# Yuri I AbramovichWR Systems · Fairfax, VA

Yuri I Abramovich

Doctor of Science, Leningrad Institute for Avionics, 1981

## About

369

Publications

25,480

Reads

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3,804

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Introduction

Additional affiliations

June 2004 - June 2015

January 2000 - January 2010

**Defense Science and Technology Organisation**

Position

- Group Leader

January 1994 - January 2005

**Cooperative Research Centre for Sensor Signal and Information Processing (CSSIP)**

Position

- Principal Investigator

## Publications

Publications (369)

In asynchronous (intermittent) interference scenarios, the content of co-channel interference sources over the data interval may be different from the interferers content over the training interval, typically with extra interference sources presented over the data interval. Under such conditions, conventional adaptive beamformer designed over the t...

Expected likelihood (EL) technique for quality assessment of parameter estimates of signals embedded in Gaussian noise is extended in this paper over the case where useful signals are immersed in a mixture of compound Gaussian and Gaussian distributed noises. The main problem here is that analytical expressions for distributions of such mixtures do...

Recent covariance estimation methods for radar space-time adaptive processing exploit practical constraints such as the rank of clutter subspace and the condition number of disturbance covariance to estimate accurate covariance even when training is not generous. While rank and condition number are very effective constraints, often practical nonide...

We address the problem of estimating the directions-of-arrival (DoAs) of multiple signals received in the presence of a combination of a strong compound-Gaussian external noise and weak internal white Gaussian noise. Since the exact distribution of the mixture is not known, we get an insight into optimum procedure via a related model where we consi...

A well known problem of regularization (diagonal loading) of the interference rejection combining (IRC) and IRC / maximum ratio combining (MRC) switching is addressed. Different empirical loading factor selection rules adjusted to specific scenarios have been introduced in the literature. It is expected that future network will be characterized by...

We address the problem of structured covariance matrix estimation for radar space-time adaptive processing (STAP). A priori knowledge of the interference environment has been exploited in many previous works to enable accurate estimators even when training is not generous. Specifically, recent work has shown that employing practical constraints suc...

The problem of radar target detection in the background interference (plus noise) environment is the central problem in statistical radar theory. As a result, there are a number of well-established optimal (in the Neyman-Pearson sense) solutions for Gaussian signals and interference models with known interference covariance matrices, as presented i...

In a recent letter we addressed the problem of detecting a fluctuating target in distributed noise using multiple coherent processing intervals. It was shown through simulations that the performance of the likelihood ratio test is dominated by the snapshot which corresponds to the minimal value of the texture. However, for this particular snapshot...

In the last decade, the radar world is assisting to a sort of new revolution, comparable to that caused by the introduction of adaptivity in the 70s. Continuing advances in device technologies combined with adaptive processing present rich opportunities for new sensing methodologies and new challenges in signal processing. Complex and integrated sy...

This paper introduces a novel non-linear processing technique for reducing the dimensions of a data set without performing hard thresholding while maintaining the detector performance as applied to the original large data set. In particular, the introduced processing technique can be utilized in spatial beamforming, high-range resolution processing...

This letter deals with the problem of fluctuating target detection in heavy-tailed K-distributed clutter over a number T of independent coherent intervals, e.g., in the case of a long observation interval (“stare mode”), or that of independent (range) resolution cells as per the track before detect techniques. The generalized likelihood ratio test...

For an antenna array input mixture of m point source signals in K-distributed noise, we compare DOA estimation delivered by Maximum Likelihood and the recently introduced Robust G-MUSIC (RG-MUSIC) technique. We demonstrate that similar to the Gaussian case, MLE is still superior to RG-MUSIC, especially within the so-called threshold region. This ma...

The problem of receive antenna array calibration in cases where the array is strongly spatially "over-sampled" is addressed in this paper. We suggest a new technique wherein spatially distributed strong clutter returns can be used for calibration with the goal of minimizing the power at the output of a number of antenna finger-beams steered into th...

This paper considers the problem of increasing the sensitivity of the receiving system in an Over-The-Horizon Radar. We are concerned with the problem of detecting small targets in noise during night-time operation when reduced ionospheric propagation support limits the radar operating frequency to the lower part of the HF band and the external noi...

We address the problem of estimation of structured covariance matrices for radar space-time adaptive processing (STAP)1. The knowledge of the interference environment has been exploited in many previous works to accurately estimate a structured disturbance covariance matrix. In particular, it has been shown that employing the rank of clutter subspa...

Regularization, which consists in shrinkage of the sample covariance matrix to a target matrix, is a commonly used and effective technique in low sample support covariance matrix estimation. Usually, a target matrix is chosen and optimization of the shrinkage factor is carried out, based on some relevant metric. In this letter, we rather address th...

