Journal articles on the topic 'Signal estimation'
To see the other types of publications on this topic, follow the link: Signal estimation.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Signal estimation.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Almradi, Ahmed M., and Sohail A. Dianat. "NDA SNR and CRLB Estimation Over MISO with STBC Channels." International Journal of Business Data Communications and Networking 8, no. 4 (October 2012): 1–16. http://dx.doi.org/10.4018/jbdcn.2012100101.
Full textAbstract:
This paper discusses the problem of Non Data Aided (NDA) Signal to Noise Ratio (SNR) estimation of Binary Phase Shift keying (BPSK) modulated signals using the Expectation Maximization (EM) Algorithm. In addition, the Cramer-Rao Lower Bounds (CRLB) for the estimation of Data Aided (DA) and Non Data Aided (NDA) Signal to Noise Ratio (SNR) estimation is derived. Multiple Input Single Output (MISO) channels with Space Time Block Codes (STBC) is used. The EM algorithm is a method that finds the Maximum Likelihood (ML) solution iteratively when there are unobserved (hidden or missing) data. Extension of the proposed approach to other types of linearly modulated signals in estimating SNR is straight forward. The performance of the estimator is assessed using the NDA CRLBs. Alamouti coding technique is used in this paper with two transmit antennas and one receive antenna. The authors’ assumption is that the received signal is corrupted by additive white Gaussian noise (AWGN) with unknown variance, and scaled by fixed unknown complex channel gain. Monte Carlo simulations are used to show that the proposed estimator offers a substantial improvement over the conventional Single Input Single Output (SISO) NDA SNR estimator due to the use of the statistical dependences in space and time. Moreover, the proposed NDA SNR estimator works close to the NDA SNR estimator over Single Input Multiple Output (SIMO) channels.
2
An, Qi, Zi-shu He, Hui-yong Li, and Yong-hua Li. "Phase Clustering Based Modulation Classification Algorithm for PSK Signal over Wireless Environment." Mobile Information Systems 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/2398464.
Full textAbstract:
Promptitude and accuracy of signals’ non-data-aided (NDA) identification is one of the key technology demands in noncooperative wireless communication network, especially in information monitoring and other electronic warfare. Based on this background, this paper proposes a new signal classifier for phase shift keying (PSK) signals. The periodicity of signal’s phase is utilized as the assorted character, with which a fractional function is constituted for phase clustering. Classification and the modulation order of intercepted signals can be achieved through its Fast Fourier Transform (FFT) of the phase clustering function. Frequency offset is also considered for practical conditions. The accuracy of frequency offset estimation has a direct impact on its correction. Thus, a feasible solution is supplied. In this paper, an advanced estimator is proposed for estimating the frequency offset and balancing estimation accuracy and range under low signal-to-noise ratio (SNR) conditions. The influence on estimation range brought by the maximum correlation interval is removed through the differential operation of the autocorrelation of the normalized baseband signal raised to the power ofQ. Then, a weighted summation is adopted for an effective frequency estimation. Details of equations and relevant simulations are subsequently presented. The estimator proposed can reach an estimation accuracy of10-4even when the SNR is as low as-15 dB. Analytical formulas are expressed, and the corresponding simulations illustrate that the classifier proposed is more efficient than its counterparts even at low SNRs.
3
Chudnikov, V. V., and B. I. Shakhtarin. "Adaptive Signal Frequency Estimation." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 6 (129) (December 2019): 41–49. http://dx.doi.org/10.18698/0236-3933-2019-6-41-49.
Full textAbstract:
The paper introduces an adaptive algorithm for estimating the frequencies of harmonic components in the signal against the background of additive white noise. This method is iterative, which distinguishes it from the periodogram and parametric spectral estimation methods. The key feature of the algorithm is that it gives a reasonably accurate estimation only for the preset number of harmonic components included in the signal under study. In the original discrete signal, a frequency search was performed at each time sample using the gradient descent method. Frequency estimation is made when the frequency error value tends to a certain value. The search is based on the representation of the value of the current sample of the harmonic signal of a known frequency through the two previous values. Knowing the number of components included in the original signal sequence, it is possible to form the resulting sequence containing only residual noise samples. A mathematical model of the algorithm is given, its work is simulated for different conditions of application, the accuracy of the algorithm, i.e., frequency estimation, and the number of iterations for various signal-to-noise ratios are shown.
4
Zhou, Qian, Si Wei Zhao, Jia Si Wei, Hao Yan, and Hui Zhao. "Parameter Estimation of Photoacoustic Signal for Glucose Solutions Using Laplace Wavelet Correlation Filtering and Least Square Estimation." Applied Mechanics and Materials 475-476 (December 2013): 225–35. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.225.
Full textAbstract:
In photoacoustic (PA) technology, piezoelectrical transducer (PZT) is the most frequently used detector for the PA signal generated by weakly absorbing liquids. Although PZT has high sensitivity, its output signals are distorted and become exponentially damped sinusoidal signal [, which is a barrier to extract correct information of glucose. Therefore it is necessary to find a proper way to extract glucose information. In this paper, a method of parameter estimation based on Laplace wavelet correlation filtering and Least Square Estimation is proposed to extract the information of PA signals, which includes signal decomposition, fitting and glucose parameter extraction. The Laplace wavelet correlation filtering is introduced to decompose piezoelectrical signals into impulse responses of single mode subsystems [2], followed by a Least Square Estimator to fit PA signal and estimate parameters of the exponentially damped sinusoidal model [3]. Good agreement between the fitting model and the PA signal is obtained. Experiments are carried out on finding meaningful parameters indicating glucose among estimated parameters of the exponentially damped sinusoidal model.
5
Aggoun, Lakhdar, and Robert J. Elliott. "Celestial signal estimation." Stochastic Analysis and Applications 12, no. 4 (January 1994): 399–407. http://dx.doi.org/10.1080/07362999408809360.
Full text
6
Nam, Gyeong-Mo, and Eui-Rim Jeong. "Distance Estimation Based on Deep Convolutional Neural Network Using Ultra-Wideband Signals." Journal of Computational and Theoretical Nanoscience 17, no. 7 (July 1, 2020): 3212–17. http://dx.doi.org/10.1166/jctn.2020.9163.
