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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Halimeh, Mhd Modar Huemmer, Christian Brendel, Andreas Kellermann, Walter Friedrich Alexander Univ Erlangen Nurnberg Multimedia Commun & Signal Proc Cauerstr 7 D-91058 Erlangen Germany

ISBN: (纸本)9781538647523

In this paper, the elitist resampling particle filter (ERPF) is introduced. The ERPF is an approach to combine generic particle filters, i.e., the SIS and SIR particle filter, based on an evolutionary selection of particles, which introduces a long-term memory to the selected group of the particles. Thereby, the ERPF aims at fusing the advantages, e.g., robustness and computational efficiency, and mitigating the drawbacks of each filter, e.g., degeneracy and sample impoverishment. Two variants of the ERPF are presented in this paper: the discrete ERPF (DERPF) and the continuous ERPF (CERPF), which to the authors' knowledge represent new forms of particle filters. The two proposed hybrids are compared to the corresponding original filters using two well-established benchmark models to illustrate that the evolutionary combinations provide a better estimation accuracy and exhibit an increased robustness against outliers.

关键词： Estimation Particle filters Robustness Sociology Statistics array signal processing"

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sensor scheduling using a 0-1 mixed integer programming framework

Sensor scheduling using a 0-1 mixed integer programming fram...

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4th ieee sensor array and multichannel signal processing workshop

作者： Chhetri, Amit S. Morrell, Darryl Papandreou-Suppappola, Antonia Arizona State Univ Dept Elect Engn Tempe AZ 85281 USA Arizona State Univ Dept Engn Tempe AZ 85281 USA

ISBN: (纸本)1424403081

In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 01 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

关键词： sensor networks

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A Real Time Tracker of Complex Circularity

A Real Time Tracker of Complex Circularity

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Kanna, Sithan Douglas, Scott C. Mandic, Danilo P. Univ London Imperial Coll Sci Technol & Med Dept EEE London SW7 2BT England So Methodist Univ Dept EE Dallas TX 75275 USA

ISBN: (纸本)9781479914814

A new insight into the relationship between the complex circularity quotient and the coefficient of a linear minimum mean square estimator (LMMSE) which estimates a complex random variable from its complex conjugate is established. An adaptive version of this estimator, suitable for real time tracking of the degree of complex circularity is proposed based on the complex least mean square (CLMS) algorithm. For Gaussian data, the mean and mean square analyses show the effect of data non-circularity on the stability bounds of the real time circularity tracker. The concept is verified over simulations on both synthetic single-and multi-channel data and on real world wind signals with varying degrees of circularity.

关键词： Complex random variables complex circularity circularity coefficient complex least mean square (CLMS) multi-channel signals

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2D MIMO Radar with Coprime arrays 10

2D MIMO Radar with Coprime Arrays

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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Li, Conghui Gan, Lu Ling, Cong Imperial Coll London Dept EEE London England Brunel Univ Sch Engn & Design London England

ISBN: (纸本)9781538647523

In this contribution, a new class of planar coprime MIMO radar systems based on quadratic integers is proposed where the antenna locations are represented by lattice points generated by prime integers in quadratic number fields. By exploiting the coprimality of certain quadratic integers, the virtual coarrays of proposed structures enjoy a quadratic gain in parameter identifiability according to the Chinese Remainder Theorem (CRT). To avoid holes in the coarray, we present Hole-free CRT arrays with guaranteed full-rank autocorrelation matrices for subspace-based target estimation. The ring of Gaussian integers and the ring of Eisenstein integers are chosen as examples of designing coprime MIMO radar systems. It is shown that the proposed arrays achieve enhanced angular resolutions and improve the side lobe suppression. In the context of target estimation, simulations show the superior performance of the coprime MIMO structures based on CRT.

关键词： Coprime sensing MIMO sparse arrays quadratic integers Chinese Reminder Theorem

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Sparse Channel Estimation for IRS-Aided Systems Exploiting 2-D Sparse arrays 12

Sparse Channel Estimation for IRS-Aided Systems Exploiting 2...

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ieee 12th sensor array and multichannel signal processing workshop (SAM)

作者： Haider, Mirza Asif Chowdhury, Md. Waqeeb T. S. Zhang, Yimin D. Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA

ISBN: (纸本)9781665406338

Intelligent reflecting surface (IRS) is a promising next-generation technology for increasing channel capacity and reducing power consumption. In this paper, we present a novel IRS configuration consisting of a small number of active elements in an optimized L-shaped sparse array to separately estimate the channels between the base station and the IRS, and the channel between multiple user equipment and the IRS. Structured matrix completion techniques are used to attain superior direction-ofarrival estimation performance with an increased number of degrees of freedom. The training overhead is minimized in the proposed system and is not directly related to the number of IRS reflecting elements. The proposed sparse array strategy simultaneously resolves multiple sources with a high accuracy and outperforms the L-shaped uniform array counterpart using the same number of active elements. The effectiveness of the proposed strategy is confirmed using simulation results.

关键词： Intelligent reflecting surface active elements sparse array structured matrix completion channel estimation

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Joint source and relay optimization for a non-regenerative MIMO relay

Joint source and relay optimization for a non-regenerative M...

