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30
Multichannel Blind Deconvolution: Fir Matrix Algebra And Separation Of Multipath Mixtures
, 1996
"... A general tool for multichannel and multipath problems is given in FIR matrix algebra. With Finite Impulse Response (FIR) filters (or polynomials) assuming the role played by complex scalars in traditional matrix algebra, we adapt standard eigenvalue routines, factorizations, decompositions, and mat ..."
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Cited by 87 (0 self)
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A general tool for multichannel and multipath problems is given in FIR matrix algebra. With Finite Impulse Response (FIR) filters (or polynomials) assuming the role played by complex scalars in traditional matrix algebra, we adapt standard eigenvalue routines, factorizations, decompositions, and matrix algorithms for use in multichannel /multipath problems. Using abstract algebra/group theoretic concepts, information theoretic principles, and the Bussgang property, methods of single channel filtering and source separation of multipath mixtures are merged into a general FIR matrix framework. Techniques developed for equalization may be applied to source separation and vice versa. Potential applications of these results lie in neural networks with feedforward memory connections, wideband array processing, and in problems with a multiinput, multioutput network having channels between each source and sensor, such as source separation. Particular applications of FIR polynomial matrix alg...
A performance analysis of subspacebased methods in the presence of model errors: Part 1The MUSIC algorithm
 Stanford University
, 1981
"... AbstractThis is the second of a twopart paper dealing with the performance of subspacebased algorithms for narrowhand directionofarrival (DOA) estimation when the array manifold and noise covariance are not correctly modeled. In Part I, the performance of the MUSIC algorithm was investigated. ..."
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Cited by 64 (15 self)
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AbstractThis is the second of a twopart paper dealing with the performance of subspacebased algorithms for narrowhand directionofarrival (DOA) estimation when the array manifold and noise covariance are not correctly modeled. In Part I, the performance of the MUSIC algorithm was investigated. In Part 11, we extend this analysis to multidimensional (MD) subspacebased algorithms including deterministic (or conditional) maximum likelihood, MDMUSIC, weighted subspace fitting (WSF), MODE, and ESPRIT. A general expression for the variance of the DOA estimates is presented that can be applied to any of the above algorithms and to any of a wide variety of scenarios (e.g., gain/phase errors, mutual coupling, sensor position errors, noise covariance mismodeling, etc.). Optimally weighted subspace fitting algorithms are also presented for special cases involving random unstructured errors to the array manifold and noise covariance. In addition, it is shown that onedimensional MUSIC outperforms all of the above MD algorithms for random angleindependent array perturbations. I.
Recent Developments in Blind Channel Equalization: From Cyclostationarity to Subspaces
 Signal Processing
, 1996
"... Since Tong, Xu and Kailath [1] demonstrated the feasibility of identifying possibly nonminimum phase channels using secondorder statistics, considerable research activity, both in algorithm development and fundamental analysis, has been seen in the area of blind identification of multiple FIR chan ..."
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Cited by 47 (1 self)
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Since Tong, Xu and Kailath [1] demonstrated the feasibility of identifying possibly nonminimum phase channels using secondorder statistics, considerable research activity, both in algorithm development and fundamental analysis, has been seen in the area of blind identification of multiple FIR channels. Many of the recently developed approaches invoke, either explicitly or implicitly, the algebraic structure of the data model, while some others resort to the use of cyclic correlation/spectral fitting techniques. The objective of this paper is to establish insightful connections among these studies and present recent developments of blind channel equalization. We also unify various representative algorithms into a common theoretical framework. 1 1
Multiple invariance ESPRIT
 IEEE Trans. Signal Process. 1992
"... A h t r n c f ESPRIT is a recently developed technique for highresolution signal parameter estimation. For the specific problem of directionofarrival (DOA) estimation, a decrease in computational complexity of orders of magnitude over other highresolution methods is achieved by exploiting an ..."
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Cited by 33 (7 self)
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A h t r n c f ESPRIT is a recently developed technique for highresolution signal parameter estimation. For the specific problem of directionofarrival (DOA) estimation, a decrease in computational complexity of orders of magnitude over other highresolution methods is achieved by exploiting an inunriancc slrucltrre denigned into the sensor array. Previously, €SPR/T took advantage of only one such invariance per dimension of the parameter vector. The ubiquitous uniform linear array is an example of a sensor array possessing many such invariances, and the qriestiori of which invariance to use naturally arises. In this paper, ESPRlT is extended to address the problem of exploiting all the invariances siniultaireously. The nonlinear multiple invariance ESPRIT algorithm is derived and compared via simulation to various standard ESPR/r solutions possible for arrays with multiple invariances. I.
ON THE IDENTIFICATION OF PARAMETRIC UNDERSPREAD LINEAR SYSTEMS
"... Identification of timevarying linear systems, which introduce both timeshifts (delays) and frequencyshifts (Dopplershifts), is a central task in many engineering applications. This paper studies the problem of identification of underspread linear systems (ULSs), defined as timevarying linear sy ..."