Full textAbstract:
Recently, high accuracy localization technique is required to provide indoor location services. The purpose of this paper is to propose a distance estimation technique based on deep convolutional neural network (DCNN) for indoor environments. Among distance estimation techniques based on wireless communication signals, the use of ultra-wideband (UWB) signals has the advantage of high accuracy in the time domain. The proposed distance estimation method uses UWB signals and proposes a new DCNN-based distance estimator. The superiority of the proposed method is confirmed through computer simulation. Widely used conventional distance estimators are based on the power threshold. The threshold is determined by signal to noise ratio (SNR) of the received signal. The arrival time of the received signal that exceeds the threshold is considered as the time-of-arrival (ToA) and the distance between transmitter and receiver is obtained from the ToA. On the other hand, the proposed distance estimator requires only the received signal without SNR estimation, which make the proposed technique simpler to implement. According to computer simulation, the conventional method is highly sensitive to SNR and distance. In contrast, the proposed method shows less than 2 m root mean square error (RMSE) performance in a wide range of SNR and the RMSE performance is not degraded in long distances. The proposed distance estimator shows excellent distance estimation performance at low SNR and long distance, so it can be applied to indoor localization system of large indoor space and can be used for precise location service.
7
Xu, Wu, Yu, and Guang. "A Robust Direction of Arrival Estimation Method for Uniform Circular Array." Sensors 19, no. 20 (October 12, 2019): 4427. http://dx.doi.org/10.3390/s19204427.
Full textAbstract:
Estimating the Direction of Arrival (DOA) is a basic and crucial problem in array signal processing. The existing DOA methods fail to obtain reliable and accurate results when noise and reverberation occur in real applications. In this paper, an accurate and robust estimation method for estimating the DOA of sources signal is proposed. Incorporating the Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm with the RANdom SAmple Consensus (RANSAC) algorithm gives rise to the RAN-ESPRIT method, which removes outliers automatically in noise-corrupted environments. In this work, a uniform circular array (UCA) is converted into a virtual uniform linear array (ULA) to begin with. Then, the covariance matrix of the received signals of the virtual linear array is reconstructed, and the ESPRIT algorithm is deployed to estimate initial DOA of the source signal. Finally, the modified RANSAC method with automatically selected thresholds is used to fit the source signal to obtain accurate DOA. The proposed method can remove the unreliable DOA feature data and leads to more accuracy of DOA estimation of source signals in reverberation environments. Experimental results demonstrate that the proposed method is more robust and efficient compared to the traditional methods (i.e., ESPRIT, TLS-ESPRIT).
8
Virosztek, Tamás, and István Kollár. "Theoretical Limits of Parameter Estimation Based on Quantized Data." Periodica Polytechnica Electrical Engineering and Computer Science 61, no. 4 (August 17, 2017): 312. http://dx.doi.org/10.3311/ppee.10224.
Full textAbstract:
Parameter estimation of band-limited periodic signals (sine and multisine waves) is a very common task in the field of measurement technology and control engineering. In the overwhelming majority of data acquisition and control systems the analog signals of the real world are sampled an quantized using analog-to-digital converters (ADCs). To estimate the parameters of the analog signal and the parameters of the quantizer from the same measurement record is an obvious need in these cases. The parameters of the recorded signal can be used to calculate the response of our system (e.g. signals of the actuators) while the parameters of the quantizer can be used to identify the transfer characteristic of the measurement channel. Maximum likelihood (ML) estimation of the quantizer and analog signal parameters has been developed to perform this task and to provide asymptotically unbiased and efficient estimators for the quantizer and signal parameters. This paper investigates the theoretical limits of this kind of estimation: provides the Cramér-Rao Lower Bound (CRLB) for the covariance of the achieved estimators and compares them to CRLB values obtained using less complex signal and channel models. This article also provides a comparison of the empirical covariance of estimator populations achieved different ways to the CRLB of estimation. The major tendencies are drawn and explanation for them is provided as well.
9
Mohammed, Bassim Sayed, and Dalya Khalid Hasan. "Estimating Angle of Arrival (AOA) for Wideband Signal by Sensor Delay Line (SDL) and Tapped Delay Line (TDL) Processors." Journal of Engineering 24, no. 4 (March 31, 2018): 96. http://dx.doi.org/10.31026/j.eng.2018.04.07.
Full textAbstract:
Angle of arrival (AOA) estimation for wideband signal becomes more necessary for modern communication systems like Global System for Mobile (GSM), satellite, military applications and spread spectrum (frequency hopping and direct sequence). Most of the researchers are focusing on how to cancel the effects of signal bandwidth on AOA estimation performance by using a transversal filter (tap delay line) (TDL). Most of the researchers were using two elements array antenna to study these effects. In this research, a general case of proposed (M) array elements is used. A transversal filter (TDL) in phase adaptive array antenna system is used to calculate the optimum number of taps required to compensate these effect. The proposed system uses a phase adaptive array antenna in conjunction with LMS algorithm to work an angle of arrival (AOA) estimator for wideband signals rather than interference canceller. An alternative solution to compensate for the effect of signal bandwidth is proposed by using sensor delay line (SDL) instead of fixed delay unit since it has variable time sampling in the time domain and not fixed time delay, depending on the angle of arrival of received signals. The proposed system has the ability to estimate two parameters for received signals simultaneously (the output Signal to Noise Ratio (SNR) and AOA), unlike others systems which estimate AOA only. The comparison of the simulation results with Multiple Signal Classification (MUSIC) technique showed that the proposed system gives good results for estimating AOA and the output SNR for wideband signals. (SDL) processor shows better performance result than (TDL) processor. MUSIC technique with both (SDL) and (TDL) processors shows unacceptable results for estimating (AOA) for the wideband signal.
10
Kumar, R. Suresh, and P. Manimegalai. "Detection and Separation of Eeg Artifacts Using Wavelet Transform." International Journal of Informatics and Communication Technology (IJ-ICT) 7, no. 3 (December 1, 2018): 149. http://dx.doi.org/10.11591/ijict.v7i3.pp149-156.
Full textAbstract:
Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real-time and recorded signals in multisensory instruments contains different and huge amount of noise, and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time-invariant filters. In this process, the input signal and the noise signal are assumed to achieve the linear output signal. During the process, the non-stationary signals arise in the bio-medical signal processing in addition to it there is no effective structure to deal with them. Wavelets transform has been proved to be the efficient tool for handling the non-stationary signals, but wavelet provide any possible way to approach multichannel signal processing. Based on the basic structure of linear estimation of non-stationary multichannel data and statistical models of spatial signal coherence acquire through the wavelet transform in multichannel estimation. The above methods can be used for Electroencephalography (EEG) signal denoising through the original signal and then implement the noise reduction technique to evaluate their performance such as SNR, MSE and computation time.
11
Li, Weiwei, Robert E. Skelton, and Emanuel Todorov. "State Estimation With Finite Signal-to-Noise Models via Linear Matrix Inequalities." Journal of Dynamic Systems, Measurement, and Control 129, no. 2 (July 15, 2006): 136–43. http://dx.doi.org/10.1115/1.2432358.
