Showing papers on "Signal-to-noise ratio published in 1995"

Linearity enhancement of multibit /spl Delta//spl Sigma/ A/D and D/A converters using data weighted averaging

Abstract: A dynamic element matching algorithm, data weighted averaging, is introduced for use in multibit /spl Delta//spl Sigma/ data converters. Using this algorithm, distortion spectra from DAC linearity errors are shaped by first-order noise shaping, resulting in a dynamic range improvement of 9 dB/octave when DAC errors dominate. Combining this technique with random dithering nearly eliminates the aliasing of the DAC errors into the baseband. Simulations show that with only 1% element matching 110 dB signal-to-noise ratio (18 b) is achieved for a third-order 3-b modulator with an oversampling ratio of 128.

A fundamental limit on delay estimation using partially correlated speckle signals

Abstract: Delay estimation is used in ultrasonic imaging to estimate blood or soft tissue motion, to measure echo arrival time differences for phase aberration correction, and to estimate displacement for tissue elasticity measurements. In each of these applications delay estimation is performed using speckle signals which are at least partially decorrelated relative to one another. Delay estimates which utilize such data are subject to large errors known as false peaks and smaller magnitude errors known as jitter. While false peaks can sometimes be removed through nonlinear processing, jitter errors place a fundamental limit on the performance of delay estimation techniques. The authors apply the Cramer-Rao Lower Bound to derive an analytical expression which predicts the magnitude of jitter errors incurred when estimating delays using radio frequency (RF) data from speckle targets. The analytical expression presented includes the effects of signal decorrelation due to physical processes, corruption by electronic noise, and a number of other factors. Simulation results are presented which show that the performance of the normalized cross correlation algorithm closely matches theoretical predictions. These results indicate that for poor signal to noise ratios (0 dB) a small improvement in signal to noise ratio can dramatically reduce jitter magnitude. At high signal to noise ratios (30 dB) small amounts of signal decorrelation can significantly increase the magnitude of jitter errors. >

Analysis of multicomponent LFM signals by a combined Wigner-Hough transform

Abstract: The aim of the paper is the performance evaluation of a method for the analysis of mono- or multicomponent linear-frequency modulation (LFM) signals, based on the Hough transform of the Wigner-Ville distribution of the signals. A closed form expression is found for the signal-to-noise ratio and the parameter estimation accuracy. The overall method, as any nonlinear method, exhibits a threshold effect. Nevertheless, it is shown to be asymptotically efficient and offers a good rejection capability of the cross terms. >

Noise reduction filters for dynamic image sequences: a review

Abstract: In this paper, a thorough review is presented of noise reduction filters for digital image sequences Detailed descriptions of several spatiotemporal and temporal noise reduction algorithms are provided To aid in comparing between these different algorithms, we classify them based on their support (ie, 3-D or 1-D filter) and whether or not motion compensation is employed Several algorithms from each of the four categories are implemented and tested on real sequences degraded to various signal-to-noise ratios These experimental results are discussed and analyzed to determine the overall advantages and disadvantages of the four general classifications, as well as, the individual filters >

Reverse link, closed loop power control in a code division multiple access system

Abstract: The process of the present invention enables a mobile radiotelephone to operate at a 100% duty cycle while providing closed loop power control. The base station measures the signal to noise ratio of the signal from the mobile and compares that SNR with the SNR threshold values the base station has for each data rate the mobile is capable of transmitting. The base station then generates power control commands to instruct the mobile to change its power depending on the outcome of the comparisons.

