Skip to main content

Christ D Richmond

Professor in the Department of Electrical and Computer Engineering
Electrical and Computer Engineering

Selected Publications


Sample-Starved Wavefront Adaptive Sensing and GLRT for MTI Radar

Conference Proceedings 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 text Cite

Waveform Optimization for Channel Matrix-Based Cognitive Radar/Sonar

Conference Proceedings 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 text Cite

Delay-Doppler Parameter Estimation for DFRC-OTFS Using 2D Root-MUSIC

Conference Proceedings 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 text Cite

B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles

Journal Article ACM 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 text Cite

Linear Time Varying Channel Matrix Approach for Modeling MIMO Radar Returns

Conference Proceedings 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 text Cite

Sparse Delay-Doppler Channel Estimation for OTFS Modulation Using 2D-Music

Conference ICASSP, 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 text Cite

Asymptotic Distribution of Channel Matrix-Based GLRT for Cognitive Radar/Sonar

Conference Conference 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 text Cite

Model-Aided Data Driven Adaptive Target Detection for Channel Matrix-Based Cognitive Sonar

Conference Proceedings 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 text Cite

Dual-Use of OTFS Architecture for Pulse Doppler Radar Processing

Conference Proceedings 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 text Cite

Adaptive Detection Algorithms for Channel Matrix-Based Cognitive Radar/Sonar

Conference Proceedings 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 text Cite

On the False Alarm Rate of Adaptive Detection Algorithms for Channel Matrix-Based Cognitive Radar/Sonar

Conference Conference 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 text Cite

On the Zak Transform-based Interpretation of OTFS Modulation

Conference Conference 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 text Cite

Theoretical Analysis of a Symmetric Two-Stage Change Detector for SAR Images

Journal Article IEEE 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 text Cite

Optimal Target Detection for Random Channel Matrix-Based Cognitive Radar/Sonar

Conference IEEE 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 text Cite

Asymptotic distribution of generalized likelihood ratio test under model misspecification with application to cooperative radar-communications

Conference ICASSP, 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 text Cite

Adaptive Radar Detection without Secondary Data for Uncooperative Spectrum Sharing Scenarios

Journal Article IEEE 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 text Cite

METRIC-Bayes: Measurements Estimation for Tracking in High Clutter using Bayesian Nonparametrics

Conference Conference 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 text Cite

On Misspecified Parameter Bounds with Application to Sparse Bayesian Learning

Conference Conference 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 text Cite

Bounds on Bearing, Symbol, and Channel Estimation under Model Misspecification

Conference Conference 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 text Cite

On Wilks' Theorem for Generalized Likelihood Ratio Test Performance of Cooperative Radar-Communications

Conference IEEE 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 text Cite

Vehicular RF Convergence: Simultaneous Radar, Communications, and PNT for Urban Air Mobility and Automotive Applications

Conference IEEE 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 text Cite

Capon–Bartlett cross-spectrum and a perspective on robust adaptive filtering

Journal Article Signal 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 text Cite

On threshold selection for improved SAR two-stage change detection

Conference 2020 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 text Cite

Simultaneous Track and Search Multiple-Channel Multiple-User Receiver (MCMUR) for Joint Radar-Communications Systems

Conference Conference 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 text Cite

Peak sidelobe level gumbel distribution of antenna arrays with random phase centers

Journal Article IEEE 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 text Cite

On Constraints in Parameter Estimation and Model Misspecification

Conference 2018 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 text Cite

Generalized Likelihood Ratio Test Performance for Cooperative Radar-Communications

Conference Conference 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 text Cite

Architectures for cooperative radar-communications: Average vs. generalized likelihood ratio tests

Conference 2018 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 text Cite

Performance bounds for parameter estimation under misspecified models: Fundamental findings and applications

Journal Article IEEE 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 text Cite

Bayesian framework and radar: On misspecified bounds and radar-communication cooperation

Conference IEEE 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 text Cite

Performance bounds on cooperative radar and communication systems operation

Conference 2016 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 text Cite

Methods and bounds for waveform parameter estimation with a misspecified model

Conference Conference 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 text Cite

Subspace detection for adaptive radar: Detectors and performance analysis

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 text Cite

Two-Stage Change Detection for Synthetic Aperture Radar

Journal Article IEEE 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 text Cite

Peak sidelobe level gumbel distribution for arrays of randomly placed antennas

Conference IEEE 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 text Cite

Prior mismatch in Bayesian direction of arrival estimation for sparse arrays

Conference IEEE 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 text Cite

Parameter bounds on estimation accuracy under model misspecification

Journal Article IEEE 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 text Cite

Mean-squared-error prediction for bayesian direction-of-arrival estimation

Journal Article IEEE 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 text Cite

Copy correlation direction-of-arrival estimation performance with a stochastic weight vector

