UM2000 Spectrum Estimation Using Multiple Signal Classification Method

2013 ◽  
Vol 734-737 ◽  
pp. 2622-2629
Author(s):  
Shen Liu ◽  
Fu Ping Wang ◽  
Xiu Cheng Liu
Keyword(s):  
Minimum Description Length ◽  
Spectral Estimation ◽  
Frequency Discrimination ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Signal Spectrum ◽  
Spectrum Estimation ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Signal Simulation

This paper focused on UM2000 signal spectrum estimation using MUSIC algorithm. Because of the limitation of data window length, traditional frequency discrimination methods fail to meet the requirement of high frequency resolution. In this paper, the influence of SNR on MUSIC spectrum estimation is analyzed and MDL (minimum description length) principle is used to determine the dimension of the signal. Simulation results based on several other modern spectral estimation methods are also presented and compared with that of MUSIC method, from which the superiority of MUSIC method is verified.

scholarly journals Enhancing the quality of communication of cellular networks using big data applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mozamel Musa Saeed ◽  
Mohammed Alsharidah
Keyword(s):  
Big Data ◽  
Spectral Density ◽  
Cellular Networks ◽  
Power Spectral Density ◽  
Spectral Estimation ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Spectral Densities ◽  
Power Spectral ◽  
Welch Method

AbstractBoth software-defined networking and big data have gained approval and preferences from both industry and academia. These two important realms have conventionally been addressed independently in wireless cellular networks. The discussion taken into consideration in this study was to analyze the wireless cellular technologies with the contrast of efficient and enhanced spectral densities at a reduced cost. To accomplish the goal of this study, Welch's method has been used as the core subject. With the aid of previous research and classical techniques, this study has identified that the spectral densities can be enhanced at reduced costs with the help of the power spectral estimation methods. The Welch method gives the result on power spectrum estimation. By reducing the effect of noise, the Welch method is used to calculate the power spectral density of a signal. When data length is increased, Welch's method is considered the best as a conclusion to this paper because excellent results are yielded by it in the area of power spectral density estimation.

scholarly journals Damped CAPES 2D Spectral Estimation for Real-Valued Vibration Signals

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Danhui Dan ◽  
Jiongxin Gong ◽  
Yiming Zhao
Keyword(s):  
Spectral Estimation ◽  
Amplitude Spectrum ◽  
Vibration Signal ◽  
Angular Frequency ◽  
Frequency Resolution ◽  
Spectrum Estimation ◽  
Vibration Signals ◽  
Vibration Data ◽  
Decay Factor ◽  
Sine Term

We propose a 2D representation in the frequency-decay factor plane of an arbitrary real-world vibration signal. The signal is expressed as the sum of a decayed-attenuation sine term modulated by an amplitude function and a noise residue. We extend the combined approach of Capon estimation and amplitude and phase estimation (CAPES) to damped real vibration signals (DR-CAPES). In the proposed DR-CAPES method, the high-resolution amplitude and phase are estimated simultaneously for both angular frequency and decay factor grids. The performance of the proposed approach is tested numerically with noisy vibration data. Results show that the DR-CAPES method has an excellent frequency resolution, which helps to overcome difficulties in spectrum estimation when vibration modes are very close, and a small bias, which makes it suitable for obtaining accurate amplitude spectrums. The results also indicate that the proposed method can accurately estimate the amplitude spectrum with the use of averaging and denoising processes.

Frequency Spectrum Estimate Based on Decomposed FLOC Matrix under Stable Distribution Noise

2014 ◽  
Vol 556-562 ◽  
pp. 4563-4567 ◽  
Author(s):  
Hai Bin Wang ◽  
Jun Bo Long ◽  
You Xue Zhou ◽  
Dai Feng Zha
Keyword(s):  
Frequency Spectrum ◽  
Stable Distribution ◽  
Estimation Method ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Complex Environment ◽  
Multiple Signal Classification ◽  
Second Order Statistics ◽  
Estimate Method ◽  
Conventional Algorithm

The radar work in a complex environment where the noise has very strong pulse, the noise can be described by stable distribution. The conventional spectrum estimation method based on second order statistics is reasonable in many cases, however, the performance of the conventional algorithm degenerate in stable distribution environment. We propose three new frequency spectrum estimate method with Fractional lower order covariance (FLOC), FLOC-Pisarenko method, FLOC-Esprit method and FLOC multiple signal classification (FLOC-MUSIC) method. The conventional spectrum estimation methods with three proposed methods under Gaussian noise and stable distribution are compared in this paper, simulations show that the conventional methods degenerate, but the proposed algorithms can work better in stable distribution environment, and are robust.

