ConferenceProceedings of the IEEE Radar Conference · January 1, 2024
Moving target indicator (MTI) radars can suffer signal-to-noise ratio (SNR) losses due to: 1) the use of heavy non-adaptive tapers, and/or 2) poor estimation of space-time adaptive weight vectors. For ground-based radars, non-adaptive temporal and spatial ...
Full textCite
ConferenceProceedings of the IEEE Radar Conference · January 1, 2024
Cognitive radar systems, driven by adaptive wave-form design, enhance target detection and tracking in complex environments. In the context of channel matrix-based cognitive radar, the asymptotic distribution of the generalized likelihood ratio test (GLRT) ...
Full textCite
ConferenceProceedings of the IEEE Radar Conference · January 1, 2024
Orthogonal time frequency space (OTFS) is a modulation scheme based on transmitting information symbols over ideal pulse-Doppler radar signals. As a result, the pilot component of an OTFS transmitted signal can be designed to take the form of a desired pul ...
Full textCite
Journal ArticleACM Transactions on Embedded Computing Systems · September 9, 2023
5G Millimeter Wave (mmWave) technology holds great promise for Connected Autonomous Vehicles (CAVs) due to its ability to achieve data rates in the Gbps range. However, mmWave suffers from a high beamforming overhead and requirement of line of sight (LOS) ...
Full textCite
ConferenceProceedings of the IEEE Radar Conference · January 1, 2023
Conventional approaches to modeling radar returns typically treat clutter stochastically, characterizing clutter returns with a covariance matrix. Such models fail to leverage the waveform dependence of the returns induced by clutter. An alternative model, ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 2023
In this paper, we address the problem of estimating the delays and Doppler shifts introduced by a sparse wireless channel for orthogonal time frequency space (OTFS) modulation. We show that in the discrete time-frequency (TF) domain, the received signal re ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · January 1, 2023
Waveform optimization is central to the perception-action cycle of the cognitive radar system, where the system continuously learns and adapts to the environment by adjusting its waveforms. This work uses Wilks' theorem to obtain the asymptotic distributio ...
Full textCite
ConferenceProceedings of Meetings on Acoustics · May 23, 2022
Data driven-based approaches including deep neural networks (DNN) have shown promise in various fields. Such techniques tend to require significant training for good convergence. Model-based approaches, however, provide practical data efficient solutions o ...
Full textCite
ConferenceProceedings of the IEEE Radar Conference · January 1, 2022
Orthogonal time frequency space (OTFS) modulation is a recently proposed modulation scheme that places the information symbols to be transmitted over the wireless channel in the delay-Doppler (DD) domain. In this paper, we argue that the OTFS discrete DD d ...
Full textCite
ConferenceProceedings of the IEEE Radar Conference · January 1, 2022
The classical problem of radar/sonar target adaptive detection relies on both a primary data set (consisting of possibly target returns plus noise), and a secondary or training data set (consisting of noise only data samples). Kelly derived a generalized l ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · January 1, 2022
In this work, we derive an analytical expression for the probability of false alarm for the generalized likelihood ratio test (GLRT) in the channel matrix-based sonar/radar framework when the waveform-independent colored noise (WICN) covariance is assumed ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · January 1, 2022
In this paper, we present a Zak transform-based development of the recently proposed orthogonal time frequency space (OTFS) modulation scheme. Unlike previous works, we focus on the interpretation of the spreading function as the Zak transform of the 'impu ...
Full textCite
Journal ArticleIEEE Transactions on Geoscience and Remote Sensing · January 1, 2022
A procedure is developed to generate theoretical receiver operating characteristic (ROC) curves for the two-stage change detector proposed by Cha et al., in order to compare its detection performance with other detectors. A modification, however, to the fi ...