Conference Conference 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 text Cite

Parameter bounds under misspecified models

Conference Conference 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 text Cite

Aspects of threshold region mean squared error prediction: Method of interval errors, bounds, Taylor's theorem and extensions

Conference Conference 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 text Cite

Mean squared error performance of adaptive matched field localization under environmental uncertainty

Conference 2012 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 text Cite

Copy correlation direction-of-arrival estimation performance

Conference Proceedings 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 text Cite

Performance of sample covariance based capon bearing only tracker

Conference Conference 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 text Cite

Numerically efficient mean squared error threshold SNR prediction for adaptive arrays

Conference 2010 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 text Cite

Sample covariance based estimation of Capon algorithm error probabilities

Conference Conference 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 text Cite

Statistical analysis of Capon-Bartlett 2-D cross spectrum

Conference ICASSP, 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 text Cite

A fresh look at the Bayesian bounds of the Weiss-Weinstein family

Journal Article IEEE 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 text Cite

MIMO radar: Joint array and waveform optimization

Conference Conference 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 text Cite

Cross coherence and joint PDF of the Bartlett and Capon power spectral estimates

Conference ICASSP, 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 text Cite

Capon Algorithm Mean-Squared Error Threshold SNR Prediction and Probability of Resolution

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 text Cite

Bayesian bounds for matchedfield parameter estimation

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 text Cite

The bayesian abel bound on the mean square error

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 text Cite

Mean-Squared Error and Threshold SNR Prediction of Maximum-Likelihood Signal Parameter Estimation With Estimated Colored Noise Covariances

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 text Cite

On the threshold region mean-squared error performance of maximum-likelihood direction-of-arrival estimation in the presence of signal model mismatch

Conference 2006 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 text Cite

The Bayesian ABEL bound on the mean square ERROR

Conference ICASSP, 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

Mean-squared error and threshold SNR prediction of maximum-likelihood signal parameter estimation with estimated colored noise covariances

Journal Article IEEE 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 text Cite

Asymptotic mean squared error performance of diagonally loaded Capon-MVDR processor

Conference Conference 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

On the probability of resolution for the amplitude and phase estimation (APES) spectral estimator

Conference ICASSP, 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 text Cite

Capon Algorithm Mean-Squared Error Threshold SNR Prediction and Probability of Resolution

Journal Article IEEE 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 text Cite

Mode filtering approaches to acoustic source depth discrimination

Conference Conference 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

Bayesian bounds for matched-field parameter estimation

Journal Article IEEE 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 text Cite

The capon-MVDR algorithm: Threshold SNR prediction and the probability of resolution

Conference ICASSP, 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

Quantitative ambiquity analysis for matched-field source localization under spatially-correlated noise field

Conference Oceans 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

Mean squared error threshold prediction of adaptive maximum likelihood techniques

Conference Conference 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

Statistics of adaptive nulling and use of the generalized eigenrelation (GER) for modeling inhomogeneities in adaptive processing

Journal Article IEEE 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 text Cite

Performance of a class of adaptive detection algorithms in nonhomogeneous environments

Journal Article IEEE 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 text Cite

Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments

Journal Article IEEE 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 text Cite

MVDR adaptive sidelobes: Extending Ruze's formula and providing an exact calculation of the probability of sidelobe suppression

Conference Proceedings 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 text Cite

Performance of the adaptive sidelobe blanker detection algorithm in nonhomogeneous environments

Journal Article IEEE 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 text Cite

Response of sample covariance based MVDR beamformer to imperfect look and inhomogeneities

Journal Article IEEE 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 text Cite

Statistics of adaptive nulling and modeling inhomogeneities in adaptive processing

Conference IEEE 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

Adaptive sidelobe blanker: A novel method of performance evaluation and threshold setting in the presence of inhomogeneous clutter

Conference Conference 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

Theoretical performance of a class of space-time adaptive detection and training strategies for airborne radar

Conference Conference 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

Statistics of adaptive nulling and modeling inhomogeneities in adaptive processing

Journal Article IEEE 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

Analysis of an adaptive detection algorithm for non-homogeneous environments

Conference ICASSP, 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 text Cite

Statistical performance analysis of the adaptive sidelobe blanker detection algorithm

Conference Conference 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

A note on non-Gaussian adaptive array detection and signal parameter estimation

Journal Article IEEE 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 text Cite

PDF's, confidence regions, and relevant statistics for a class of sample covariance-based array processors

Journal Article IEEE 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 text Cite

Derived PDF of maximum likelihood signal estimator which employs an estimated noise covariance

Journal Article IEEE 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 text Cite

Adaptive array processing in non-Gaussian environments

Conference IEEE 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

Exact pdfs for sample covariance based array processors with elliptically contoured data

Conference ICASSP, 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