Full textAbstract:
This paper presents estimation design methods for linear systems whose white noise sources have intensities affinely related to the variance of the signal they corrupt. Systems with such noise sources have been called finite signal-to-noise (FSN) models, and the results provided in prior work demonstrate that estimation problem for FSN systems (estimating to within a specified covariance error bound) is nonconvex. We shall show that a mild additional constraint for scaling will make the problem convex. In this paper, sufficient conditions for the existence of the state estimator are provided; these conditions are expressed in terms of linear matrix inequalities (LMIs), and the parametrization of all admissible solutions is provided. Finally, a LMI-based estimator design is formulated, and the performance of the estimator is examined by means of numerical examples.
12
Izah, Rofiatul, Subiyanto Subiyanto, and Dhidik Prastiyanto. "Improvement of DSOGI PLL Synchronization Algorithm with Filter on Three-Phase Grid-connected Photovoltaic System." Jurnal Elektronika dan Telekomunikasi 18, no. 1 (August 31, 2018): 35. http://dx.doi.org/10.14203/jet.v18.35-45.
Full textAbstract:
Synchronous Reference Frame Phase Locked Loop (SRF PLL) has been widely used for synchronization three-phase grid-connected photovoltaic (PV) system. On the grid fault, SRF PLL distorted by negative sequence component and grid harmonic that caused an error in estimating parameter because of ripple and oscillation. This work combined SRF PLL with Dual Second Order Generalized Integrator (DSOGI) and filter to minimize ripple and minimize oscillation in the phase estimation and frequency estimation. DSOGI was used for filtering and obtaining the 90o shifted versions from the vαβ signals. These signals (vαβ) were generated from three phase grid voltage signal using Clarke transform. The vαβ signal was the inputs to the positive-sequence calculator (PSC). The positive-sequence vαβ was transformed to the dq synchronous reference frame and became an input to SRF-PLL to create the estimation frequency. This estimation frequency from SRF PLL was filtered by the low-pass filter to decrease grid harmonic. Moreover, the output of low-pass filter was a frequency adaptive. The performance of DSOGI PLL with filter is compared with DSOGI PLL, SRF PLL, and IEEE standard 1547(TM)-2003. The improvement of DSOGI PLL with filter gave better performances than DSOGI PLL and SRF PLLbecause it minimized ripples and oscillations in the phase and frequency estimations.
13
Davis, Daniel J., and John H. Challis. "Vertical Ground Reaction Force Estimation From Benchmark Nonstationary Kinematic Data." Journal of Applied Biomechanics 37, no. 3 (June 1, 2021): 272–76. http://dx.doi.org/10.1123/jab.2020-0237.
Full textAbstract:
Time-differentiating kinematic signals from optical motion capture amplifies the inherent noise content of those signals. Commonly, biomechanists address this problem by applying a Butterworth filter with the same cutoff frequency to all noisy displacement signals prior to differentiation. Nonstationary signals, those with time-varying frequency content, are widespread in biomechanics (eg, those containing an impact) and may necessitate a different filtering approach. A recently introduced signal filtering approach wherein signals are divided into sections based on their energy content and then Butterworth filtered with section-specific cutoff frequencies improved second derivative estimates in a nonstationary kinematic signal. Utilizing this signal-section filtering approach for estimating running vertical ground reaction forces saw more of the signal’s high-frequency content surrounding heel strike maintained without allowing inappropriate amounts of noise contamination in the remainder of the signal. Thus, this signal-section filtering approach resulted in superior estimates of vertical ground reaction forces compared with approaches that either used the same filter cutoff frequency across the entirety of each signal or across the entirety of all signals. Filtering kinematic signals using this signal-section filtering approach is useful in processing data from tasks containing an impact when accurate signal second derivative estimation is of interest.
14
Liu, Shiming, Sihai Li, Jiangtao Zheng, Qiangwen Fu, and Yanhua Yuan. "C/N0 Estimator Based on the Adaptive Strong Tracking Kalman Filter for GNSS Vector Receivers." Sensors 20, no. 3 (January 29, 2020): 739. http://dx.doi.org/10.3390/s20030739.
Full textAbstract:
The carrier-to-noise ratio (C/N0) is an important indicator of the signal quality of global navigation satellite system receivers. In a vector receiver, estimating C/N0 using a signal amplitude Kalman filter is a typical method. However, the classical Kalman filter (CKF) has a significant estimation delay if the signal power levels change suddenly. In a weak signal environment, it is difficult to estimate the measurement noise for CKF correctly. This article proposes the use of the adaptive strong tracking Kalman filter (ASTKF) to estimate C/N0. The estimator was evaluated via simulation experiments and a static field test. The results demonstrate that the ASTKF C/N0 estimator can track abrupt variations in C/N0 and the method can estimate the weak signal C/N0 correctly. When C/N0 jumps, the ASTKF estimation method shows a significant advantage over the adaptive Kalman filter (AKF) method in terms of the time delay. Compared with the popular C/N0 algorithms, the narrow-to-wideband power ratio (NWPR) method, and the variance summing method (VSM), the ASTKF C/N0 estimator can adopt a shorter averaging time, which reduces the hysteresis of the estimation results.
15
Wang, Huan, Chang Xing Li, and Yong Zhuang Li. "Code Rate Estimation Algorithm for BPSK Signal Based on Wavelet Transformation." Advanced Materials Research 740 (August 2013): 178–82. http://dx.doi.org/10.4028/www.scientific.net/amr.740.178.
Full textAbstract:
A wavelet transformation based estimating algorithm for the symbol rate of BPSK signals is adopted . This method extracts baseband signal from the generated BPSK modulated signal by means of different ways, utilizing the modulus of wavelet transformation coefficients of this baseband signal to construct a singular pulse sequence consistent with the code rate of original modulated signal. Theoretical analysis on the power spectrum of this singular pulse sequence indicates that there exist discrete spectral lines in the integral multiples of baseband signal symbol rate, thus detecting these discrete spectral lines can achieve the estimation of signal symbol rate. Our proposed algorithm can estimate the signal symbol rate under the low SNR condition.
16
Bukkapatnam, Satish T. S., Soundar R. T. Kumara, and Akhlesh Lakhtakia. "Fractal Estimation of Flank Wear in Turning." Journal of Dynamic Systems, Measurement, and Control 122, no. 1 (June 4, 1999): 89–94. http://dx.doi.org/10.1115/1.482446.
Full textAbstract:
A novel fractal estimation methodology, that uses—for the first time in metal cutting literature—fractal properties of machining dynamics for online estimation of cutting tool flank wear, is presented. The fractal dimensions of the attractor of machining dynamics are extracted from a collection of sensor signals using a suite of signal processing methods comprising wavelet representation and signal separation, and are related to the instantaneous flank wear using a recurrent neural network. The performance of the resulting estimator, evaluated using actual experimental data, establishes our methodology to be viable for online flank wear estimation. This methodology is adequately generic for sensor-based prediction of gradual damage in mechanical systems, specifically manufacturing processes. [S0022-0434(00)02401-1]
17
Sharma, Abhinav, R. Gowri, Vinay Chowdary, Abhishek Sharma, and Vibhu Jately. "Maximum Likelihood Direction of Arrival Estimation using Chicken Swarm Optimization Algorithm." International Journal of Mathematical, Engineering and Management Sciences 6, no. 2 (April 1, 2021): 621–35. http://dx.doi.org/10.33889/ijmems.2021.6.2.038.