Full textCite
ConferenceIEEE National Radar Conference - Proceedings · May 7, 2021
Conventional techniques for characterizing clutter depend on covariance-based statistical modeling. This presents a disadvantage to cognitive radar/sonar since optimizing waveform design becomes highly nonconvex. Modeling the clutter and target responses v ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 2021
The goal of this paper is to develop an expression for the asymptotic distribution of the generalized likelihood ratio test (GLRT) statistic under model misspecification, that is when the assumed data model is different from the true model. Under such a sc ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · January 1, 2021
We address the design of GLRT-based, space-time radar detectors in presence of a communication signal. We consider a disturbance that is either spatially correlated and temporally white or spatially and temporally correlated. The former case assumes that t ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · November 1, 2020
Robust tracking of a target in a clutter environment is an important and challenging task. In recent years, the nearest neighbor methods and probabilistic data association filters were proposed. However, the performance of these methods diminishes as numbe ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · November 1, 2020
The sparse vector recovery problem can lead to a combinatorial search of prohibitive computations. Hence, reformulations amenable to convex optimization strategies have been considered. Alternatively, Bayesian inference approaches can curtail computations ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · November 1, 2020
The constrained Cramér-Rao bound (CRB) has been used successfully to study parameter estimation in flat-fading scenarios, and established the value of side information such as known waveform properties (e.g. constant modulus) and known training symbols. Th ...
Full textCite
ConferenceIEEE National Radar Conference - Proceedings · September 21, 2020
The analysis of the generalized likelihood ratio test (GLRT) radar receiver when the radar is coexisting with a cooperative in-band communication (comm.) system is challenged by the discrete nature of the comm. symbols. While the asymptotic performance of ...
Full textCite
ConferenceIEEE National Radar Conference - Proceedings · September 21, 2020
Modern RF environments are becoming increasingly congested. This limits the opportunities and capabilities of modern RF systems, obstructing the development and proliferation of new technologies. Novel vehicular RF technologies promise a new era of transpo ...
Full textCite
Journal ArticleSignal Processing · June 1, 2020
Adaptive filtering / beamforming (ABF) optimized for maximum signal-to-interference-plus-noise ratio (SINR) results in filter weights that depend on the data covariance and the signal array response vector. The effectiveness of practical application of suc ...
Full textCite
Conference2020 IEEE International Radar Conference, RADAR 2020 · April 1, 2020
The sample intensity ratio estimator and the sample coherence estimator are test statistics which are generally used for detecting areas of change between two synthetic aperture radar (SAR) images of the same scene, taken at different times. Cha et al. hav ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · November 1, 2019
A multiple-channel multiple-user receiver (MCMUR) exploits both spatial and temporal degrees of freedom to separate radar and communications signals coexisting jointly in the same frequency band, and to cancel interference waveforms. In this paper, we pres ...
Full textCite
Journal ArticleIEEE Transactions on Antennas and Propagation · August 1, 2019
The maximum value of an antenna array's sidelobe beampattern, or radiation pattern in the power domain, is an important parameter determining its performance. In this paper, when array antenna elements have random phase centers, we approximate the maximum ...
Full textCite
Conference2018 21st International Conference on Information Fusion, FUSION 2018 · September 5, 2018
Under perfect model specification several deterministic (non-Bayesian) parameter bounds have been established, including the Cramer-Rae, Bhattacharyya, and the Barankin bound; where each is known to apply only to estimators sharing the same mean as a funct ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · July 2, 2018
The performance of generalized likelihood ratio tests (GLRT) in radar detection is a well-studied subject, as is the performance of a maximum-likelihood decoder for a communication (comm.) receiver. The theoretical analysis of a cooperative radar-comm. rec ...
Full textCite
Conference2018 IEEE Radar Conference, RadarConf 2018 · June 8, 2018
A radar receiver cooperating with a communication system to share spectrum is challenged by composite hypothesis testing that is compounded by the persistent presence of in-band communication signals. Two established approaches to composite hypothesis test ...
Full textCite
Journal ArticleIEEE Signal Processing Magazine · November 1, 2017
Inferring information from a set of acquired data is the main objective of any signal processing (SP) method. The common problem of estimating the value of a vector of parameters from a set of noisy measurements is at the core of a plethora of scientific a ...
Full textCite
ConferenceIEEE Workshop on Statistical Signal Processing Proceedings · August 24, 2016
The Bayesian framework is versatile as it allows for incorporation of prior knowledge or experience in making inference. The case of no prior knowledge at all is likewise seamlessly supported. The Bayesian framework is naturally suited to many fields of sc ...
Full textCite
Conference2016 IEEE Radar Conference, RadarConf 2016 · June 3, 2016
A theoretical framework that embraces the competing objectives of cooperative radar-communication operations is proposed that engages the apparent trade-space in an optimal fashion. Specifically, minimization of a cooperative risk metric that extends the N ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · February 26, 2016
Parameter estimation for phase modulated signals is an important area of research as it is applicable to many areas ranging from radar signal processing to gravity wave detection. However, in many of these applications, the phase model required to accurate ...
