If the signal is non gaussian, np detector does not give promising results. There have been different statistical distributions proposed to model such impulsive noise such as the. In order to optimize signal detection in nongaussian environments, the work is addressed to provide realistic modeling of a generic noise probability density. Joint signal parameter estimation in nongaussian noise by. For this reason, the main goal of this dissertation is to develop statistical signal processing algorithms for the detection and modulation classi cation of signals in radio channels where the additive noise is non gaussian. The detection of a known deterministic signal in unknown nongaussian noise is a problem of great interest in many fields, such as communications and image processing. The model depends on few parameters which can be estimated quickly and easily, and so general to be able to describe many kinds of noise such as symmetric or asymmetric. Receiver noise noise is the unwanted electromagnetic energy that interferes with the ability of the receiver to detect the wanted signal. In most practical situations, the signal is nongaussian or becomes nongaussian after going through a nonlinear propagation media. On optimal threshold and structure in threshold system based detector.
Kassam, signal detection in nongaussian noise, springerverlag, new york, 1988. Hosbased noise models for signaldetection optimization in nongaussian environments a. This comparison is meaningful since the linear detectors are often used even when the noise is a priori known to be nongaussian. Red i am attaching screens to be processed to noise. Pro auto system where pdf, fundamental analysis applied. Orthogonal polynomial approximation, signal detection and estimation, non gaussian noise 1 introduction transformation method. We investigate the non gaussian signal detection in gaussian noise. Pdf radar signal detection in nongaussian noise using rbf. Radar signal detection in nongaussian noise using rbf neural network article pdf available in journal of computers 31 august 2008 with 308 reads how we measure reads. Regazzoni2 department of biophysical and electronic engineering dibe, university of genoa via allopera pia 11a 16145 genova italy phone.
Vincent poor essential background reading for engineers and scientists working in such fields as communications, control, signal, and image processing, radar and sonar, radio astronomy, seismology, remote sensing, and instrumentation. Nongaussian noise benefits for coherent detection of. Robust multiuser detection in nongaussian channels. The performance of these linear and nonlinear detectors have been compared in a bayesian and in a neymanpearson detection strategy when the signal to be detected and the native nongaussian noise are known a priori. Kassam has a number of ieee papers on the topic, and since you are a student, both the book and papers are probably available.
Under what circumstances is a nonuniform quantizer. Signal detection by generalized detector in compoundgaussian. Signal detection in nongaussian noise, sprin ger verlag, 1988. The principle is introduced, the gps signal detection structure is described, the ambiguity of initial pseudorandom noise prn code. Generalized detector, constant false alarm rate, detection performance, gaussian noise, radar.
The problem of detecting the presence of a random signal embedded in additive correlated nongaussian noise modeled as a spherically invariant random process is. Hosbased noise models for signaldetection optimization in. One of the primary uses of higher order statistics in signal processing has been for detecting and estimation of non gaussian signals in gaussian noise of unknown covariance. Comparison of bistable systems and matched filters in non. Detection of random signals in additive noise springerlink. Dec 11, 2014 signal detection under weakly nongaussian noise distribution since gaussian noise is fully characterized by the covariance matrix or the twobody correlation function, any nonvanishing higherorder cumulants or reduced correlation functions are signatures of nongaussianity of the probability distribution function pdf, p x. Additionally, however, a brief discussion of narrowband random signal detection in narrowband noise is included in this chapter. Introduction the detection of signals in the presence of noise is a significant problem that arises in various signal processing applications, such as radar and sonar systems. Kassam, signal detection in nongaussian noise, springer. Detection of narrowband signals in spherically invariant. Noiseenhanced nonlinear detector to improve signal detection.
Kassam, signal detection in nongaussian noise, springerverlag. Kassam, signal detection in nongaussian noise, springer verlag. Detection of binary signal in gaussian noise pdf investing post. Hosbased generalized noise pdf models for signal detection. The new result in this paper is the use of the nongaussian noise. In this suboptimal detection context, a classical approach 2,3 is to implement a non linear scheme composed of a nonlinear preprocessor followed by the linear scheme that would be used in a gaussian noise. A robust detector of known signal in nongaussian noise. By using this noise model, the robustness of various detection strategies can be assessed. Gps signal detection under multiplicative and additive noise. An introduction to signal detection and estimation springer. If the signal is nongaussian, np detector does not give promising results. In the signal detection and estimation problems, we often assume that the.