We consider the problem of estimating the direction of arrival of a signal
embedded in $K$-distributed noise, when secondary data which contains noise
only are assumed to be available. Based upon a recent formula of the Fisher
information matrix (FIM) for complex elliptically distributed data, we provide
a simple expression of the FIM with the two...

This paper considers the problem of range-folded spread clutter mitigation in parallax (geographically remote) transmit (Tx) and receive (Rx) high-frequency (HF) over-the-horizon radar (OTHR). We demonstrate that MIMO radar technology could be applied to provide the required level of spread range-folded clutter.

The problem of adaptive detection of a signal of interest embedded in elliptically distributed noise with unknown scatter matrix ${mbi{R}}$ is addressed, in the specific case where the number of training samples $T$ is less than the dimension $M$ of the observations. In this under-sampled scenario, whenever ${mbi {R}}$ is treated as an arbitrary po...

This work addresses the problem of target maneuver detection using passive bearing measurements when the target motion dynamics can be described by a discrete constant velocity (CV) model. The proposed expected likelihood (EL) maneuver detector (ELMD) extends the EL approach from a direction of arrival estimation framework to maneuver detection of...

This paper proposes superdirective adaptive mode-selective processing in oversampled 2D transmitting (Tx) and receiving (Rx) antenna arrays, enabled by MIMO radar technology, for skywave OTHR applications. The actual reactive power in Tx antenna arrays is controlled by considering two main principles: (1) avoiding extreme steering angles in convent...

Modern high frequency (HF) over-the-horizon Radar's (OTHR's) that perform parametric sensing over a huge coverage of several million square kilometers operate in harsh sensing environments consisting of strong interference and clutter. The highly dynamic nature of such an environment governed by harsh ionosphere propagation conditions and a highly...

This paper proposes a multi-channel adaptive array spatial covariance matrix estimation technique in which the covariance is modeled as consisting of two complementary components. The first component has finite rank and is meant to capture the low-rank components of the external interference environment. The second component has full rank and corre...

The use of skywave over-the-horizon radar for the detection and tracking of ships is significantly more challenging than the equivalent task for aircraft. This is due in large part to multi-path and Doppler disturbed propagation through the ionosphere. In this paper we report initial results for a newly proposed class of radar called Mode-Selective...

The likelihood ratio (LR) for testing if the covariance matrix of the observation matrix X is R has some invariance properties that can be exploited for covariance matrix estimation purposes. More precisely, it was shown in Abramovich et al. (2004, 2007, 2007) that, in the Gaussian case, LR(R0|X), where R0 stands for the true covariance matrix of t...

For direction of arrival (DOA) estimation in the threshold region, it has been shown that use of Random Matrix Theory (RMT) eigensubspace estimates provides significant improvement in MUSIC performance. Here we investigate whether these RMT methods can also improve the threshold performance of unconditional (stochastic) maximum likelihood DOA estim...

SIMO channel identification problems arise in many practical applications, such as geolocation of HF sources propagated via the multi-layer ionosphere. In this case, memory of the channel (often modeled as a finite impulsive response (FIR) channel) makes the traditional assumptions on the channel estimation training samples as independent and ident...

In Abramovich [“Bounds on Maximum Likelihood Ratio-Part I: Application to Antenna Array Detection-Estimation With Perfect Wavefront Coherence,” IEEE Trans. Signal Process., vol. 52, pp. 1524-1536, June 2004], it was demonstrated, for multivariate complex Gaussian distribution, that the probability density function (p.d.f.) of the likelihood ratio (...

Recently it has been proposed that two-dimensional (2D) oversampled received arrays could be used to provide signal-to-external noise ratio (SENR) gains for over-the-horizon radar applications which are strongly externally noise limited. These array configurations can be used to exploit superdirective adaptive beamforming techniques. A key element...

We address the problem of estimating the covariance matrix from a complex central angular Gaussian distribution when the number of samples T is less than the size of the observation space M. As regularization is needed, we consider the expected likelihood (EL) approach as a means to set the regularization parameters. The EL principle, originally de...

We consider the problem of estimating the scatter matrix in complex elliptically symmetric (CES) distributions using the expected likelihood (EL) approach. The latter, originally derived in the Gaussian case, is based on the fact that the probability density function (p.d.f.) of the likelihood ratio (LR) for the (unknown) actual covariance matrix d...

In over-the-horizon radar (OTHR) the need to preferentially select propagation mode arises when one or more modes are perturbed by ionospheric disturbances. Due to mixed-mode propagation and range-elevation coupling, such control is only implementable using noncausal beamforming via MIMO radar architectures. We introduce three key principles that g...

The Slepian-Bangs formula provides a very convenient way to compute the
Fisher information matrix (FIM) for Gaussian distributed data. The aim of this
letter is to extend it to a larger family of distributions, namely elliptically
contoured (EC) distributions. More precisely, we derive a closed-form
expression of the FIM in this case. This new expr...