Effects of undersampling on the proper interpretation of modulation transfer function, noise power spectra, and noise equivalent quanta of digital imaging systems

Abstract: The proper understanding of modulation transfer function (MTF), noise power spectra (NPS), and noise equivalent quanta (NEQ) in digital systems is significantly hampered when the systems are undersampled. Undersampling leads to three significant complications: (1) MTF and NPS do not behave as transfer amplitude and variance, respectively, of a single sinusoid, (2) the response of a digital system to a delta function is not spatially invariant and therefore does not fulfill certain technical requirements of classical analysis, and (3) NEQ loses its common meaning as maximum available SNR2 (signal-to-noise) at a particular frequency. These three complications cause the comparisons of MTF and NEQ between undersampled digital systems to depend on the frequency content of the images being evaluated. A tutorial of MTF, NPS, and NEQ concepts for digital systems is presented, along with a complete theoretical treatment of the above-mentioned complications from undersampling.

Estimation of amplitude and phase parameters of multicomponent signals

Abstract: This paper considers the problem of estimating signals consisting of one or more components of the form a(t)e/sup j/spl phi/(t/), where the amplitude and phase functions are represented by a linear parametric model. The Cramer-Rao bound (CRB) on the accuracy of estimating the phase and amplitude parameters is derived. By analyzing the CRB for the single-component case, if is shown that the estimation of the amplitude and the phase are decoupled. Numerical evaluation of the CRB provides further insight into the dependence of estimation accuracy on signal-to-noise ratio (SNR) and the frequency separation of the signal components. A maximum likelihood algorithm for estimating the phase and amplitude parameters is also presented. Its performance is illustrated by Monte-Carlo simulations, and its statistical efficiency is verified. >

A comparison of several algorithms for SAR raw data compression

Abstract: Proposes new algorithms for synthetic aperture radar (SAR) raw data compression and compares the resulting image quality with the quality achieved by commonly used methods. The compression is carried out in time and frequency domain, with statistic, crisp, and fuzzy methods. The algorithms in the time domain lead to high resolution and a good signal-to-noise ratio, but they do not optimize the performance of the compression according to the frequency envelope of the signal power in both range and azimuth directions. The hardware requirements for the compression methods in the frequency domain are significant, but a higher performance is obtained. Even with a data rate of 3 bits/sample, a satisfactory phase accuracy is achieved which is an essential parameter for polarimetric and interferometric applications. Preliminary analysis concerning the suitability of the proposed algorithms for different SAR applications shows that the compression ratio should be adaptively selected according to the specific application. >

Influence of RF oscillators on an OFDM signal

Abstract: This paper explains the mechanisms that lead to a degradation of an OFDM signal because of the phase noise of the RF oscillators. An approach for easy calculation of SNR, independent of carrier numbers, will be given. This SNR approach uses a plot of the phase noise power density for the calculation. The theoretical results lead to an improved synthesizer concept. Values of SNR and BER will be given for the new synthesizer concept. >

The estimation of time delay and Doppler stretch of wideband signals

Abstract: The problem of estimating the time delay and the Doppler stretch for wideband signals from a moving target is considered. The Cramer-Rao bound and the maximum likelihood (ML) method of estimation are derived. Due to the uncertainty of the reflection coefficient, the ML method may not be practicable. An alternative method involving the location of the peak of the wideband ambiguity function of the signal is suggested. The performance of the method is analysed, and, under high signal-to-noise ratios (SNRs), the method is asymptotically unbiased, and the variances of the estimates are closed to the Cramer-Rao bound for a large variety of signals. Optimum signals for the joint estimation of the time delay and the Doppler stretch under practical constraints are designed and, through computer simulations, their performance are shown to be superior to the commonly used signals. >

A selection combining scheme for RAKE receivers

Abstract: A selection combining scheme for a RAKE receiver operating over a multipath fading channel is introduced, by which the m largest channel outputs are selected instead of only the largest one, as in the conventional selection combining receiver. Expressions for the error probability of this scheme for an exponential multipath intensity profile (MIP) with arbitrary decay constant are found by first deriving the joint density function of the m ordered channel outputs, then averaging the conditional error probability over the joint density function. The performance is compared with that of maximal ratio combining in both an interference-limited and a noise-limited environment. The interference-limited environment chosen is a multicell CDMA system. Numerical results show that the performance of the selection combining scheme is superior to that of conventional selection combining, and can be very close to that of maximal ratio combining, depending upon the value of m and the rate of decay of the MIP.