Full textCite
Chapter · January 1, 2016
Coherent processing of various forms of multidimensional signals is commonplace in radar applications. Space-time adaptive processing in radars is a well-established example of coherent processing involving the domains of space (multiple receiving antenna ...
Full textCite
Journal ArticleIEEE Transactions on Geoscience and Remote Sensing · December 1, 2015
Coherent change detection using paired synthetic aperture radar (SAR) images is often performed using a classical coherence estimator that is invariant to the true variances of the populations underlying each paired sample. While attractive, this estimator ...
Full textCite
ConferenceIEEE National Radar Conference - Proceedings · June 22, 2015
Extreme Value Theory (EVT) is used to analyze the peak sidelobe level distribution for array element positions with arbitrary probability distributions. Computations are discussed in the context of linear antenna arrays using electromagnetic energy. The re ...
Full textCite
ConferenceIEEE National Radar Conference - Proceedings · June 22, 2015
We study the mean-squared-error (MSE) performance of Bayesian direction-of-arrival (DOA) estimation for sparse linear arrays in which prior belief about the target location is incorporated into the estimation process. We utilize a recent extension of the m ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · May 1, 2015
When the assumed data distribution differs from the true distribution, the model is said to be misspecified or mismatched. Model misspecification at some level is an inevitability of engineering practice. While Huber's celebrated work assesses maximum-like ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · September 9, 2013
In this article, we study the mean-squared-error performance of Bayesian direction-of-arrival (DOA) estimation in which prior belief about the target location is incorporated into the estimation process. Our primary result is an extension of the method of ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · January 1, 2013
Copy-aided direction finding of co-channel signals with known structure is an effective method of angle estimation applicable to any blind or non-blind frontend signal processing. The frontend processing yields for each emitter a copy weight vector that ca ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · January 1, 2013
A class of parameter bounds emerges as a consequence of the covariance inequality, i.e. Cauchy-Schwarz inequality for expectations. The expectation operator forms an inner product space. Flexibility in the choice of expectation integrand and measure for in ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2012
The method of interval errors (MIE) predicts mean-squared error (MSE) performance at low signal-to-noise ratios (SNR) where global errors dominate. It is algorithm specific and enabled by an estimate of asymptotic MSE performance and sidelobe error probabi ...
Full textCite
Conference2012 IEEE Statistical Signal Processing Workshop, SSP 2012 · November 6, 2012
Matched field processing (MFP) is the use of full-field acoustic modeling to obtain improved detection and localization over conventional planewave and range focused beamforming in passive sonar signal processing. MFP localization (MFL), however, is a chal ...
Full textCite
ConferenceProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop · October 12, 2012
The mean squared error performance of a copy weight correlation (CC) based method of angle estimation proposed by Forsythe and Richmond is studied via application of the method of interval error (MIE). It is demonstrated that at low SNRs the CC method lean ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2011
Bearing estimates input to a tracking algorithm require a concomitant measurement error to convey confidence. When Capon algorithm based bearing estimates are derived from low signal-to-noise ratio (SNR) data, the method of interval errors (MIE) provides a ...
Full textCite
Conference2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010 · December 20, 2010
The method of interval estimation (MIE) is an established technique for extending asymptotic mean squared error (MSE) predictions like the Cramér-Rao bound to lower signal-to-noise ratio. While application of MIE to the adaptive array problem was successfu ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2010
The method of interval estimation (MIE) provides a strategy for mean squared error (MSE) prediction of algorithm performance at low signal-to-noise ratios (SNR) below estimation threshold where asymptotic predictions fail. MIE interval error probabilities ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 2010
An exact joint probability density function (PDF) (not approximate as in [4]) is provided for the Capon power spectral estimate and the average output power of any other deterministic filter when based on the same data sample covariance matrix. The cross c ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · November 3, 2008
Minimal bounds on the mean square error (MSE) are generally used in order to predict the best achievable performance of an estimator for a given observation model. In this paper, we are interested in the Bayesian bound of the Weiss-Weinstein family. Among ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2007
In this paper, techniques for the optimization of multiple-input multiple-output (MIMO) radar waveform correlations and array geometries are investigated. The primary focus of this study is improved angle-estimation performance. This performance can be cha ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · August 6, 2007
The Bartlett algorithm results from a conventional (Fourier or beamforming) approach to power spectral estimation and the Capon algorithm results from an adaptive approach. Both algorithms make use of the data sample covariance matrix (SCM). The Bartlett a ...