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4th ieee sensor array and multichannel signal processing workshop

作者： Fang, Zheng Hua, Yingbo Koshy, John C. Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA Telecordia Technol Adv Wireless Signal Processing Res Red Bank NJ USA

ISBN: (纸本)1424403081

We consider a non-regenerative MIMO relay system where the source, relay and destination are all equipped with multiple antennas. The relay does not decode the packets but performs a multidimensional amplify-and-forward function (a relay matrix) on the baseband signals. Under the condition that the source is white, the relay matrix that maximizes the capacity between the source and the destination has been previously found. In this paper, we show a new result on how the source covariance matrix and the relay matrix can be jointly optimized to maximize the source-destination capacity. It is shown that the optimal coordinate system governed by the previously discovered relay matrix is still valid under the joint optimization, and the joint optimization yields a further capacity gain when the SNR at the relay is low.

关键词： Radio links

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Toward bandwidth invariance of spatial processing in the non-cooperative receiver

Toward bandwidth invariance of spatial processing in the non...

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4th ieee sensor array and multichannel signal processing workshop

作者： Shaw, Arnab Jamali, Moshin Wilkins, Nathan Wright State Univ 3640 Colonel Glenn Highway Dayton OH 45435 USA Univ Toledo Toledo OH 43606 USA AF Res Lab Wright Patterson AFB OH 45433 USA

ISBN: (纸本)1424403081

As the modern electro-magnetic environment in urban and battlefield scenarios becomes increasingly denser, system designers tend to gravitate toward wide bandwidth solutions. Not only do spread spectrum designs permit increased co-channel utilization, they also tend to be inherently more secure, decreasing the probability of intercept by non-cooperative receivers. This is in part due to the code that must be applied in order to modulate the information bandwidth into a much wider transmitted bandwidth. In addition the non-cooperative receiver must contend with issues of increased noise, decreased sensitivity, and increased signal processing resource requirements among others. The problem is further exacerbated for receivers that must perform emitter geo-location or other forms of spatial processing, since the conventional high-resolution techniques rely on phase measurements based on the monochromatic assumption. This paper will discuss some of the existing methods suggested to contend with wide bandwidth spatial processing for noncooperative receivers and their limitations. It will introduce a new method based on the bilinear transformation that overcomes some of these limitations. It will present simulation results that demonstrate the advantage of this technique.

关键词： signal receivers

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Parametric GLRT for multichannel adaptive signal detection

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ieee TRANSACTIONS ON signal processing 2007年第11期55卷 5351-5360页

作者： Sohn, Kwang June Li, Hongbin Himed, Braham Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA USAF Res Lab SNRT Rome NY 13441 USA

This paper considers the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbance. A parametric generalized likelihood ratio test (GLRT) is developed by modeling the disturbance as a multichannel autoregressive (AR) process. Maximum likelihood (ML) parameter estimation underlying the parametric GLRT is examined. It is shown that the ML estimator for the alternative hypothesis is nonlinear and there exists no closed-form expression. To address this issue, an asymptotic ML (AML) estimator is presented, which yields asymptotically optimum parameter estimates at reduced complexity. The performance of the parametric GLRT is studied by considering challenging cases with limited or no training signals for parameter estimation. Such cases (especially when training is unavailable) are of great interest in detecting signals in heterogeneous, fast changing, or dense-target environments, but generally cannot be handled by most existing multichannel detectors which rely more heavily on training at an adequate level. Compared with the recently introduced parametric adaptive matched filter (PAMF) and parametric Rao detectors, the parametric GLRT achieves higher data efficiency, offering improved detection performance in general.

关键词： generalized likelihood ratio test (GLRT) maximum likelihood (ML) parameter estimation multichannel signal detection parametric models space-time adaptive processing (STAP)

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Node density and range improvement in cooperative networks using randomized Sspace-time block coding with time synchronization errors

Node density and range improvement in cooperative networks u...

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4th ieee sensor array and multichannel signal processing workshop

作者： Palat, Ramesh Chembil Annamalai, A. Reed, Jeffrey H. Virginia Tech Mobile & Portable Radio Res Grp Blacksburg VA 24061 USA

ISBN: (纸本)1424403081

Cooperative communication in energy-constrained networks is a topic of emerging interest in recent years especially for sensor network applications. We consider cooperative transmission from a cluster of nodes to a remote receiver. The transmission protocol used is randomized orthogonal space-time block coding, which allows each node to randomly transmit one column of a given orthogonal space-time code matrix. Previous work on the topic has shown that the scheme can achieve maximum possible diversity order for a given SNR as the number of cooperating nodes increases. In this paper we examine the range extension achievable under realistic conditions accounting for time synchronization errors and use of pulse shaping filters. We show that the scaling of range as the number of nodes increase with timing error is not linear. It reaches a limit beyond which range improvement is not significant.

关键词： sensor networks

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multichannel thresholding with sensing dictionaries

Multichannel thresholding with sensing dictionaries

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2nd ieee International workshop on Computational Advances in Multi-sensor Adaptive processing

作者： Gribonval, Remi Mailhe, Boris Rauhut, Holger Schnass, Karin Vandergheynst, Pierre Ecole Polytech Fed Lausanne Signal Proc Inst ITS CH-1015 Lausanne Switzerland

ISBN: (纸本)9781424417131

This paper shows introduces the use sensing dictionaries for p-thresholding, an algorithm to compute simultaneous sparse approximations of multichannel signals over redundant dictionaries. We do both a worst case and average case recovery analyses of this algorithm and show that the latter results in much weaker conditions on the dictionary, sensing dictionary pair. We then do numerical simulations to confirm our theoretical findings, showing that p-thresholding is an interesting low complexity alternative to simultaneous greedy or convex relaxation algorithms for processing sparse multichannel signals with balanced coefficients, and finally point a connection to compressed sensing exploiting the additional freedom in designing the sensing dictionary.

关键词： Multidimensional signal processing

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