Classification of co-channel communication signals using cyclic cumulants

Abstract: Traditional methods of signal classification, including phase and frequency histograms, modulus measurements, and power-spectrum measurements, fail when the signal-to-noise ratio is sufficiently low or when there are interfering signals present. These methods fail because the interfering signals and noise contribute substantially to the measured values of the classification features, thereby obscuring the contribution to the measurement from the signal of interest. The required signal selectivity of classification features for this situation can, in some instances be provided by features based on the cyclostationarity of both the signal of interest and the interferers. A set of cyclic-cumulant-based features for signal classification is proposed and analyzed, and results of classification experiments using simulated data are presented. The simulation results reveal that each of a number of spectrally overlapping signals can be successfully classified by measuring and processing the proposed features.

Detection of Forced Climate Signals. Part 1: Filter Theory

Abstract: This paper considers the construction of a linear smoothing filter for estimation of the forced part of a change in a climatological field such as the surface temperature. The filter is optimal in the sense that it suppresses the natural variability or “noise” relative to the forced part or “signal” to the maximum extent possible. The technique is adapted from standard signal processing theory. The present treatment takes into account the spatial as well as the temporal variability of both the signal and the noise. In this paper we take the signal's waveform in space-time to be a given deterministic field in space and lime. Formulation of the expression for the minimum mean-squared error for the problem together with a no-bias constraint leads to an integral equation whose solution is the filter. The problem can be solved analytically in terms of the space-time empirical orthogonal function basis set and its eigenvalue spectrum for the natural fluctuations and the projection amplitudes of the sig...

Experimental results of localization of moving underwater signal by adaptive beamforming

Abstract: The problem of weak moving signal localization and tracking in the presence of single motionless strong interference is investigated using real data of an underwater experiment in the Baltic sea (Sept. 1990) with a horizontal receiving array of 64 hydrophones and with two independent powerful narrowband sources imitating the signal and interference. Three simple adaptive beamforming methods were employed for the experimental data processing. The first one is based on the well-known projection approach to adaptive beamforming, the second method uses the adaptive canceler approach (also termed the dipole pattern method), and the third method combines these approaches. The signal-to-interference power ratio (SIR) threshold of the signal localization and tracking is evaluated by a special technique, which allows examination of the considered algorithms with change of the SIR in consecutive order. The results of the data processing show the high possibilities of signal localization in the presence of strong interference. The combined method performs better than the methods considered and enables localization of the signal source up to an SIR/spl sime/-25 dB. >

A methodology for quantitative performance evaluation of detection algorithms

Abstract: We present a methodology for the quantitative performance evaluation of detection algorithms in computer vision A common method is to generate a variety of input images by varying the image parameters and evaluate the performance of the algorithm, as algorithm parameters vary Operating curves that relate the probability of misdetection and false alarm are generated for each parameter setting Such an analysis does not integrate the performance of the numerous operating curves In this paper, we outline a methodology for summarizing many operating curves into a few performance curves This methodology is adapted from the human psychophysics literature and is general to any detection algorithm The central concept is to measure the effect of variables in terms of the equivalent effect of a critical signal variable, which in turn facilitates the determination of the breakdown point of the algorithm We demonstrate the methodology by comparing the performance of two-line detection algorithms

Two algorithms for adaptive retrieval of slowly time-varying multiple cisoids in noise

Abstract: Two algorithms for tracking parameters of slowly varying multiple complex sine waves (cisoids) in noise (the multiple frequency tracker and the adaptive notch filter) are described. For high signal-to-noise ratio (SNR), the properties of the algorithms (i.e., stability, noise rejection, and tracking speed) are studied analytically using a linear filter approximation technique. The tradeoff between noise rejection and tracking error for both algorithms is shown to be similar. Different choices of the design variables are discussed, namely (i) minimal mean-square estimation error for random walk modeled frequency variations and (ii) minimal stationary estimation variance subject to a given tracking delay. >