Full textCite
Chapter · January 1, 2007
Below a specific threshold signal-to-noise ratio (SNR), the mean-squared error (MSE) performance of signal parameter estimates derived from the Capon algorithm degrades swiftly. Prediction of this threshold SNR point is of practical significance for robust ...
Full textCite
Chapter · January 1, 2007
Matched-field methods concern estimation of source locations and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Because of the nonlinear parameter-dependence of the signal field, the estimate is subjec ...
Full textCite
Chapter · January 1, 2007
This paper deals with lower bound on the Mean Square Error (MSE). In the Bayesian framework, we present a new bound which is derived from a constrained optimization problem. This bound is found to be tighter than the Bayesian Bhattacharyya bound, the Reuve ...
Full textCite
Chapter · January 1, 2007
An interval error-based method (MIE) of predicting mean squared error (MSE) performance of maximum-likelihood estimators (MLEs) is extended to the case of signal parameter estimation requiring intermediate estimation of an unknown colored noise covariance ...
Full textCite
Conference2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 · December 1, 2006
The mean squared error (MSE) performance prediction of MaximumLikelihood (ML) Direction-Of-Arrival (DOA) angle estimation has been studied extensively. Previous analyses consider Cramér-Rao Bounds, sensitivity/asymptotic [in signal-to-colored noise ratio ( ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · December 1, 2006
This paper deals with lower bound on the Mean Square Error (MSE). In the Bayesian framework, we present a new bound which is derived from a constrained optimization problem. This bound is found to be tighter than the Bayesian Bhattacharyya bound, the Reuve ...
Cite
Journal ArticleIEEE Transactions on Information Theory · May 1, 2006
An interval error-based method (MIE) of predicting mean squared error (MSE) performance of maximum-likelihood estimators (MLEs) is extended to the case of signal parameter estimation requiring intermediate estimation of an unknown colored noise covariance ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2005
The asymptotic local mean squared error (MSB) performance of the Capon algorithm, a.k.a the minimum variance distortionless response (MVDR) spectral estimator, has been studied extensively by several authors. Stoica et al. [21], Vaidyanathan and Buckley [2 ...
Cite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 2005
The Amplitude and Phase EStimation (APES) algorithm is a spectral estimation approach that estimates the complex amplitude of the power spectrum of a random process. Although its resolution performance has been observed to be slightly better than conventio ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · January 1, 2005
Below a specific threshold signal-to-noise ratio (SNR), the mean-squared error (MSE) performance of signal parameter estimates derived from the Capon algorithm degrades swiftly. Prediction of this threshold SNR point is of practical significance for robust ...
Full textCite
ConferenceConference Record - Asilomar Conference on Signals, Systems and Computers · December 1, 2004
Mode filtering in passive sonar represents a class of linear beamforming approaches in which the steering vectors are parameterized by the depth-dependent mode functions and horizontal wavenumbers that characterize propagation in a shallow waveguide. In th ...
Cite
Journal ArticleIEEE Transactions on Signal Processing · December 1, 2004
Matched-field methods concern estimation of source locations and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Because of the nonlinear parameter-dependence of the signal field, the estimate is subjec ...
Full textCite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · October 7, 2004
The threshold region mean squared error (MSE) performance of the Capon-MVDR algorithm is predicted via an adaptation of an interval error based method referred to herein as the method of interval errors (MIE). MIE requires good approximations of two quanti ...
Cite
ConferenceOceans Conference Record (IEEE) · December 1, 2003
Matched-field methods find source location by matching the measured signal field with the modeled signal field. The resulted ambiguity output is often characterized by a multimodal structure. At high signal-to-noise ratio (SNR), the peak at the true source ...
Cite
ConferenceConference Record of the Asilomar Conference on Signals, Systems and Computers · December 1, 2003
Below a threshold signal-to-noise ratio (SNR), the mean squared error (MSE) performance of nonlinear maximum-likelihood (ML) estimation degrades swiftly. Threshold SNR prediction for ML signal parameter estimation requiring intermediate estimation of an un ...
