common in many signal processing areas like Radar, Sonar [1], communications [2], speech analysis [3], power system [4]....
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...The polynomial phase signal is then constructed using P (n) = a0 + a1n+ a2n 2 n ∈ [1, 1024] (18)...
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...Non-stationary signals are common in many signal processing areas like Radar, Sonar [1], communications [2], speech analysis [3], power system [4]....
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TL;DR: The study reveals that the proposed approach for phase estimation from noisy reconstructed interference fields in digital holographic interferometry using an unscented Kalman filter outperforms at lower SNR values (i.e., especially in the range 0-20 dB).
Abstract: In this research work, we introduce a novel approach for phase estimation from noisy reconstructed interference fields in digital holographic interferometry using an unscented Kalman filter. Unlike conventionally used unwrapping algorithms and piecewise polynomial approximation approaches, this paper proposes, for the first time to the best of our knowledge, a signal tracking approach for phase estimation. The state space model derived in this approach is inspired from the Taylor series expansion of the phase function as the process model, and polar to Cartesian conversion as the measurement model. We have characterized our approach by simulations and validated the performance on experimental data (holograms) recorded under various practical conditions. Our study reveals that the proposed approach, when compared with various phase estimation methods available in the literature, outperforms at lower SNR values (i.e., especially in the range 0-20 dB). It is demonstrated with experimental data as well that the proposed approach is a better choice for estimating rapidly varying phase with high dynamic range and noise. (C) 2014 Optical Society of America
28 citations
"Signal tracking approach for simult..." refers methods or result in this paper
...First is to propose an efficient phase estimation approach from one dimensional complex phase modulated signal through UKF based parameter estimation or signal tracking, similar to [18], and compare the performance of the proposed approach with the stateof-the-art....
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...We note that the state model used in [18], which uses only 2 terms of the Taylor series, can not be efficiently used for phase derivative estimation/ instantaneous frequency estimation as there is no support for derivative terms of the state vector in the state space model....
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TL;DR: This paper showed that very coarse representations of formant change over time result in accurate classification of American English vowels, and that more detailed representations of contour did not improve identification for most vowels.
Abstract: Changes in formant frequency over time are important for vowel identification: listeners identify stimuli containing time-varying formants better than stimuli with steady-state formants. Statistically based pattern classifiers used as models for human perception have shown that very coarse representations of formant change over time result in accurate classification of American English vowels. In this study, using synthetic stimuli with five levels of formant contour detail, human listeners achieved maximum vowel identification for relatively coarse representations of formant movement containing information about onset, offset, and midpoint frequencies. More detailed representations of contour did not improve identification for most vowels.
17 citations
"Signal tracking approach for simult..." refers background in this paper
...Non-stationary signals are common in many signal processing areas like Radar, Sonar [1], communications [2], speech analysis [3], power system [4]....
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