Blind source detection and separation using second order non-stationarity

Abstract: We address the problem of using an array of sensors for detecting a narrow band source and separating its signal from unwanted disturbance signals, that is jammers and noise. The power of the desired signal is assumed to move from one level to another. This second order non-stationarity occurs, for instance, in frequency hopping systems, and more generally, at the beginning or at the end of any communication. We derive a method based on the generalized eigenstructure of two covariance matrices which requires no a priori knowledge of the array manifold, but only second order stationarity of the disturbance signals. The loss in signal to interference plus noise ratio (SINR) due to finite sample effect is calculated in closed form at the first order and validated by simulations. This last result shows that the method gives interesting performance in a wide range of situations.

Performance analysis of the minimum variance beamformer

Abstract: We present an analysis of the signal-to-interfere-plus-noise ratio (SINR) at the output of the minimum variance beamformer. The analysis yields an explicit expression for the SINR in terms of the different parameters affecting the performance, including the signal-to-noise ratio (SNR), the interference-to-noise ratio (INR), the signal-to-interference ratio (SIR), the angular separation between the desired signal and the interference, the array size and shape, the correlation between the desired signal and the interference, and the finite sample size.

Blind fractionally-spaced equalization of noisy FIR channels: adaptive and optimal solutions

Abstract: Blind fractionally spaced (FS) equalizers only require output samples taken at rates higher than the symbol rate to estimate the channel or the equalizer. Methods for finding FIR zero-forcing equalizers directly from the observations are described and adaptive versions are developed. In contrast, most methods require channel estimation as a first step to estimating the equalizer. For the noisy channel, the FIR equalizer is shown to be minimum mean-square error. FS equalizers are not unique, thereby allowing optimum zero-forcing parametric FIR or nonparametric IIR equalizers to be derived such that in addition to being zero-forcing, they also minimize the noise power at the output. These optimum equalizers do not depend on the input distribution and are also valid for deterministic inputs. Finally, if the additive noise is white, they do not depend on the SNR.

Speed detection method

Abstract: An improved remote speed sensing technique is described which improves performance reliability by increasing the relative signal to noise ratio of a speed detector compared to that of a vehicle radar detector, by localizing at least one axis of the illuminating radiation to an angular region which is comparable to or within the subtence of the target vehicle, while minimizing illumination of a radar detector on the target vehicle.

Fundamental noise limits for miniature acoustic and vibration sensors

Abstract: Recent technological advances in microfabrication and fiber optics have made practical the construction of very small, sensitive sensors for acoustic or vibration measurements. As the sensitivity is increased or the size is decreased, a sensor becomes more susceptible to mechanical noise resulting from molecular agitation. Traditional noise analysis is often focused exclusively on electrical or optical noise ; consequently, mechanical-thermal noise may not be considered in new types of sensors until the prototype testing reveals an unexpectedly high noise floor. Fortunately, mechanical-thermal noise is relatively easy to estimate early in the design process because the equivalent noise force is only a function of the temperature and the mechanical losses in the sensor. There are a number of specific techniques that are applicable for evaluating either the total mechanical-thermal noise or the spectral distribution of that noise for simple or complex sensors. These techniques are presented and, in addition, a summary of other noise components is given in the context of design guidelines for high-sensitivity sensors.

Quantum nondemolition demonstration via repeated backaction evading measurements.

Abstract: Repeated backaction evading measurements have been performed for the first time. The first backaction evading device prepares the field state while the second one measures it again. The conditional variance of the signal at the output of the first device given the measurement is 1.8 dB below the shot noise and the signal to noise ratio transfer coefficient is 1.34. The conditional variance of the final signal given the first device measurement is also 1.8 dB below the shot noise and the normalized correlation between the two meter outputs is 0.3. These figures are clearly in the quantum regime, and they constitute a full demonstration of the quantum nondemolition principle.