Cite
Journal ArticleIEEE Transactions on Signal Processing · May 1, 2000
This paper examines the integrity of the generalized eigenrelation (GER), which is an approach to assessing performance in an adaptive processing context involving covariance estimation when the adaptive processors are subject to undernulled interference. ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · May 1, 2000
A two-dimensional (2-D) adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter (AMF) in nonhomogene ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · May 1, 2000
The adaptive sidelobe blanker (ASB) algorithm is a two-stage detector consisting of a first stage adaptive matched filter (AMF) detector followed by a second-stage detector called the adaptive coherence (or cosine) estimator (ACE). Only those data test cel ...
Full textCite
ConferenceProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop · January 1, 2000
Exact finite sum expressions for the probability density function (PDF) and cumulative distribution function (CDF) for the magnitude response of the SCB MVDR beamformer are derived. Exact expressions for the mean and variance of this beam pattern are given ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · January 1, 1999
The two-dimensional adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter (AMF) in non-homogeneous ...
Full textCite
Journal ArticleIEEE Signal Processing Letters · December 1, 1998
The sample covariance based (SCB) minimum variance distortionless response (MVDR) beamformer has desirable properties under ideal homogeneous data conditions with perfect look. Such properties include maximum-likelihood optimality yielding an unbiased asym ...
Full textCite
ConferenceIEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP · December 1, 1998
Recently a generalized eigen-relation (GER) constraint was employed to model inhomogeneities in an adaptive processing context. This constraint facilitated closed-form analysis of classical adaptive detectors under a nonhomogeneous data assumption. In this ...
Cite
ConferenceConference Record of the Asilomar Conference on Signals, Systems and Computers · December 1, 1998
The Adaptive Sidelobe Blanker (ASB) detection algorithm consists of a cascade of two detectors: an Adaptive Matched Filter (AMF) followed by an Adaptive Coherence Estimator (ACE). The ASB has been shown to be effective at mitigating false alarms due to the ...
Cite
ConferenceConference Record of the Asilomar Conference on Signals, Systems and Computers · December 1, 1998
First generation airborne radar systems were non-adaptive, performing such operations as moving target indication (MTI), synthetic aperture radar (SAR) imaging, and displaced phased center array (DPCA) data processing. In most cases the processing was sepa ...
Cite
Journal ArticleIEEE Transactions on Signal Processing · December 1, 1998
This paper exarmines the integrity of the generalized eigenrelation (GER) as an approach to modeling inhomogeneities in adaptive processing. In the process, some fundamental properties of adaptive nulling are established, and novel statistics are derived f ...
Cite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 1998
The adaptive matched filter (AMF) detector is known to be highly vulnerable to jammers and clutter discretes on which it has not properly trained. A vulnerability often leading to impractical false alarm rates in non-homogeneous environments. Sequentially ...
Full textCite
ConferenceConference Record of the Asilomar Conference on Signals, Systems and Computers · January 1, 1998
A method was proposed for reducing the high false alarm rate of the adaptive matched filter (AMF) under non-homogeneous conditions. It consists of sequentially following the AMF test with the adaptive cosine estimator (ACE) which determines what fraction o ...
Cite
Journal ArticleIEEE Signal Processing Letters · December 1, 1996
Kelly's generalized likelihood ratio test (GLRT) statistic is reexamined under a broad class of data distributions known as complex multivariate elliptically contoured (MEC), which include the complex Gaussian as a special case. We show that, mathematicall ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · December 1, 1996
In this paper, we add to the many results on sample covariance matrix (SCM) dependent array processors by i) weakening the traditional assumption of Gaussian data and ii) providing for a class of array processors additional performance measures that are of ...
Full textCite
Journal ArticleIEEE Transactions on Signal Processing · December 1, 1996
A probability density function (pdf) for the maximum likelihood (ML) signal vector estimator is derived when the estimator relies on a noise sample covariance matrix (SCM) for evaluation. By using a complex Wishart probabilistic model for the distribution ...
Full textCite
ConferenceIEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP · January 1, 1996
In several adaptive array application areas the Gaussian distribution has not proven to be an accurate model of the measured data. Nevertheless, Gaussian based processors have demonstrated robust performance in spite of this statistical mismatch. A need th ...
Cite
ConferenceICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · January 1, 1996
Practical application of array processors typically requires use of a sample covariance matrix (SCM). We add to the many results on SCM based (SCB) array processors by weakening the traditional assumption of data Gaussianity and subsequently providing for ...
Cite