Polynomial transformation method for nongaussian noise. Different models can also be used to model different noisetypes such as the gaussian, poisson, impulsive, nongaussian models among others 3. Detection of narrowband signals with random phase angles. Signal detection and modulation classi cation in nongaussian. It can be applied either under the ideal but often not realistic assumption of gaussian background noise, or on the basis of realistic statistical models of channel noise. Nongaussian impulsive noise has been used to model different noise sources in many communication systems, such as multiple access interference, manmade electromag netic noise, car ignition and mechanical switching and many others.
In most practical situations, the signal is non gaussian or becomes non gaussian after going through a nonlinear propagation media. Ndimensional probability density function is binary orthogonal modu lation on. Pdf optimum reception in nongaussian electromagnetic. For this purpose, a novel gps signal detection scheme based on high order cyclostationarity is proposed. Pdf signal detection in nongaussian noise by a kurtosisbased. The locally optimum lo criterion is selected from a large number of detection criteria.
A general introduction to signal detection in non gaussian noise can be found in ref. In such nongaussian interference, the detection key is to. Signal detection and estimation artech house radar library hardcover. In this paper, we generate colored gaussian noise, colored nongaussian noise.
Procedia apa bibtex chicago endnote harvard json mla ris xml iso 690 pdf. Detection and estimation of chirp signals in nongaussian. This is the detection of signals in additive noise which is not required to have gaussian probability density functions in its statistical description. Gaussian pdf, the middleton class a pdf, and some such. Since gaussian noise is fully characterized by the covariance matrix or the twobody correlation function, any nonvanishing higherorder cumulants or reduced correlation functions are signatures of nongaussianity of the probability distribution function pdf, px.
Actually, in many real applications in the fields of seismology, underwater acoustics, electromagnetic telecommunications, etc. Sequential strategy to solve the problem of sequential detection for unknown 1, wald proposed two possible solutions. Radar signal detection in nongaussian noise using rbf neural. However, the computational complexity of ml detection is quite high, and therefore, effective nearoptimal multiuser detection techniques in nongaussian noise are needed. We will further assume that both xn and n have zero means and that they are statistically independent. Introduction the detection of signals in the presence of noise is a significant problem that arises in various signal processing applications, such as. The obtained detection structure does not depend on the noise univariate probability density function pdf. Here our signal will be modeled entirely as a non deterministic random process. In this paper, we consider the mai mitigation problem in dscdma channels with nongaussian ambient noise. Regazzoni dibe, university of genoa, genoa, italy abstract two pdf models suitable for describing nongaussian iid noise are introduced. W and divergence with binary communication system where cannot. The principle is introduced, the gps signal detection structure is described, the ambiguity of initial pseudorandom noise prn code phase and doppler shift of gps signal is analysed. The authors discuss the need to provide a realistic model of a generic noise probability density function pdf, in order to optimize the signal detection in nongaussian environments. Generally, nongaussian detection problems are analytically intractable and.
Kassam conditional tests in nonparametric detection in nonparametric methods in. Possible applications to noise pdf modeling are the optimization of signal detection, parameter estimation, classification, etc. Some univariate noise probability density function models. However, while this is a good model for thermal noise, various studies have shown that the noise experienced in most radio channels, due to a variety of manmade and natural. The detector has been tested and applied on an underwater. Following the scheme of our development so far, the focus will be on the detection of a random signal in additive white noise.
It is noted that, at the uniform noise level, the detection efficacy in eq. Random signal detection in correlated nongaussian noise. The essential feature of stochastic resonance is the performance enhancement of nonlinear systems by an appropriate nonzero noise level 519. For this reason, the main goal of this dissertation is to develop statistical signal processing algorithms for the detection and modulation classi cation of signals in radio channels where the additive noise is. This paper deals with noncoherent discretetime detection of a narrowband signal subject to slow and nonselective fading and embedded in correlated nongaussian noise modeled as a spherically invariant random process whose modulating random variable is continuous. Pdf some univariate noise probability density function models. Pdf signal detection in nongaussian noise by a kurtosis. 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. Signal detection and modulation classi cation in non. To the best of our knowledge, there is no previous work on td for detecting an arbitrary signal in nongaussian noise with unknown pdf, which is the focus of this paper. Locally optimum detection of a noise model based on. Robust signaltonoise ratio estimation based on waveform. Betz, detection of weak random signals in iid nongaussian noise, ieee trans.