Full textAbstract:
Aspects towards the area of array signal processing are majorly confined to two techniques, Direction of arrival (DOA) estimation and adaptive beamforming (ABF). There exist different traditional techniques for estimating the direction of incoming signals such as spectral and Eigen structure-based methods that find the direction of incoming signals. The major drawback of these techniques are that they fail to find the direction of the incoming signal in environments of low signal to noise (SNR). The maximum likelihood (ML) method has an upper hand in terms of statistical performance as compared to conventional methods and finds the direction of signal in low SNR conditions. In this article, the chicken swarm optimization (CSO) algorithm is explored for the optimization of ML function to find the direction of signals in uniform linear arrays (ULA). The algorithm is inspected with respect to the root mean square error (RMSE) and the probability of resolution (PR). Simulation results of the proposed technique prove that the ML-CSO algorithm outperforms other heuristic approaches such as the flower pollination algorithm (FPA) and other conventional techniques such as Capon, multiple signal classification (MUSIC), estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm in lower SNR environment.
18
Lánský, Petr, and Priscilla E. Greenwood. "Optimal Signal Estimation in Neuronal Models." Neural Computation 17, no. 10 (October 1, 2005): 2240–57. http://dx.doi.org/10.1162/0899766054615653.
Full textAbstract:
We study optimal estimation of a signal in parametric neuronal models on the basis of interspike interval data. Fisher information is the inverse asymptotic variance of the best estimator. Its dependence on the parameter value indicates accuracy of estimation. Our models assume that the input signal is estimated from neuronal output interspike interval data where the frequency transfer function is sigmoidal. If the coefficient of variation of the interspike interval is constant with respect to the signal, the Fisher information is unimodal, and its maximum for the most estimable signal can be found. We obtain a general result and compare the signal producing maximal Fisher information with the inflection point of the sigmoidal transfer function in several basic neuronal models.
19
Li, Jian Feng, Wei Yang Chen, and Xiao Fei Zhang. "Conjugate ESPRIT for MIMO Radar without Using Non-Circular Signals." Applied Mechanics and Materials 513-517 (February 2014): 3850–54. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3850.
Full textAbstract:
Without using non-circular signals, conjugate estimation of signal parameters via rotational invariance technique (ESPRIT) for joint estimation of direction of departure (DOD) and direction of arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The characteristics of the Vandermonde-like matrix are employed to expand the virtual array of MIMO radar. Then the rotational invariance in the signal subspace is exploited to get the automatically paired estimations of angles. The proposed algorithm works with the same data model as that of ESPRIT, and has better angle estimation performance and can detect more targets than ESPRIT. Simulation results verify the usefulness of our approach.
20
A. Stoorvogel, A., H. H. Niemann, A. Saberi, and P. Sannuti. "Optimal fault signal estimation." International Journal of Robust and Nonlinear Control 12, no. 8 (2002): 697–727. http://dx.doi.org/10.1002/rnc.714.
Full text
21
Gunaratne, S., P. Taaghol, and R. Tafazolli. "Signal quality estimation algorithm." Electronics Letters 36, no. 22 (2000): 1882. http://dx.doi.org/10.1049/el:20001323.
Full text
22
Joindot, Michel. "Signal analysis and estimation." Signal Processing 17, no. 2 (June 1989): 186–87. http://dx.doi.org/10.1016/0165-1684(89)90024-8.
Full text
23
Zhou, Ju, Lihua Lei, and Naijin Liu. "Spectrum estimation of electromagnetic signal based on AR model parametric spectrum estimation." MATEC Web of Conferences 232 (2018): 04067. http://dx.doi.org/10.1051/matecconf/201823204067.
Full textAbstract:
For the low accuracy of classical spectrum estimation, the AR model method in modern parameter estimation is proposed to analyze the spectrum of electromagnetic signal. The basic principle of AR model is introduced and the Burg algorithm is simulated by Matlab. The electromagnetic signal in the real environment is simulated by the classical FFT method and the AR model method. Comparing the results show that the AR model is more accurate and reliable in the detection of electromagnetic signals, so modern parameter spectral estimation can be used as a method for spectrum analysis of electromagnetic signals.
24
Nakamura, M. "Waveform and Latency Estimation from Neuroelectric Signals Using the Bispectrum." Methods of Information in Medicine 33, no. 01 (1994): 32–34. http://dx.doi.org/10.1055/s-0038-1634992.
Full textAbstract:
Abstract:A technique based on bispectra and cross-bispectra is described for estimating waveform and latency from a set of noisy signals with variable latency. Waveform estimation is performed by averaging bispectra of observed noisy signals. Latency estimation is performed by using the product function of a function derived from the cross-bispectrum and the cross-correlation. The method is numerically assessed by simulations, using a signal with uniformly distributed latency and computer-generated noise sequences.
25
Mizumachi, Mitsunori, and Katsuyuki Niyada. "Robust Estimation of Sound Source Direction with Deterministic Background Noise and Stochastic Source Dynamics Models." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 2 (March 20, 2010): 208–13. http://dx.doi.org/10.20965/jaciii.2010.p0208.
Full textAbstract:
Direction of Arrival (DOA), a type of auxiliary information used in acoustic signal processing, is vulnerable to acoustical noise, so we want to male the estimation of DOA in noisy environments, relying on spectral sparseness. The energy of acoustic signals such as speech is wide-band, with individual signals localized in specific but different frequency regions. Our proposal involves filtering out spatial features provisionally from subband frequency components at the dominant frequency of the target signal using particle filtering with a sound source dynamics model. The feasibility of our proposal is confirmed by estimating a sound source direction in noisy conditions, also confirming that frequency selectivity and state estimation using particle filters help improve DOA estimation robustness against noise in noisy conditions.
26
DOWNIE, T. R. "ACCURATE SIGNAL ESTIMATION NEAR DISCONTINUITIES." International Journal of Wavelets, Multiresolution and Information Processing 02, no. 04 (December 2004): 433–53. http://dx.doi.org/10.1142/s0219691304000627.
