Download or read book Adaptive Detection of a Known Signal in Non Gaussian Noise written by Steven V. Czarnecki and published by . This book was released on 1982 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design of a locally optimal detector for a known signal in non-Gaussian noise is discussed. The optimal detector non-linearity is approximated adaptively in the noise pdf tail region, and a polynomial is used to approximate the non-linearity near the mean. Examples for several different noise environments are presented, showing in these cases that the adaptive detector is able to achieve a high level of performance.
Download or read book Methods of Computer Aided Analysis of Non Gaussian Noise and Application to Robust Adaptive Detection written by I. Kirsteins and published by . This book was released on 1984 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a methodology for the modeling of certain non-stationary and non-gaussian random time series data with application to weak signal detection. Some components of the noise, which give it its nongaussian characteristics, can be individually modeled, synthesized and subtracted to provide a gaussian residual. Further, it is shown that this process can also be carried out when signals are present. The proposed methodology is applied to some Arctic Acoustic data using a combination of adaptive differential quantization and adaptive signal estimation algorithms based on singular-value-decomposition of a data matrix which we have developed. The combination of adaptive differential quantization with low-rank approximations to data matrices or estimated covariance matrices is believed to be a new and effective method for multivariable, robust, adaptive detection.
Download or read book Signal Detection in Non Gaussian Noise written by Saleem A. Kassam and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a unified treatment of a class of problems of signal detection theory. This is the detection of signals in addi tive noise which is not required to have Gaussian probability den sity functions in its statistical description. For the most part the material developed here can be classified as belonging to the gen eral body of results of parametric theory. Thus the probability density functions of the observations are assumed to be known, at least to within a finite number of unknown parameters in a known functional form. Of course the focus is on noise which is not Gaussian; results for Gaussian noise in the problems treated here become special cases. The contents also form a bridge between the classical results of signal detection in Gaussian noise and those of nonparametric and robust signal detection, which are not con sidered in this book. Three canonical problems of signal detection in additive noise are covered here. These allow between them formulation of a range of specific detection problems arising in applications such as radar and sonar, binary signaling, and pattern recognition and classification. The simplest to state and perhaps the most widely studied of all is the problem of detecting a completely known deterministic signal in noise. Also considered here is the detection random non-deterministic signal in noise. Both of these situa of a tions may arise for observation processes of the low-pass type and also for processes of the band-pass type.
Download or read book Adaptive Detection for Multichannel Signals in Non Ideal Environments written by Zeyu Wang and published by CRC Press. This book was released on 2024-06-14 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically presents adaptive multichannel signal detection in three types of non-ideal environments, including sample-starved scenarios, signal mismatch scenarios, and noise plus subspace interference environments. The authors provide definitions of key concepts, detailed derivations of adaptive multichannel signal detectors, and specific examples for each non-ideal environment. In addition, the possible future trend of adaptive detection methods is discussed, as well as two further research points – namely, the adaptive detection algorithms based on information geometry, and the hybrid approaches that combine adaptive detection algorithms with machine learning algorithms. The book will be of interest to researchers, advanced undergraduates, and graduate students in sonar, radar signal processing, and communications engineering.
Download or read book Nearly Optimal Detection of Signals in Non gaussian Noise written by Steven V. Czarnecki and published by . This book was released on 1983 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation addresses the problem of finding nearly optimal detector structures for non-Gaussian noise environments. It is assumed that the noise statistics are unknown except for a very loose characterization. Under this condition, the goal is to study adaptive detector structures that are simple, yet capable of high levels of performance. Attention is focused on the discrete-time locally optimal detector for a constant signal in independent, identically distributed noise. A definition for non-Gaussian noise is given, several common univariate density models are exhibited, and some physical non-Gaussian noise data is discussed. Two approaches in designing adaptive detector nonlinearities are presented, where it is assumed that the noise statistics are approximately stationary. Both proposals utilized simple measurements of the noise behavior to adapt the detector, and in several examples the adaptive detectors are shown capable of attaining nearly optimal performance levels. A simulation is presented demonstrating their successful application.