Stochastic resonance with colored noise for neural signal. Cyclostationary detection in nongaussian noise has been considered in 14. We investigate the nongaussian signal detection in gaussian noise. Detection of narrowband signals in spherically invariant noise.
A general introduction to signal detection in nongaussian noise can be found in ref. For the case of independent non gaussian noise samples, the theory of locally opdimum bayes detection lobd. The majority of the signal detection and modulation classification algorithms available in the literature assume that the additive noise has a gaussian distribution. Detection in nongaussian noise university of washington. Signal detection in nongaussian noise springerlink. Signal detection under weakly nongaussian noise distribution. Simulations for density click here conditions and probability. N2 detection of chirps in non gaussian additive and multiplicative noise is explored via a novel cyclostationary approach. Frequency estimation of fm signals under nongaussian and. Moreover, the multicycle detector requires the knowledge of the signal phase as well.
Therefore, we accomplish the nongaussian signal detection by using. This book contains a unified treatment of a class of problems of signal detection theory. The models are used in the design of a lod test for detecting weak signals in real nongaussian noise. For a given gaussian noise level, it is shown in figs.
Estimation of the parameters of sinusoidal signals in nongaussian noise, ieee trans actions on signal processing 57 no. Pdf detection of random signals in gaussian mixture noise. In this second part of an ongoing study, the general problem of optimum and suboptimum detection of threshold i. The problem of hosbased signal detection methods applied in real communication systems is addressed. If a clean speech signal is corrupted by additive gaussian noise n, its probability density function can be expressed as. Toward the detection of gravitational waves under non. Pdf this paper has focused attention on the problem of optimizing signal detection in presence of additive independent stationary nongaussian noise. Sequential strategy to solve the problem of sequential detection for unknown 1. This is the detection of signals in addi tive noise which is not required to have gaussian. Signal detection and modulation classification in non. T1 detection and estimation of chirp signals in nongaussian noise. An introduction to signal detection and estimation springer texts in electrical engineering h.
For example, in watermark detection in discrete cosine transform dct domain, the signal is the watermark or a signature, which is usually known, while the dct coefficients of an image is the noise, whose. Schwartz department of electrical engineering and computer science princeton university princeton, nj 08544 abstract in this report, we study procedures for robust detection of slowly fading narrow. Detection of random signals in gaussian mixture noise article pdf available in ieee transactions on information theory 416. However,it requires the knowledge,but for a scale factor, of the noise correlation matrix. Both signal processing algorithms and performance measures are obtained canonically, and specifically when the electromagnetic interference environment emi is. The pdf model is expressed in terms of a fourthorder statistical parameter. Orthogonal polynomial approximation, signal detection and estimation, nongaussian noise 1 introduction transformation method.
Nearly optimal detection of signals in nongaussian noise dtic. Kassam, optimum quantization for signal detection, ieee trans actions on. However, these detectors require the knowledge of the noise probability density function pdf. Hosbased noise models for signaldetection optimization. Of course the focus is on noise which is not gaussian. It may enter the receiver through the antenna along with the desired signal or it may be generated within the receiver. Blum, \on the optimality of nite level quantizations for distributed signal detection, ieee transactions on information theory, pp. A robust detector of known signal in nongaussian noise using. Therefore, we accomplish the non gaussian signal detection by using. This paper deals with noncoherent discretetime detection of a narrowband signal subject to slow and nonselective fading and embedded in correlated non gaussian noise modeled as a spherically invariant random process whose modulating random variable is continuous. Preprocessing of data by the in the signal detection and estimation problems, we often assume that the additive random noise process is gaussian. At first, an asymptotic sufficient statistic for an arbitrary fading law is derived. Quadratic tests for detection of abrupt changes in. Robust detection of fading narrowband signals in nongaussian noise m.
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