Filtering noncorrelated noise in impedance cardiography

Abstract: Impedance cardiography (ICG) may be altered by noises as respiration and movement artifacts, mainly during exercise. In this work, a scaled Fourier linear combiner (SFLC) event-related to the R-R interval of ECG is proposed. It estimates the deterministic component of the impedance cardiographic signal and removes the noises uncorrelated to this interval. The impedance cardiographic signal is modeled as Fourier series with the coefficients estimated by the least mean square (LMS) algorithm. Simulations have been carried out to evaluate the filter performance for different noise conditions. Moreover, the method capability to remove uncorrelated noises was also examined in physiological data obtained in rest and exercise, by synchronizing respiration and pedalling with a metronome. Analyzing the ICG power spectrum, it was concluded that the proposed filter could remove the noises that are not synchronized with heart rate. >

Echelle Spectroscopy with a CCD at Low Signal-to-Noise Ratio

Abstract: The measurement of some physical parameters of astronomical objects can only be carried out with high resolution spectra. Unfortunately the high dispersion of the light on the detector restricts such observations to relatively bright sources. However, some spectral information can be concentrated into a single spectral “line” by a cross-correlation algorithm, allowing the observation of fainter objects. Such a technique, taken from the CORAVEL optical correlation, is presented. A complete description of the errors of the correlation function parameters is given and the minimum signal-to-noise ratio is also discussed Finally, a short investigation of the best resolution needed to observe efficiently radial velocities and velocity broadenings is made.

Pulse elongation and deconvolution filtering for medical ultrasonic imaging

Abstract: Range sidelobe artifacts which are associated with pulse compression methods can be reduced with a new method composed of Pulse Elongation and Deconvolution (PED). Both approaches yield similar signal-to-noise ratio (SNR) improvements. The deconvolution is implemented as a stabilized inverse filter. The excitation wave form is optimized in a minimum mean square error (MMSE) sense. An analytical expression for the power spectrum of the optimal pulse is presented and several techniques to numerically optimize the excitation pulse are shown. The effects of PED are demonstrated in computer simulations as well as ultrasonic images.

Phase-only matched filtering with dual liquid-crystal spatial light modulators

Abstract: A real-time optical processing system with dual liquid-crystal spatial light modulators is presented that have been used as an amplitude input and a multilevel phase-only filter, respectively. Numerical calculations are performed for a gray-level and binarized amplitude- phase correlations. An improvement of performance criteria such as discrimination capability, light efficiency, and signal-to-noise ratio has been made for an amplitude in a binary mode to phase correlator. The higher the threshold level of binarized objects is, the better performance criteria produce. Optical experimental results supporting with calculations are described.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Estimating noise characteristics from flight test data using optimal Fourier smoothing

Abstract: A technique based on Fourier series analysis was developed to separate signal from noise for flight test data. This was done with an optimal filter designed in the frequency domain. The method is general, and separates signal and noise based on the spectral content of the measurement time history. Smoothed time histories with no time lag were computed, and noise characteristics were accurately estimated. The technique can be used independently of other procedures, and does not require assumptions about the independence of the noise processes or the frequency content of the measurements. Simulated data was used to demonstrate the technique and to evaluate the accuracy of estimated noise characteristics. For 20 simulation cases, noise standard errors were estimated within 5% of the true values. Flight test data from a lateral maneuver of the F-18 High Alpha Research Vehicle was then analyzed. The theoretical analysis was shown to be sound for both simulated data and flight test data.

Comparing Recognition of Distorted Speech Using an Equivalent Signal-to-Noise Ratio Index

Abstract: An index of equivalent performance in noise was developed to compare recognition in different forms of speech distortion. Speech-recognition performance of young and elderly listeners with and with...