Download or read book Adaptive Detection in Non Stationary Interference Part 3 written by and published by . This book was released on 1987 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of Parts I and II of the report with this title has been extended into two directions. In the first case, the performance of an adaptive system with respect to signals arriving from directions other than the steering direction is evaluated. It is shown that these signals are reflected more strongly than would be suggested by the sidelobe levels of the adaptive patterns themselves. In the other case, the detection problem is generalized to include the detection of signals known only to lie in a subspace of the space of steering vectors. Again, performance is derived and the penalty associated with the greater uncertainty of the signal model is shown to be small. The analysis of Part I essentially repeated here, both to keep this report self-contained and to present an alternative version of the basic derivations. Keywords: Adaptive antennas; Signal to noise ratio; Maximum likelihood detection statistical hypothesis testing; Signal to noise ratio; Gaussian noise.
Download or read book Adaptive Signal Detection in Non Gaussian Interference written by Nicholas Biagio Pulsone and published by . This book was released on 1997 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Adaptive Detection and Estimation of Nearly Periodic Signals written by Thomas G. Kincaid and published by . This book was released on 1969 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report proposes a design of an adaptive receiver for the detection and estimation of nearly periodic signals in additive Gaussian noise. A nearly periodic signal is defined to be a sample function of a Gaussian random process which can be divided into equal length intervals, called periods, in such a manner that the correlation between periods decreases exponentially with their separation. The receiver computes a low signal-to-noise ratio conditional likelihood ratio from which the observer must make decisions. The likelihood ratio is conditional because the receiver estimates any unknown parameters necessary for the computation of the true likelihood ratio. Thus the receiver can only compute a likelihood ratio conditioned upon these estimates being the true values of the unknown parameters. The receiver consists of pre-emphasis filters followed by a comb filter, energy detector, and weighted summation. A theoretical evaluation of the receiver, in terms of ROC curves, is made for the special case of nearly periodic signals with statistically independent equal-strength harmonics in white noise of known power. (Author).
Download or read book An Adaptive Detection Algorithm written by Edward J. Kelly and published by . This book was released on 1986 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general problem of signal detection in a background of unknown Gaussian noise is addressed, using the techniques of statistical hypothesis testing. Signal presence is sought in one data vector, and another independent set of signal-free data vectors is available which share the unknown covariance matrix of the noise in the vector. A likelihood ratio decision rule is derived and its performance evaluated in both the noise-only and signal-plus-noise cases.
Download or read book Adaptive Antennas and Receivers written by Melvin M. Weiner and published by CRC Press. This book was released on 2018-10-08 with total page 1240 pages. Available in PDF, EPUB and Kindle. Book excerpt: In our modern age of remote sensing, wireless communication, and the nearly endless list of other antenna-based applications, complex problems require increasingly sophisticated solutions. Conventional antenna systems are no longer suited to high-noise or low-signal applications such as intrusion detection. Detailing highly effective approaches to non-Gaussian weak signal detection, Adaptive Antennas and Receivers provides an authoritative introduction to state-of-the-art research on the modeling, testing, and application of these technologies. Edited by innovative researcher and eminent expert Melvin M. Weiner, this book is the first to integrate three advanced approaches to non-Gaussian weak signal detection into a single reference: homogeneous partitioning of the surveillance volume, adaptive antennas, and adaptive receivers. Comprising self-contained chapters contributed by renowned experts such as Donald D. Weiner and Ronald Fante, each chapter explores the techniques, theoretical basis, and applications of the approach under discussion. The book considers signal detection in the presence of external noise such as clutter residue, interference, atmospheric noise, jammers, external thermal noise, in vivo surrounding tissue, and camouflaging material, making it ideal for use across a broad spectrum of applications. This authoritative reference supplies more than 750 figures and tables, 1460 equations, and 640 references. Adaptive Antennas and Receivers is an ideal resource for improving performance in surveillance, communication, navigation, artificial intelligence, computer tomography, neuroscience, and intrusion detection systems, to name only a few.