Full textAbstract:
Wavelet thresholding is an effective method for noise reduction of a wide class of naturally occurring signals. However, bias near to a discontinuity and Gibbs phenomenon are a drawback in wavelet thresholding. The extent to which this is a problem is investigated. The Haar wavelet basis is good at approximating discontinuities, but is bad at approximating other signal artefacts. A method of detecting jumps in a signal is developed that uses non-decimated Haar wavelet coefficients. This is designed to be used in conjunction with most existing thresholding methods. A detailed simulation study is carried out and results show that when discontinuities are present a substantial reduction in bias can be obtained, leading to a corresponding reduction in mean square error.
27
Benšic, Tin, Marinko Barukcic, Željko Hederic, Venco Corluka, Nebojsa Bozidar Raicevic, and Ilona Iatcheva. "Position estimation of active magnetic bearing shaft using auxiliary coils." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 4 (July 2, 2018): 1328–41. http://dx.doi.org/10.1108/compel-08-2017-0366.
Full textAbstract:
Purpose The purpose of this paper is to develop a system for estimating the position of the active magnetic bearing (AMB) shaft. A new approach using the static and dynamic inductances and complex analytic signal to simplify the estimation procedure. Finite element (FE) simulations are introduced as a part of the system synthesis. Design/methodology/approach The paper presents an AMB displacement estimation system. The system is created with three inductive sensors. The position is computed from refined static and dynamic inductance obtained from complex analytic signals of flux and current. FE simulation is used to relate refined inductances to the displacement and to verify the model. Findings This paper shows the applicability of complex analytic signal transformation on estimation systems. The use of new refined inductance is presented in contrast to the classical approach of static and dynamic inductances. The paper shows that classical approach of static and dynamic inductance is not usable for the presented estimation system. Practical implications For the practical implementation of the presented system, it is necessary to know the exact dimensions of the AMB stator and the voltage and frequency used to supply the inductance estimation system. Originality/value The paper presents a system for estimating the displacement of AMB. The paper introduces the application of complex analytic signal to the estimation of AMB displacement. The mentioned signal is used to compute the new refined inductances. The comparison to the classical approach of static and dynamic inductances is given in this paper. The paper introduces FE simulations to the estimation system synthesis.
28
Zhou, Shen, and Liu Rongfang. "Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping." Mathematical Problems in Engineering 2019 (April 14, 2019): 1–6. http://dx.doi.org/10.1155/2019/7396074.
Full textAbstract:
In the case of low signal-to-noise ratio, for the frequency estimation of single-frequency sinusoidal signals with additive white Gaussian noise, the phase unwrapping estimator usually performs poorly. In this paper, an efficient and accurate method is proposed to address this problem. Different from other methods, based on fast Fourier transform, the sampled signals are estimated with the variances approaching the Cramer-Rao bound, followed with the maximum likelihood estimation of the frequency. Experimental results reveal that our estimator has a better performance than other phase unwrapping estimators. Compared with the state-of-the-art method, our estimator has the same accuracy and lower computational complexity. Besides, our estimator does not have the estimation bias.
29
Zheng, Peng, Feng Liu, and Xin Zhang. "Parameter Estimation of the Direct Sequence Spread Spectrum Signal Based on Time-Smoothing Cyclic Periodogram." Applied Mechanics and Materials 195-196 (August 2012): 181–85. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.181.
Full textAbstract:
The direct sequence spread spectrum (DS-SS) signal is a typical kind of LPI signals widely-used in the modern digital communication system, and it is difficult to be detected for its statistical characteristic similar to noise. An algorithm for estimating the code rate, carrier frequency of DS-SS signals was proposed using time-smoothing cyclic periodogram instead of cyclic spectrum according to cyclostationary feature of DS-SS signal to improve the precision of parameter estimation. The estimation performance was analyzed for the cyclic spectrum by time-smoothing cyclic periodogram from the tapering points in the case of limited data length. Simulation results showed that the proposed algorithm is effective.
30
Memduh; TAŞCIOĞLU, KÖSE. "Signal-to-noise ratio estimation of noisy transient signals." Communications Faculty Of Science University of Ankara 57, no. 1 (2015): 11–19. http://dx.doi.org/10.1501/commua1-2_0000000084.
Full text
31
Ksendzuk, A. V., and A. A. Kanatchikov. "SPACEBORNE SAR SIGNAL DETECTION AND PARAMETER ESTIMATION IN SPACE TRACKING AND SURVEILLANCE SYSTEM MODELING." Issues of radio electronics, no. 3 (March 20, 2019): 31–35. http://dx.doi.org/10.21778/2218-5453-2019-3-31-35.
Full textAbstract:
The development of information support of the space tracking and surveillance system is a highly topical task, the solution of which will help to increase the effectiveness of monitoring space objects. Development and practical application of the software for Spaceborne synthetic aperture radar (SAR) signal detection and parameter estimation described and analyzed. Architecture of the software is described, processing results in the simulation mode (comparison of different processing methods) and real SAR satellite signals processing mode analyzed. In simulation mode detection and parameter estimation methods compared statistically as averaged estimation error as a function of the signal‑to‑noise ratio. Estimator statistical characteristics – bias, variation, error histogram – derived and analyzed.
32
Wang, Ke, Xiaopeng Yan, Zhiqiang Zhu, Xinhong Hao, Ping Li, and Qian Yang. "Blind Estimation Methods for BPSK Signal Based on Duffing Oscillator." Sensors 20, no. 22 (November 10, 2020): 6412. http://dx.doi.org/10.3390/s20226412.
Full textAbstract:
To realize the blind estimation of binary phase shift keying (BPSK) signal, this paper describe a new relational expression among the state of Duffing oscillator excited by BPSK signal, the pseudo-random code of BPSK signal, and the difference frequency between the to-be-detect signal and internal drive force signal of Duffing oscillator. Two output characteristics of Duffing oscillators excited by BPSK signals named implied periodicity and pilot frequency array synchronization are presented according to the different chaotic states of Duffing oscillator. Then two blind estimation methods for the carrier frequency and pseudo-random sequence of the BPSK signal are proposed based on these two characteristics, respectively. These methods are shown to have a significant effect on the parameter estimation of BPSK signals with no prior knowledge, even at very low signal-to-noise ratios (SNRs).
33
Ata, Serdar Ozgur, and Cevdet Isik. "High-Resolution Direction-of-Arrival Estimation via Concentric Circular Arrays." ISRN Signal Processing 2013 (March 28, 2013): 1–8. http://dx.doi.org/10.1155/2013/859590.
Full textAbstract:
Estimating the direction of arrival (DOA) of source signals is an important research interest in application areas including radar, sonar, and wireless communications. In this paper, the problem of DOA estimation is addressed on concentric circular antenna arrays (CCA) in detail as an alternative to the well-known geometries of the uniform linear array (ULA) and uniform circular array (UCA). We define the steering matrix of the CCA geometry and investigate the performance analysis of the array in the DOA-estimation problem by simulations that are realized through varying the parameters of signal-to-noise ratio, number of sensors, and resolution angle of sensor arrays by using the MUSIC (Multiple Signal Classification) algorithm. The results present that CCA geometries provide higher angle resolutions compared to UCA geometries and require less physical area for the same number of sensor elements. However, as a cost-increasing effect, higher computational power is needed to estimate the DOA of source signals in CCAs compared to ULAs.