scholarly journals Comparative analysis of power spectrum estimation methods

2010 ◽  
Vol 51 ◽  
Author(s):  
Gintarė Petreikytė ◽  
Kazys Kazlauskas
Keyword(s):  
Comparative Analysis ◽  
Power Spectrum ◽  
Signal To Noise Ratio ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Parametric Methods ◽  
Signal To Noise ◽  
Power Spectrum Estimation ◽  
The Subject

The subject of this paper is the comparative analysis of the eleven most important nonparametric, parametric and subspace power spectrum estimation methods. Theoretically and experimentally we analyse how the frequency resolution of the spectrum estimation methods depends on the signal length, signal-to-noise ratio (SNR) and the order parametric methods.

scholarly journals ANALYSIS OF THE EFFICIENCY OF SPECTRAL ESTIMATION METHODS FOR DETECTION OF UAV ACOUSTIC SIGNALS

2021 ◽  
pp. 4-15
Author(s):  
М. V. Buhaiov ◽  
V. V. Branovytskyi ◽  
Y. O. Khorenko
Keyword(s):  
Acoustic Emission ◽  
Unmanned Aerial Vehicles ◽  
Acoustic Signal ◽  
Spectral Estimation ◽  
Acoustic Signals ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Signal To Noise ◽  
Statistical Quality ◽  
Aerial Vehicles

One of the most important components of counteracting small unmanned aerial vehicles is their reliable detection. You can use propeller noise to detect such objects at short distances. An energy or harmonic detector is used to receive unmanned aerial vehicles acoustic emission. At low signal-to-noise ratios , which is most common in practice, the harmonic detector provides a higher probability of detection compared to energy. The principle of the harmonic detector is based on spectral analysis of acoustic signals. A mathematical model of the acoustic signal of an aircraft-type unmanned aerial vehicles is proposed. It is shown that at short time intervals (tens of milliseconds) such signals can be considered as stationary and for its analysis can be used known methods of spectral estimation. Nonparametric, parametric and subspace methods of spectral estimation are considered for processing of acoustic emission of unmanned aerial vehicles. To conduct a comparative analysis of different methods of spectral estimation, a statistical quality index was used, which can be calculated as a variation of the estimation of power spectral density. This index characterizes the method of spectral estimation in terms of frequency resolution and the ability to detect harmonic components of the signal into noise and not create interference that exceeds the amplitude of the signal. As a result of researches it was established that at high signal-to-noise ratios parametric methods are more effective in comparison with nonparametric. However, such a statement will be valid only if the correct order of the model. It is shown that the use of spatial methods is impractical for the analysis of acoustic signals of unmanned aerial vehicles. The use of the value of the statistical quality indicator as a threshold for deciding on the presence or absence of the acoustic signal of the unmanned aerial vehicles in the adopted implementation and its further processing should be used at SNR values greater than 5 dB.

scholarly journals Joint DOA and Polarization Estimation for Unequal Power Sources

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qingyuan Fang ◽  
Yong Han ◽  
Ming Jin ◽  
Wenyi Dong
Keyword(s):  
Estimation Method ◽  
Estimation Methods ◽  
Invariance Property ◽  
Music Algorithm ◽  
Power Sources ◽  
Multiple Signal Classification ◽  
Power Difference ◽  
Joint Direction ◽  
Polarization Estimation ◽  
Cramer Rao Bound

For most joint direction of arrival (DOA) and polarization estimation methods, the performances of proposed methods in dealing with unequal power sources are not discussed. However, sources with unequal powers apparently exist widely in actual applications. In this study, we propose a joint DOA and polarization estimation method for unequal power sources by utilizing the invariance property of noise subspace (IPNS) to the power of sources. This work extends the IPNS method to the dual polarized antenna array for joint DOA and polarization estimation. Moreover, we theoretically prove that the IPNS remains valid even when the sources are correlated. The computer simulations illustrate that the proposed method can effectively estimate the DOA and polarization parameters as the power difference between sources increases, as opposed to the polarimetric multiple signal classification (MUSIC) algorithm, which suffers from degradation in resolution probability. In addition, the performances of the proposed method are provided, as well the Cramer Rao Bound (CRB), which show approximate performance as the polarimetric MUSIC algorithm.