Download or read book High Level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter Volume 5 A New Approach to Radar Detection Based on the Partitioning and Statistical Characterization of the Surveillance Volume written by and published by . This book was released on 1995 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: In signal processing applications it is common to assume Gaussian statistics in the design of optimal signal processors. However, non-Gaussian processes do arise in many situations. For example, measurements reveal that radar clutter may be approximated by either Weibull, K-distributed, Lognormal, or Gaussian distributions depending upon the scenario. When the possibility of a non-Gaussian problem is encountered, the question as to which probability distributions should be utilized in a specific situation for modeling the data needs to be answered. In practice, the underlying probability distributions are not known a priori. Consequently, an assessment must be made by monitoring the environment. Another consideration is that radar detection problems can usually be divided into strong, intermediate, and weak signal cases. Hence, the system that monitors a radar environment must be able to subdivide the surveillance volume into weak background noise and clutter patches in addition to approximating the underlying probability distributions for each patch. This is in contrast to current practice where a single robust detector, usually based on the Gaussian assumption, is employed. The objective of this work is to develop techniques that monitor the environment and select the appropriate detector for processing the data. The main contributions are: (1) an image processing technique is devised which enables partitioning of the surveillance volume into background noise and clutter patches, (2) the Ozturk algorithm is used to identify suitable approximations to the probability density function for each clutter patch, and (3) rules to be used with an expert system shell under development at the University of Massachusetts and Boston University.
Download or read book Signal Detection in Non Gaussian Noise Environments written by Pankaj Srivastava and published by . This book was released on 1991 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Paysages v g taux naturels written by and published by . This book was released on 1785 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Adaptive Technique for Multiple Signal Detection and Identification written by John W Sammon (Jr) and published by . This book was released on 1967 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of detecting and identifying multiple signals which are corrupted by independent additive noise is mathematically formulated. It is explicitly assumed that (1) the epoch and time duration of the signals are known, (2) the statistics of the corrupting noise are known, (3) the number of signals and their individual shapes are not known, and (4) the a priori probabilities of the occurrence of the individual signals are not known. An adaptive technique is developed to determine (1) the number of signals, (2) the signal shapes, and (3) the relative frequency of each signal's occurrence. The adaptive procedure uses only the observations made at the receiver output. Computer simulated results are given for the case of Gaussian noise. These results clearly indicate that approximate detection and identification can be achieved adaptively. (Author).
Download or read book Robust Detection of Fading Narrow Band Signals in Non Gaussian Noise written by M. Weiss and published by . This book was released on 1985 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report, we study procedures for robust detection of slowly fading narrowband signals in nearly Gaussian noise, a common model for radar/sonar systems. For the classical quadrature matched filter test, we introduce an uncertainty about the envelope statistic and develop a robust test for this one-sample situation. It is demonstrated that this test is capable of protecting only against relatively weak contaminations. With uncertainty taken directly on the noise samples, we develop an estimation-detection theoretic approach: The detection statistic preserves the structure of the quadrature matched filter, but in place of the linear sample mean, a minimax robust estimator of the random amplitude is substituted. This test is shown to be asymptotically maximin optimal (in the sense of Huber) for a wide family of decision rules and for several common target signal models. Originator supplied keywords include: robust detection; non-Gaussian detection; fading narrow-band signals; combined robust estimation-detection; scale invariance; and adaptive threshold.
Download or read book Adaptive Signal Detection for the Optimal Communications Receiver written by Robert H. Baran and published by . This book was released on 1983 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of weak signal reception in non-Gaussian noise has been shown to have an optimal solution the structure of which involves a no-memory nonlinearity followed by a matched filter. The shape of the nonlinearity is completely determined by the noise amplitude probability density function. The assumptions underlying this theory are examined and applications to radio communication in atmospheric noise are considered. Since the likelihood ratio test on which the theory is based is not a robust procedure, the receiver system must adjust the shape of the nonlinearity to account for the statistics of the prevailing noise environment. (Author).
Download or read book The Detection of Signals in Non Gaussian Noise written by Norman Solat and published by . This book was released on 1964 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