34
Si, Wei-Jian, Qiang Liu, and Zhi-An Deng. "Adaptive Reconstruction Algorithm Based on Compressed Sensing Broadband Receiver." Wireless Communications and Mobile Computing 2021 (January 15, 2021): 1–12. http://dx.doi.org/10.1155/2021/6673235.
Full textAbstract:
Existing greedy reconstruction algorithms require signal sparsity, and the remaining sparsity adaptive algorithms can be reconstructed but cannot achieve accurate sparsity estimation. To address this problem, a blind sparsity reconstruction algorithm is proposed in this paper, which is applied to compressed sensing radar receiver system. The proposed algorithm can realize the estimation of signal sparsity and channel position estimation, which mainly consists of two parts. The first part is to use fast search based on dichotomy search, which is based on the high probability reconstruction of greedy algorithm, and uses dichotomy search to cover the number of sparsity. The second part is the signal matching and tracking algorithm, which is mainly used to judge the signal position and reconstruct the signal. Combine the two parts together to realize the blind estimation of the sparsity and the accurate estimation of the number of signals when the number of signals is unknown. The experimental analyses are carried out to evaluate the performance of the reconstruction probability, the accuracy of sparsity estimation, the running time of the algorithm, and the signal-to-noise ratio.
35
Jia, Libin, Jeffrey D. Naber, and Jason R. Blough. "Review of Sensing Methodologies for Estimation of Combustion Metrics." Journal of Combustion 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/8593523.
Full textAbstract:
For reduction of engine-out emissions and improvement of fuel economy, closed-loop control of the combustion process has been explored and documented by many researchers. In the closed-loop control, the engine control parameters are optimized according to the estimated instantaneous combustion metrics provided by the combustion sensing process. Combustion sensing process is primarily composed of two aspects: combustion response signal acquisition and response signal processing. As a number of different signals have been employed as the response signal and the signal processing techniques can be different, this paper did a review work concerning the two aspects: combustion response signals and signal processing techniques. In-cylinder pressure signal was not investigated as one of the response signals in this paper since it has been studied and documented in many publications and also due to its high cost and inconvenience in the application.
36
Bang, Woorim, and Ji Won Yoon. "Power Grid Estimation Using Electric Network Frequency Signals." Security and Communication Networks 2019 (September 24, 2019): 1–11. http://dx.doi.org/10.1155/2019/1982168.
Full textAbstract:
The electric network frequency (ENF) has a statistical uniqueness according to time and location. The ENF signal is always slightly fluctuating for the load balance of the power grid around the fundamental frequency. The ENF signals can be obtained from the power line using a frequency disturbance recorder (FDR). The ENF signal can also be extracted from video files or audio files because the ENF signal is also saved due to the influence of the electromagnetic field when video files or audio files are recorded. In this paper, we propose a method to find power grid from ENF signals collected from various time and area. We analyzed ENF signals from the distribution level of the power system and online uploaded video files. Moreover, a hybrid feature extraction approach, which employs several features, is proposed to infer the location of the signal belongs regardless of the time that the signal was collected. Employing our suggested feature extraction methods, the signal which extracted from the power line can be classified 95.21% and 99.07% correctly when ENF signals have 480 and 1920 data points, respectively. In the case of ENF signals extracted from multimedia, the accuracy varies greatly according to the recorded environment such as network status and microphone quality. When constructing a feature vector from 120 data points of ENF signals, we could identify the power grid had an average of 94.17% accuracy from multimedia.
37
Gao, Chunxian, and Hui Liu. "Passive Localization for Mixed-Field Moving Sources." Polish Maritime Research 25, s2 (August 1, 2018): 69–74. http://dx.doi.org/10.2478/pomr-2018-0076.
Full textAbstract:
Abstract Due to the mobility of underwater equipment, high-precision underwater positioning technology will face two technical challenges: dealing with mixed-field signals composed of near-field signals and far-field signals; adapting to variable component of mixed-field signals considering the mobility of equipment. Under this condition, an effective method based on MUSIC is addressed in this paper. After distinguishing far-field signal subspace from mixed-field signal subspace, estimations of DOAs and powers of far-field sources are carried out. Then the corresponding far-field and noise signal components can be eliminated from the signal subspace. After that, based on path-following algorithm, modified 2D-MUSIC is performed for DOA and range estimations of near-field sources. The performance of the proposed method is verified and compared with the other methods through computer simulations. Reasonable classification of source types and accurate localization estimation can be achieved by using the proposed method.
38
Sienkowski, Sergiusz. "A Method of m-Point Sinusoidal Signal Amplitude Estimation." Measurement Science Review 16, no. 5 (October 1, 2016): 244–53. http://dx.doi.org/10.1515/msr-2016-0030.
Full textAbstract:
Abstract The paper presents a new and original method of m-point estimation of sinusoidal signal amplitude. In this method, an m-point estimator is calculated on the basis of m initial signal samples. The way the estimator is constructed is explained. It is shown that the starting point for constructing the estimator is two initial signal samples. Next, in order to determine the estimator general form, three and m subsequent initial signal samples appearing in a signal period are used. Some special cases of an estimator are considered. Such an estimator is compared with a four-point estimator proposed by Vizireanu and Halunga. It is shown that the m-point estimator makes it possible to estimate the signal amplitude more accurately.
39
Eschlwech, Philipp, and Erwin Biebl. "Target simulation for UHF RFID DoA estimation systems." Advances in Radio Science 17 (September 19, 2019): 109–18. http://dx.doi.org/10.5194/ars-17-109-2019.
Full textAbstract:
Abstract. In this work a new method for the evaluation of UHF RFID Direction of Arrival (DoA) estimation systems is developed and demonstrated. Instead of simulating the system performance or manually measuring it in realistic or ideal environments, a method for the evaluation of DoA systems using received signals produced by a target simulator is proposed. The simulator generates the signals for each channel of the DoA estimator by attenuating and phase shifting the signals of an UHF RFID chip to replicate the signal propagation conditions for a chosen tag distance and arrival angle. This combines the advantages of the simulative approach and real world evaluation: it is fast, reproducible and doesn't require special measurement environments. To facilitate this method, plane and spherical wave signal models for the simulation of RFID targets are derived, multichannel phase-shifting and attenuation hardware for the simulation of such signals is presented and a demonstrative evaluation of a RFID DoA estimation system is performed, replicating evaluation scenarios in non reflective and multipath environments.
