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In this paper, noise estimation based on series expansion of orthogonal functions is proposed. The proposed method searches speechless frequency regions and estimates the noise spectrum from the searched speechless frequency regions. The proposed method can adapt to changing of noise power without estimation delay. Experimental results show that the proposed method provides a good performance against...
In this paper we consider the estimation of the frequency of a complex exponential in noise. This problem is of prime significance in many signal processing applications. In particular, we focus on robust low computational complexity estimators that rely on the highly efficient FFT algorithm. We generalise a number of interpolators to the zero-padded case and derive both their interpolation expressions...
Orthogonal frequency division multiplexing (OFDM) systems require the knowledge of signal-to-noise ratio (SNR) at the receiver in order to maximize the system performance. In general, the noise variance is required by the SNR estimator and the knowledge of noise variance also improves the performances of carrier frequency offset (CFO) and channel state estimations. This paper first investigates the...
In this paper, we present a new frequency estimation of multi-component sinusoidal signals with arbitrary lowpass envelope. Conventional methods fail to produce reasonable results. The proposed method is based on estimation of the jump points in the frequency domain. No assumptions on the shape or properties of envelope is required, except being a narrowband. Unlike previous algorithms, this algorithm...
The estimation of the parameters of a decaying complex exponential in noise was examined by Bertocco et al. who developed a frequency domain interpolator using two DFT coefficients around the maximum bin. Quinn, on the other hand, and more recently Aboutanios and Mulgrew (A&M), proposed similar frequency estimators for the undamped case. In this paper, we adapt the Quinn and A&M algorithms...
In this paper, we analyze an algorithm devised for the frequency estimation of a real, noisy sinusoid, at low signal-to-noise ratios. The algorithm consists of a combination between a closed-form estimator and frequency selective filtering. We reveal its connection with the constrained notch filter approach. We calculate the asymptotic cost function and report results on bias and variance.
Formant frequency is a one of the most important speech feature, which has widespread applications in speech recognition, synthesis, and compression. In this paper, a new time-frequency domain scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented. In order to overcome the adverse effect of noise, instead of conventional autocorrelation function (ACF), a...
We address the problem of the frequency estimation of a sinusoid embedded in additive, white noise, by using a combination of statistical estimators and filtering. We test a low-complexity, iterative algorithm, devised for low signal-to-noise ratios, that approach the Cramer-Rao lower bound in a few iterations. We calculate the asymptotic cost function and evaluate the bias.
When applied to ground penetrating radar (GPR), the multiple signal classification (MUSIC) algorithm is an important frequency estimation method as it can detect very closely spaced targets, particularly when one of the target responses is substantially less than another. The MUSIC algorithm however must be seeded with the number of targets to find and will indicate that number of targets regardless...
Compressed sensing and the related recently introduced smashed filter are novel signal processing methods, which allow for low-complexity parameter estimation by projecting the signal under analysis on a random subspace. In this paper the smashed filter of Davenport et al. is applied to a principal problem of digital communications: pilot-based time offset and frequency offset estimation. An application,...
A precise estimation of SFO (Sampling Frequency Offset) is an important issue in OFDM (Orthogonal Frequency Division Multiplexing) system. However, the conventional method causes serious performance degradation of SFO estimation in low SNR (Signal to Noise Ratio) or large Doppler frequency environment. Therefore, in this paper, we propose a SFO estimation method which can achieve stable operation...
Population Monte Carlo is a statistical method that is used for generation of samples approximately from a target distribution. The method is iterative in nature and is based on the principle of importance sampling. In this paper, we show that in problems where some of the parameters are conditionally linear on the remaining parameters, we can improve the computational efficiency of population Monte...
Orthogonal frequency division multiplexing (OFDM) offers high data rates and robust performance in frequency selective channels by link adaptation utilizing information about the channel quality. A crucial parameter required for adaptive transmission is the signal-to-noise ratio (SNR). In this paper, we propose a novel SNR estimation algorithm for wireless OFDM systems based on the reuse of the synchronization...
In this paper, we present a novel method for joint estimation of the order and fundamental frequency of a set of harmonically related sinusoids. This method uses a subband based approach to estimate the involved parameters using subspace techniques, and the resulting algorithm is termed frequency-selective harmonic MUSIC (F-HMUSIC). The performance of F-HMUSIC is evaluated and compared to both harmonic...
The problem of estimating frequencies of sinusoids in noise has been studied intensively by the signal processing community during the last decades. Traditionally high resolution subspace-based techniques suffer from high computational complexity, and generally sensitive to the colored noise. We present here a frequency-domain based subspace parameter estimation algorithm termed frequency-selective...
The accuracy of the frequency estimation of a multifrequency signal component by Interpolated Discrete Fourier Transform (IpDFT) method is affected by systematic errors. In a Weighted Multipoint Interpolated Discrete Fourier Transform (WMIpDFT) method has been proposed in order to reduce these errors. This method uses only the rectangular and the 2-term maximum sidelobe decay windows. In this paper...
The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals...
The key to jam frequency-hopping communication is to estimate its parameters efficiently and precisely. An algorithm for estimating the hop duration of frequency hopping (FH) signals based on multi-window partially overlapped reassigned smoothed pseudo WVD (RSPWVD) and adaptive threshold detection technique is proposed. It divides the signal into segments according to some analytical window, analyses...
It is gaining extensive research concentration to estimate a suitable factor that will subtract just the necessary amount of the noise spectrum from each frequency bin (ideally) to prevent destructive subtraction of the speech while removing most of the residual noise. Considering the advantage of multi-band spectral subtraction method which takes into account the fact that colored noise affects the...
In this paper we present a novel frequency estimation technique, assisted by an imperfect second order arctan based Digital Phase-Locked Loop (D-PLL), for complex single sinusoidal signals in additive white Gaussian noise. The imperfect loop contains the frequency information in its phase error process, at steady state, which is then used to estimate the frequency after the signal has been acquired...
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