Download or read book High Level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter Volume 3 Spherically Invariant Random Processes for Radar Clutter Modeling Simulation and Distribution Identification written by and published by . This book was released on 1995 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This investigation is motivated by the problem of detection of weak signals in a strong radar clutter background. The fundamental issues that need to be addressed in the weak signal detection problem are radar clutter modeling, simulation and distribution approximation. These issues are easily addressed when the clutter is a correlated Gaussian random process. However, these issues have not received much attention when the clutter is a correlated non-Gaussian random process. This thesis addresses the problem of modeling, simulation and distribution approximation of correlated non-Gaussian radar clutter. The theory of spherically invariant random processes is used for statistical characterization of non-Gaussian radar clutter. Several examples of multivariate probability density functions arising from spherically invariant random processes are presented. A new result which uniquely characterizes the multivariate probability density functions arising from spherically invariant random processes is obtained. Two new canonical computer simulation procedures are developed in order to simulate radar clutter that can be described by spherically invariant random processes. Finally, a new algorithm is used to address the problem of distribution identification of the clutter using relatively small sample sizes. This technique makes use of the result which uniquely characterizes the multivariate probability density functions arising from spherically invariant random processes and reduces the multivariate distribution approximation problem to an equivalent univariate distribution approximation problem resulting in a major simplification of processing.
Download or read book High level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter written by Muralidhar Rangaswamy and published by . This book was released on 1995 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High Level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter Volume 4 The Problem of Weak Signal Detection written by and published by . This book was released on 1995 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This investigation is motivated by the problem of weak signal detection in a strong clutter background. The concept of the Locally optimum Detector has been used to address this problem. The problem of weak signal detection has been extensively addressed in the literature when the received radar samples can be modeled as independent and identically distributed. However, this issue has not received much attention when the received radar samples are correlated and have a non-Gaussian probability density function. Also, performance analysis is not generally carried out for finite sample sizes. This thesis addresses the performance of Locally Optimum Detectors in radar weak signal detection for finite sample sizes where the radar disturbance is modeled as a correlated non-Gaussian random process. The theory of Spherically Invariant Random Process is used for statistical characterization of non-Gaussian radar clutter. In particular, the K-distribution and the Student-T distributions have been considered as models for radar clutter. A canonical form is established for the Locally Optimum Detector that is a product of the Gaussian linear receiver and a zero memory nonlinearity. The functional form of the zero memory nonlinearity depends on the approximation used for the underlying radar clutter probability density function. Since the weak signal detector is nonlinear, thresholds for specified false alarm probability cannot be established in closed form. Given a specified false alarm probability a new method for threshold estimation based on extreme value theory is derived that reduces by orders of magnitude the computation and sample size required to set the threshold.
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 High level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter written by and published by . This book was released on 1995 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Government Reports Announcements Index written by and published by . This book was released on 1996-05 with total page 1130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter written by Mohamed Adel Slamani and published by . This book was released on 1995 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter written by Mohamed Adel Slamani and published by . This book was released on 1995 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High level Adaptive Signal Processing Architecture with Applications to Radar Non Gaussian Clutter written by and published by . This book was released on 1995 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Electrical Electronics Abstracts written by and published by . This book was released on 1995 with total page 1576 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1995 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Adaptive Radar Detection and Range Estimation written by Chengpeng Hao and published by Springer Nature. This book was released on 2021-12-03 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.
Download or read book Signal Detection in Correlated Gaussian and Non Gaussian Radar Clutter written by and published by . This book was released on 1993 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this report is the detection of weak targets in a strong clutter environment. Two situations arise depending on whether or not the weak targets can be separated from the clutter. For both cases new receivers are derived which provide significant improvement in performance over other recently proposed techniques. This work includes development of an adaptive joint-domain space-time processor, effective non-gaussian weak signal detectors based on spherically invariant random processes, and a new method for approximating the underlying probability density function of random data which works extremely well with only 100 samples. Locally optimum detector, Spherically invariant, Random processes, Probability density function, Weak signal detector, Radar, Space-time processing, Clutter, Non-gaussian.