40
Wang, Jiao Na, Chong Zhi Wang, Cheng Zhi Zeng, Pei De Yang, and Hai Rong Zheng. "A New Time Delay Estimation for Acoustic Elastography." Advanced Materials Research 718-720 (July 2013): 1006–11. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.1006.
Full textAbstract:
A new signal processing algorithm based on a Wavelet Transform is proposed for time delay estimation in acoustic elastography. The proposed estimator using correlation coefficient as a measure of the similarity of the two signal waveforms are reasonable. And we select the wavelet function most similar to the simulated ultrasonic signal as the mother wavelet. The practical simulation shows that the algorithm offers higher noise suppression capability and is able to implement ultrasonic signal time delay estimation.
41
Thanh, Hán Trọng, Nguyen Thanh Chuyen, and Nguyen Xuan Quyen. "DOA Estimation Method for CHAOS Radar System." Journal of Science and Technology: Issue on Information and Communications Technology 17, no. 12.2 (December 9, 2019): 35. http://dx.doi.org/10.31130/ict-ud.2019.84.
Full textAbstract:
CHAOS signal has been drawing a lot of research interest recently due to its performance in security systems. In this paper, an approach to estimate the direction of target for Distributed Chaos Radar System using Total Forward - Backward Matrix Pencil (TFBMP) algorithm. This algorithm works directly on signal samples of signals received by M – element Uniform Linear Antenna array. Therefore, the correlation between the received signals does not significantly impact on its performance and efficiency. This fact permits us to estimate not only wideband incoherent signals but also wideband coherent signals. Furthermore, this algorithm can also extract the Direction Of Arrival (DOA) with only one snapshot of signal, which means that the sampling frequency in real time receivers can be considerably reduced. The simulation results for DOA of incoming CHAOS signals using the proposed approach will be shown and analyzed to verify its performance.
42
Gudiškis, Andrius. "HEART BEAT DETECTION IN NOISY ECG SIGNALS USING STATISTICAL ANALYSIS OF THE AUTOMATICALLY DETECTED ANNOTATIONS / ŠIRDIES DŪŽIŲ NUSTATYMAS IŠ IŠKRAIPYTŲ EKG SIGNALŲ ATLIEKANT AUTOMATIŠKAI APTIKTŲ ATSKAITŲ STATISTINĘ ANALIZĘ." Mokslas – Lietuvos ateitis 7, no. 3 (July 13, 2015): 300–303. http://dx.doi.org/10.3846/mla.2015.787.
Full textAbstract:
This paper proposes an algorithm to reduce the noise distortion influence in heartbeat annotation detection in electrocardiogram (ECG) signals. Boundary estimation module is based on energy detector. Heartbeat detection is usually performed by QRS detectors that are able to find QRS regions in a ECG signal that are a direct representation of a heartbeat. However, QRS performs as intended only in cases where ECG signals have high signal to noise ratio, when there are more noticeable signal distortion detectors accuracy decreases. Proposed algorithm uses additional data, taken from arterial blood pressure signal which was recorded in parallel to ECG signal, and uses it to support the QRS detection process in distorted signal areas. Proposed algorithm performs as well as classical QRS detectors in cases where signal to noise ratio is high, compared to the heartbeat annotations provided by experts. In signals with considerably lower signal to noise ratio proposed algorithm improved the detection accuracy to up to 6%. Širdies ritmas yra vienas svarbiausių ir daugiausia informacijos apie pacientų būklę teikiančių fiziologinių parametrų. Širdies ritmas nustatomas iš elektrokardiogramos (EKG), atliekant QRS regionų, kurie yra interpretuojami kaip širdies dūžio ãtskaitos, paiešką. QRS regionų aptikimas yra klasikinis uždavinys, nagrinėjamas jau keletą dešimtmečių, todėl širdies dūžių nustatymo iš EKG signalų metodų yra labai daug. Deja, šie metodai tikslūs ir patikimi tik esant dideliam signalo ir triukšmo santykiui. Kai EKG signalai labai iškraipomi, QRS aptiktuvai ne visada gali atskirti QRS regioną, o kartais jį randa ten, kur iš tikro jo būti neturėtų. Straipsnyje siūlomas algoritmas, kurį taikant sumažinama triukšmo įtaka nustatant iš EKG signalų QRS regionus. Tam naudojamas QRS aptiktuvas, kartu prognozuojantis širdies dūžio atskaitą. Remiamasi arterinio kraujo spaudimo signalo duomenimis, renkama atskaitų statistika ir atliekama jos analizė.
43
Kechik, D. A., Yu P. Aslamov, and I. G. Davydov. "Method of estimation of frequency variation relying on estimation of shift of spectral peaks." «System analysis and applied information science», no. 1 (April 26, 2021): 53–61. http://dx.doi.org/10.21122/2309-4923-2021-1-53-61.
Full textAbstract:
Problem of estimation of variated frequency of components of polyharmonic signals has been arose. Three-dimensional time-frequency representation of signals is usually used to resolve this problem. But simple and reliable method of instantaneous frequency tracking is needed. Frequency tracking method based on estimation of shifts of peaks of spectrogram has been proposed in this paper. It is assumed that shift of spectral peaks of components of signal is proportional to variation of fundamental frequency. Logarithmic scaling of time-frequency representation is used to make spectral peaks equidistant. Temporal dependence of shift of spectral maximums is obtained using correlation of windowed spectrum at the first frame and spectrum of signal in the current window. Then obtained track is translated in linear scale. Proposed method does not estimate values of instantaneous frequency or central frequency of signal component but estimates its variation. Advantage of the method is that it can estimate frequency track even if range of frequency variation and its central value are known roughly or unknown at all. Multiple components do not interfere to estimate fundamental frequency variation. Reduction of bandwidth is recommended to increase accuracy of frequency track estimation, but analysis of time-frequency representation containing a few components is also possible. Dependency of performance of analysis of synthetic signals using the method on various signal to noise ratios under different conditions was estimated. Applicability of the method for vibrational diagnosing of rotary equipment was checked out using spectral interference method.
44
Tang, Peng Fei, Bin Yuan, Qian Qiang Lin, and Zeng Ping Chen. "Parameter Estimation of Multicomponent Cubic Phase Signals." Applied Mechanics and Materials 380-384 (August 2013): 3726–29. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3726.
Full textAbstract:
This paper presents an algorithm for estimating the parameters of multicomponent cubic phase signals. This algorithm combines the product generalized cubic phase function (PGCPF) and the product cubic phase function (PCPF) which are used to estimate the cubic phase coefficient and chirp rate of the cubic phase signal, respectively. This algorithm starts by estimating the parameters of the signal component with the strongest amplitude. Then removing the signal component whose parameters have been estimated, it proceeds to estimate the next signal component, and so on, until all of the signal components have been estimated. Numerical simulations are carried out to validate the performance of the proposed algorithm.