We present the results of theoretical signal-to-noise (SNR) performance assessment for optimal (adaptive) and conventionally beamformed uniform rectangular antenna arrays with inter-element spacing smaller than the half-wavelength. We provide theoretical analysis of SNR in such arrays, exposed to strong night-time external noise arriving from all a...

This work addresses the problem of direction-of-arrival (DOA) estimation using spatial compressive sensing (SCS) with bias mitigation via an expected likelihood (EL) approach. Compressive sensing (CS)-based estimation approaches such as SCS suffer from two main bias sources: a) a grid-bias resulting from the discretization of the azimuth bearing sp...

In this study, we provide comparative analysis of the so-called “threshold conditions” for conditional (deterministic, CML) and unconditional (stochastic, UML) maximum likelihood estimation. Specifically, we analyze SNR and sample support values where the accurate UML and CML DoA estimation starts to rapidly divert from the Cramér-Rao bound (CRB) d...

We consider the problem of covariance matrix estimation for strongly non-homogeneous data (clutter), modelled as spherically invariant complex random vectors. When normalized, such data are described by a complex angular Gaussian distribution. For a number of independent identically distributed (i.i.d.) samples with this distribution, we introduce...

In this paper we derive a generic signal processing model for oversampled linear antenna arrays based on network theory and Nyquist sampling theory. The theoretical model is verified with experimental data collected on an HF OTHR receive array.

This work addresses the problem of spatial compressive sensing (SCS) DOA estimation performance evaluation by exploiting an estimation-theoretic method known as expected likelihood (EL). This work provides a novel application of the EL method to mitigate two bias sources present in the SCS DOA estimation approach due to discretization of the azimut...

Comparative analysis of the threshold SNR and/or sample support values where genuine maximum likelihood DOA estimation starts to produce "outliers" is conducted for unconditional (stochastic) and conditional (deterministic) problem formulations. Theoretical predictions based on recent results from Random Matrix Theory (RMT) are provided and sup por...

This paper reports results of an experimental program called the Mode Selection Experiment which was designed to demonstrate ionospheric propagation mode selectivity on transmit over a one-way skywave propagation path. This corresponds to the transmitter-to-target part of the two way propagation path used in OTHR. The purpose of the experiment was...

We analyze the performance of a recently introduced class of two-dimensional (2-D) multivariate parametric models for space-time adaptive processing (STAP) in airborne radars on the DARPA airborne side-looking radar model known as KASSPER Dataset 1. Investigation of the impact of linear uniform antenna array errors on techniques that exploit spatia...

Current operational HF over-the-horizon (OTH) radars are now accepted as effective and comparatively low-cost wide-area surveillance sensors. They are routinely used to provide air and surface situational awareness over vast regions of land and sea. The technology in, and performance of, these current generation radars is impressive, however, there...

In this paper, the “expected likelihood” approach, previously introduced for the stochastic (unconditional) Gaussian case, is extended over the so-called deterministic (conditional) Gaussian case. Direction of arrival (DOA) estimation when arbitrary temporally correlated waveforms transmitted by point sources of interest impinge onto a uniformly sp...

The convergence rate of a number of adaptive processing algorithms for coherent signal extraction from Gaussian interference is compared. Our main attention is paid to a relatively new hybrid method of regularization of the maximum-likelihood estimate (MLE) of the covariance matrix (CM) of Gaussian vectors with discrete and continuous power spectra...

Use of multiple transmit waveforms to enable MIMO radar opera-tion is a technology with strong application to HF over-the-horizon (OTH) radar. We consider the problem of target detection when the OTH radar is operating in an environment with a stable ionospheric propagation path supporting high quality Doppler spectra from backscattered signals and...

In this study, we analyse sensitivity of the likelihood ratio (LR) p.d.f with respect to the residual temporal correlation of antenna training samples, caused by non-rectangular band-pass filters and over-sampling. This temporal correlation causes deviation of the actual LR p.d.f. from the theoret-ical one derived for independent (Gaussian) trainin...

Finite amount of data spectrum sensing effects are addressed in decentralized dynamic spectrum allocation (DSA) that exploits adaptive antenna array interference mitigation (IM) diversity at the receiver. The system is based on spectrally efficient filter bank multi-carrier (FBMC) PHY and consists of base stations (BSs) that use a “good neighbor” r...

We introduce an iterative procedure for design of adaptive KL-variate linear beamformers that are structured as the Kronecker product of K-variate (transmit) and L-variate (receive) beamformers. We focus on MIMO radar applications for scenarios where only joint transmit and receive adaptive beamforming can efficiently mitigate multi-mode propagated...

We reexamine the well-known problem of "threshold behavior" or "performance breakdown" in the detection-estimation of very closely spaced emitters. In this extreme regime, we analyze the performance for maximum-likelihood estimation (MLE) of directions-of-arrival (DOA) for two close Gaussian sources over the range of sample volumes and signal-to-no...