Methods for Characterizing Flicker and its Applications

2005 ◽  
Vol 4 (2) ◽  
Author(s):  
Alexandre B Nassif ◽  
Thavatchai Tayjasanant ◽  
Dr. Wilsun Xu
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Superior Performance ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Power Spectrum Estimation ◽  
Time Frequency ◽  
Power Quality Disturbance ◽  
Common Signal

Flicker is an important power quality disturbance and has received an increasing concern from power system researchers. Interharmonics are the non-integral frequencies other than harmonic frequencies. Nowadays, research has shown that interharmonics and flicker seem to be closely related. To clarify this relationship, flicker is characterized in the frequency domain. The traditional Fourier-based methods have shown some drawbacks in representing non-stationary, non-periodic power signals and therefore other methods should be investigated for accomplishing this task. This paper introduces the most common signal processing approaches to assess the problem, power spectrum estimation methods and linear transforms. The wavelet transform has shown superior performance comparing to other methods and circumventing the problem time-frequency resolution.

scholarly journals Estimation and Comparison of Horizontal Winds Using Various Spectral Estimation Methods on Profiler Radars

2014 ◽  
Vol 31 (3) ◽  
pp. 620-629 ◽  
Author(s):  
V. K. Anandan ◽  
V. N. Sureshbabu ◽  
Toshitaka Tsuda ◽  
Jun-ichi Furumoto ◽  
S. Vijayabhaskara Rao
Keyword(s):  
Lower Stratosphere ◽  
Beam Steering ◽  
Spectral Estimation ◽  
Power Spectra ◽  
Radar Data ◽  
Signal Classification ◽  
Estimation Methods ◽  
Multiple Signal Classification ◽  
Spectral Estimators ◽  
Wind Profiles

Abstract The lower atmospheric wind profiles are obtained by the postset beam steering (PBS) technique on middle and upper (MU) atmosphere radar data. The Capon beamformer is used to improve the beam synthesizing in the desired directions within the radar transmit beamwidth. From a synthesized beam, the power spectrum is obtained by various spectral estimators, such as Fourier, multiple signal classification (MUSIC), and eigenvector (EV). The wind vector components are derived from radial velocities estimated from the power spectra of synthesized beams. As the reliability of the PBS wind estimate depends on the choice of spectral estimators, a detailed analysis is carried out to compare the performance of estimators in deriving wind profiles on the radar data. The results suggest that EV shows a better performance in deriving possible spectrum parameters and is useful for reliable wind profiling up to the lower stratosphere. The wind profiles derived by PBS with EV are more consistent with near-time observations using GPS sonde and Doppler beam swinging (DBS) methods. The study also suggests that MUSIC cannot be used to reliably estimate atmospheric spectrum parameters.

TIME-FREQUENCY CHARACTERIZATION OF FETAL PHONOCARDIOGRAPHIC SIGNALS USING WAVELET SCALOGRAM

2011 ◽  
Vol 11 (02) ◽  
pp. 391-406 ◽  
Author(s):  
VIJAY S. CHOURASIA ◽  
ANIL K. TIWARI ◽  
RANJAN GANGOPADHYAY
Keyword(s):  
Fetal Heart ◽  
Spectral Estimation ◽  
Diagnostic Technique ◽  
Well Being ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Time Frequency ◽  
Quantitative Measurements ◽  
Envelope Detection

Fetal phonocardiography is a simple and noninvasive diagnostic technique for surveillance of fetal well-being. The fetal phonocardiographic (fPCG) signals carry valuable information about the anatomical and physiological states of the fetal heart. This article is concerned with a study of continuous wavelet transform (CWT)-based scalogram in analyzing the fPCG signals. The scalogram has both spatial and frequency resolution powers, whereas traditional spectral estimation methods only have the frequency resolution ability. The fPCG signals are acquired by a specially developed data recording system. Segmentation of these signals into fundamental components of fetal heart sound (S1 & S2) is carried out through envelope detection and thresholding techniques. CWT-based scalogram is used for time-frequency characterization of the segmented fPCG signals. It has been shown that the wavelet scalogram provides enough features of the fPCG signals that will help to obtain qualitative and quantitative measurements of the time-frequency characteristics of the fPCG signals and consequently, assist in diagnosis. The proposed method for time-frequency analysis (TFA) and the associated pre-processing have been shown to be suitable for the characterization of fPCG signals, yielding relatively good and robust results in the experimental evaluation.

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