45
Petrović, Predrag B. "Algorithm for Simultaneous Parameter Estimation of A Multiharmonic Signal." Metrology and Measurement Systems 19, no. 4 (December 1, 2012): 693–702. http://dx.doi.org/10.2478/v10178-012-0061-4.
Full textAbstract:
Abstract Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. Differing from the existing parameter estimation algorithms either in power quality monitoring or in harmonic compensation, the proposed algorithm enables a simultaneous estimation of the fundamental frequency, the amplitudes and phases of harmonic waves. A pure sinusoid is obtained from an input multiharmonic input signal by finite-impulse-response (FIR) comb filters. Proposed algorithm is based on the use of partial derivatives of the processed signal and the weighted estimation procedure to estimate the fundamental frequency, the amplitude and the phase of a multi-sinusoidal signal. The proposed algorithm can be applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The simulation results verify the effectiveness of the proposed algorithm.
46
Wand, Weidong, Qunfei Zhang, Wentao Shi, Juan SHI, Weijie Tan, and Xuhu Wang. "Iterative Sparse Covariance Matrix Fitting Direction of Arrival Estimation Method Based on Vector Hydrophone Array." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 1 (February 2020): 14–23. http://dx.doi.org/10.1051/jnwpu/20203810014.
Full textAbstract:
Aiming at the direction of arrival (DOA) estimation of coherent signals in vector hydrophone array, an iterative sparse covariance matrix fitting algorithm is proposed. Based on the fitting criterion of weighted covariance matrix, the objective function of sparse signal power is constructed, and the recursive formula of sparse signal power iteration updating is deduced by using the properties of Frobenius norm. The present algorithm uses the idea of iterative reconstruction to calculate the power of signals on discrete grids, so that the estimated power is more accurate, and thus more accurate DOA estimation can be obtained. The theoretical analysis shows that the power of the signal at the grid point solved by the present algorithm is preprocessed by a filter, which allows signals in specified directions to pass through and attenuate signals in other directions, and has low sensitivity to the correlation of signals. The simulation results show that the average error estimated by the present method is 39.4% of the multi-signal classification high resolution method and 73.7% of the iterative adaptive sparse signal representation method when the signal-to-noise ratio is 15 dB and the non-coherent signal. Moreover, the average error estimated by the present method is 12.9% of the iterative adaptive sparse signal representation method in the case of coherent signal. Therefore, the present algorithm effectively improves the accuracy of target DOA estimation when applying to DOA estimation with highly correlated targets.
47
Zhou, Peng, and Chi Sheng Li. "A Novel Symbol Rate Estimation Algorithm for Phase Modulating Signals in Wireless Communications." Applied Mechanics and Materials 443 (October 2013): 392–96. http://dx.doi.org/10.4028/www.scientific.net/amm.443.392.
Full textAbstract:
In this paper, we proposed a new symbol rate estimation algorithm for phase shift keying (PSK) and qua drawtube amplitude modulation (QAM) signals in AWGN channel First we constructe a delay-multiplied signal, from which we obtaine the modulated information. Then we calculated the instantaneous autocorrelation of the delay-multiplied signal to pick out the phase jump. To eliminate the restriction of frequency resolution in fast Fourier transform, we performed a Chirp-Z transform to find out the exact spectral line which represente the symbol rate of the signal to be analyzed. Compared with the existing algorithms, it is a simple solution that has a better performance and accuracy in low signal-to-noise-ratio channel conditions. Simulation results show that the probability of relative estimating deviation below 0.1% reaches 100% and the average and standard variance of absolute estimation deviation are at the magnitude of 10-2 when SNR is over 2dB.
48
Chen, Hao, and Jun Hai Guo. "Radar Echo Parameter Estimation Using Sparse Time-Frequency Analysis Method." Applied Mechanics and Materials 543-547 (March 2014): 2229–33. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2229.
Full textAbstract:
The echoes of pulse radar from maneuvering targets are amplitude modulation and frequency modulation (AM-FM) signal. At present, the methods of estimating parameters of AM-FM signal are time-frequency analysis method, empirical mode decomposition and empirical wavelet transform based adaptive data analysis methods. This paper takes the idea of intrinsic mode function in guessing the initial phase, and applies the newly developed sparse time-frequency analysis method in AM-FM signal parameter estimation. Simulation results show that the estimating performance of this method in AM-FM signal is good under different SNR and it has low computational cost, and this method is applicable in target acceleration and velocity estimation.
49
Sebastian, Jilt, Mriganka Sur, Hema A. Murthy, and Mathew Magimai-Doss. "Signal-to-signal neural networks for improved spike estimation from calcium imaging data." PLOS Computational Biology 17, no. 3 (March 1, 2021): e1007921. http://dx.doi.org/10.1371/journal.pcbi.1007921.
Full textAbstract:
Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result in slowly-varying fluorescence signals with low temporal resolution. Estimating the temporal positions of the neuronal action potentials from these signals is a challenging problem. In the literature, several generative model-based and data-driven algorithms have been studied with varied levels of success. This article proposes a neural network-based signal-to-signal conversion approach, where it takes as input raw-fluorescence signal and learns to estimate the spike information in an end-to-end fashion. Theoretically, the proposed approach formulates the spike estimation as a single channel source separation problem with unknown mixing conditions. The source corresponding to the action potentials at a lower resolution is estimated at the output. Experimental studies on the spikefinder challenge dataset show that the proposed signal-to-signal conversion approach significantly outperforms state-of-the-art-methods in terms of Pearson’s correlation coefficient, Spearman’s rank correlation coefficient and yields comparable performance for the area under the receiver operating characteristics measure. We also show that the resulting system: (a) has low complexity with respect to existing supervised approaches and is reproducible; (b) is layer-wise interpretable, and (c) has the capability to generalize across different calcium indicators.
50
Wang, Zengke, Yi Li, and Wei Xu. "A Blind Parameter Estimation Method of Frequency Hopping Signal with Low SNR." International Journal of Circuits, Systems and Signal Processing 15 (April 5, 2021): 248–53. http://dx.doi.org/10.46300/9106.2021.15.28.
Full textAbstract:
In order to effectively estimate the parameters of the frequency hopping signals under low signal-to-noise ratio (SNR), a blind parameter estimation method based on the modified discrete time Wigner-Ville distribution (MDTWVD) is proposed. We choose a low order Chebyshev polynomial as the kernel function for reducing the cross-term. Then, the parameters of the frequency hopping signals are finally obtained from the MDTWVD. The simulation experiment results show that the method used in this paper can effectively and accurately estimate frequency hopping signals parameters, especially under low SNR condition compared with other estimating methods.