Download or read book Space Time Adaptive Processing for Radar Second Edition written by J.R. Guerci and published by Artech House. This book was released on 2014-11-01 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Space-time adaptive processing (STAP) is an exciting technology for advanced radar systems that allows for significant performance enhancements over conventional approaches. Based on a time-tested course taught in industry, government and academia, this second edition reviews basic STAP concepts and methods, placing emphasis on implementation in real-world systems. It addresses the needs of radar engineers who are seeking to apply effective STAP techniques to their systems, and serves as an excellent reference for non-radar specialists with an interest in the signal processing applications of STAP. Engineers find the analysis tools they need to assess the impact of STAP on a variety of important radar applications. A toolkit of STAP algorithms and implementation techniques allows practitioners the flexibility of adapting the best methods to their application. In addition, this second edition adds brand new coverage on “STAP on Transmit” and “Knowledge-Aided STAP (KA-STAP).
Download or read book Robust Adaptive Signal Processing Methods for Heterogeneous Radar Clutter Scenarios written by and published by . This book was released on 2004 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper addresses the problem of radar target detection in severely heterogeneous clutter environments. Specifically, we present the performance of the normalized matched filter test in a background of disturbance consisting of clutter having a covariance matrix with known structure and unknown scaling plus background white Gaussian noise. It is shown that when the clutter covariance matrix is low rank, the (LRNMF) test retains invariance with respect to the unknown scaling as well as the background noise level and has an approximately constant false alarm rate (CFAR). Performance of the test depends only upon the number of elements, the number of pulses processed in a coherent processing interval, and the rank of the clutter covariance matrix. Analytical expressions for calculating the false alarm and detection probabilities are presented. Performance of the method is shown to degrade with increasing clutter rank especially for low false alarm rates. An adaptive version of the test (LRNAMF) is developed and its performance is studied with simulated data from the KASSPER program. Results pertaining to sample support for subspace estimation, CFAR, and detection performance are presented. Target contamination of training data has a deleterious impact on the performance of the test. Therefore, a technique known as self-censoring reiterative fast maximum likelihood/adaptive power residue (SCRFML/APR) is developed to treat this problem and its performance is discussed. The SCRFML/APR method is used to estimate the unknown covariance matrix in the presence of outliers. This covariance matrix estimate can then be used in the LRNAMF or any other eigen-based adaptive processing technique.
Download or read book Weibull Radar Clutter written by Matsuo Sekine and published by IET. This book was released on 1990 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: The material presented in this book is intended to provide the reader with a pratical treatment of Weibull distribution as applied to radar systems. This book is primarily written for radar engineeres. Topics include: general derivation of Weibull distribution, measurements of Weibull-distributed clutter, comparison of Weibulkl distribution with various distributions including Rayleigh, gamma, log-nornal and k- distributions to name just a few.
Download or read book Space Time Adaptive Processing STAP Performance in Non Homogeneous Radar Clutter written by and published by . This book was released on 2001 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract report addresses the statistical analysis of the non-homogeneity detector (NHD) for non-Guassian interference scenarios. An important issue in STAP is that of homogeneity of training data. Non-homogeneity of the training data has a deleterious effect on STAP performance in that undernulled clutter significantly degrades detection and false alarm characteristics. Previous work in this area has proposed the use of non-homogeneity detector based on a generalized inner product (GIP). The unsuitability of the GIP based test for non-Guassian interference scenarios is noted. We present a new non-homogeneity detector for non-Guassian interference scenarios which can be modeled by a spherically invariant random process (SIRP). Our work includes a statistical analysis of the NHD for non-Guassian interference taking into account the fact that finite sample support is used for covariance estimation. In particular, exact theoretical expressions for the NHD test statistic PDF and the mean of a related test statistic are derived. We also note that the related test statistic admits a remarkably simple stochastic representation as a ratio of an F-distributed random variable and a beta-distributed loss factor. Based on this development, a formal goodness-of-fit test is presented. Performance analysis is carried out using simulated and measured data from the MCARM Program.