This paper presents a new sensor concept designed to provide maritime domain awareness over large ocean areas. The Mode-Selective OTHR introduced herein achieves significant detection and tracking capability against maritime vessels relative to traditional OTHR designs because it is designed specifically to reject disturbed ionospheric propagation...

Decentralized dynamic spectrum allocation (DSA) that exploits adaptive antenna array interference mitigation (IM) diversity at the receiver, is addressed in interference limited environment with high level of frequency reuse. The system consists of base stations (BSs) that may belong to different providers in license-exempt spectrum, who can optimi...

Performance assessment of algorithms for direction of arrival (DOA) estimation are typically done using large-sample justified asymptotic constructs such as consistency, efficiency, and the Cramér–Rao lower bound. The performance in parameter accuracy (usually the mean square error of the DOA estimate) of the algorithm relative to the true paramete...

“Performance breakdown” of maximum-likelihood (ML) direction-of-arrival (DoA) estimation is analyzed. “Performance breakdown” occurs when signal-to-noise ratio (SNR) and/or training sample volume fall below some threshold values and a ML set of DoA estimates calculated for properly detected number of sources, unavoidably contains an estimation “out...

A new class of decentralized dynamic spectrum allocation (DSA) algorithms that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is proposed for interference-limited environments with high level of frequency reuse. The system model consists of base stations (BS) that can optimize uplink frequency allocation to t...

Decentralized dynamic spectrum allocation (DSA) that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is addressed in interference-limited environment with high level of frequency reuse. The system consists of base stations (BSs) that may belong to different providers in license-exempt spectrum, who can optimiz...

The problem of a point target detection masked by clutter distributed over range and Doppler, including the range and Doppler of the target, is considered for a multimode propagation scenario commonly encountered in quasimonostatic HF over-the-horizon radars (OTHR). Here, a clutter signal spread in Doppler frequency due to propagation via a disturb...

The well-known problem of adaptive signal detection in background interference is addressed for situations where only a small number of training data samples are available. Since all known constant false-alarm rate (CFAR) adaptive detectors such as the traditional generalized likelihood-ratio test (GLRT), adaptive matched filter (AMF), and adaptive...

We characterize a sequence of M interference observations by a time-varying autoregressive model of order m (TVAR(m)). We recently demonstrated that the maximum-likelihood (ML) TVAR(m) covariance matrix estimate (CME) of Gaussian data is the Dym-Gohberg transformation of the sample (direct data) covariance matrix averaged over the T independent tra...

We introduce an iterative procedure for design of adaptive KL-variate linear beamformers that are structured as the Kronecker product of K-variate (transmit) and L-variate (receive) beamformers. Focusing on MIMO radar applications for scenarios where only joint transmit and receive adaptive beamforming can efficiently mitigate multi-mode propagated...

This chapter introduces the expected likelihood approach as a mechanism that allows assessment of the quality of estimates without resorting to asymptotic or clairvoyant analysis. To address an important low-sample support regime, the expected likelihood approach was expanded into the sample data circumstances where the number of samples T does not...

The central statistical problem in many applications such as radar, electronic warfare and sonar, is to find a certain parametric model of the M-variate covariance matrix of the input data, given a number T of observed independent identically distributed (iid) training data samples yj ε CM × 1 (j = 1, . . . , T ). Typically the training data is obs...

Performance of maximum-likelihood estimation (MLE) is analysed in the so-called threshold region. Here, due to insufficient training sample volume and/or signal-to-noise ratio, the actual MLE performance degrades considerably with respect to the Cramer-Rao bound, because of the onset of severely erroneous estimates ("outliers"). Recently, for a lim...

Spatial calibration of OTHR transmitting and receiving arrays is an important issue when implementing this class of radar. In the paper we demonstrate how MIMO radar techniques can be applied to the calibration of an OTHR transmit array. We provide experimental results to validate our approach.

We analyse an iterative adaptive multiple-input-multiple-output (MIMO) radar receiver in the situation where a K L-variate adaptive transmit-receive beamformer is structured as the Kronecker product of a K-variate (transmit) and an L-variate (receive) beamformer. We present results for the special case of two clutter propagation modes separated in...

We introduce an iterative adaptive multiple-input-multiple-output (MIMO) radar receiver that is useful when the KL-variate adaptive transmit-receive beamformer is structured as the Kronecker product of a K-variate transmit and an L-variate receive beamformer. We consider the case of two clutter propagation modes with different elevation angles, and...

A potential global performance of dynamic spectrum allocation (DSA) that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is analyzed for interference-limited environments with high level of frequency reuse assuming Rayleigh propagation model. The system consists of base stations (BSs) that may belong to differ...