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Cited by 30 (11 self)
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Identification of timevarying linear systems, which introduce both timeshifts (delays) and frequencyshifts (Dopplershifts), is a central task in many engineering applications. This paper studies the problem of identification of underspread linear systems (ULSs), defined as timevarying linear systems whose responses lie within a unitarea region in the delay–Doppler space, by probing them with a known input signal. The main contribution of the paper is that it characterizes conditions on the bandwidth and temporal support of the input signal that ensure identification of ULSs described by a finite set of delays and Dopplershifts, and referred to as parametric ULSs, from single observations. In particular, the paper establishes that sufficientlyunderspread parametric linear systems are identifiable as long as the time–bandwidth product of the input signal is proportional to the square of the total number of delay–Doppler pairs in the system. In addition, the paper describes a procedure that enables identification of parametric ULSs from an input train of pulses in polynomial time by exploiting recent results on subNyquist sampling for time delay estimation and classical results on recovery of frequencies from a sum of complex exponentials. 1.
Analysis of a Decision Directed Beamformer
, 1995
"... In this paper we study a technique for using decision direction to extract digital signals from antenna array data. The algorithm alternates between (1) estimating and demodulating the received signals, and (2) using the resulting bit decisions to regenerate the signal waveforms and recompute the be ..."
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Cited by 22 (5 self)
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In this paper we study a technique for using decision direction to extract digital signals from antenna array data. The algorithm alternates between (1) estimating and demodulating the received signals, and (2) using the resulting bit decisions to regenerate the signal waveforms and recompute the beamformer weights. An analysis of the (asymptotic) symbol error rate performance of the algorithm for the case of Mary PSK signals is included, along with several representative simulation examples. This work was supported in part by a contract from ESystems, Inc., Greenville Division (Dr. William A. Gardner, Principal Investigator), and by the National Science Foundation under grant MIP9110112. 1. Introduction The problem of extracting communication signals using an array of sensors is one of increasing importance to modern communications. For example, as the demand for bandwidth and time slots in mobile cellular radio systems increases, thought has been given to the use of multiple an...
The Effects of Array Calibration Errors on DFBased Signal Copy Performance
 IEEE Trans. on Signal Processing
, 1995
"... This paper studies the effect of array calibration errors on the performance of various DF (direction finding) based signal copy algorithms. Unlike blind copy methods, this class of algorithms requires an estimate of the directions of arrival (DOAs) of the signals in order to compute the copy weight ..."
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Cited by 18 (5 self)
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This paper studies the effect of array calibration errors on the performance of various DF (direction finding) based signal copy algorithms. Unlike blind copy methods, this class of algorithms requires an estimate of the directions of arrival (DOAs) of the signals in order to compute the copy weight vectors. Under the assumption that the observation time is sufficiently long, the following algorithms are studied: classical beamforming, least squares, total least squares, linearly constrained minimum variance beamforming, and structured stochastic estimation. Expressions for the meansquare error of the signal estimates are derived as a function of the calibration errors for both the case where the DOAs are known precisely and for the case where the DOAs must be estimated. This work was supported by a contract from ESystems, Inc., Greenville Division (Dr. William A. Gardner, Principal Investigator), and by the National Science Foundation under grant MIP9110112. 1. Introduction An im...
Instantaneous And FrequencyWarped Signal Processing Techniques For Auditory Source Separation
, 1994
"... This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of FrequencyWarped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complexvalued, frequencyvarying sinusoid p[n ..."
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Cited by 18 (0 self)
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This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of FrequencyWarped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complexvalued, frequencyvarying sinusoid p[n], transforming it into a signal with slowlyvarying parameters. This transformation facilitates the removal of p[n] from an additive mixture while minimizing the amount of damage done to other signal components. The average winding rate of a complexvalued phasor is explored as an estimate of the instantaneous frequency. Theorems are provided showing the robustness of this measure. To implement frequency tracking, a FrequencyLocked Loop algorithm is introduced which uses the complex winding error to update its frequency estimate. The input signal is dynamically demodulated and filtered to extract the envelope. This envelope may then be remodulated to reconstruct the target partial, which ...
Geolocation of RF Emitters by Many UAVs
"... This paper presents an approach to using a large team of UAVs to find radio frequency (RF) emitting targets in a large area. Small, inexpensive UAVs that can collectively and rapidly determine the approximate location of intermittently broadcasting and mobile RF emitters have a range of applications ..."
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Cited by 9 (3 self)
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This paper presents an approach to using a large team of UAVs to find radio frequency (RF) emitting targets in a large area. Small, inexpensive UAVs that can collectively and rapidly determine the approximate location of intermittently broadcasting and mobile RF emitters have a range of applications in both military, e.g., for finding SAM batteries, and civilian, e.g., for finding lost hikers, domains. Received Signal Strength Indicator (RSSI) sensors on board the UAVs measure the strength of RF signals across a range of frequencies. The signals, although noisy and ambiguous due to structural noise, e.g., multipath effects, overlapping signals and sensor noise, allow estimates to be made of emitter locations. Generating a probability distribution over emitter locations requires integrating multiple signals from different UAVs into a Bayesian filter, hence requiring cooperation between the UAVs. Once likely target locations are identified, EOcamera equipped UAVs must be tasked to provide a video stream of the area to allow a user to identify the emitter. I.