Recently, the authors proposed a miniaturized microphone array not utilizing the phase difference but utilizing the directivity of each microphone, namely aggregated microphones. We have already showed that the phased...
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ISBN:
(纸本)1424403081
Recently, the authors proposed a miniaturized microphone array not utilizing the phase difference but utilizing the directivity of each microphone, namely aggregated microphones. We have already showed that the phased microphone array and the aggregated microphones can be described within the same framework. We have also showed that it is possible to apply the aggregated microphones to the various methods of the phased microphone array. However, the difference of the performance between the phased array and the aggregated microphones has not been evaluated yet. The effect of the directivity and the posture of each microphone on the performance of the aggregated microphones has not also been evaluated yet. In this paper, we evaluate the performance of DCMP (Directionally Constrained Minimization of Power) adaptive array utilizing aggregated microphones.
Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance;nevertheless, it poses additional challeng...
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ISBN:
(纸本)1424403081
Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance;nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. I n this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3(rd)-order pi-segmented model of O'Brien-Savarino [4] is calculated for a 16-block fine with block length equal to 0.3m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays.
This paper is concerned with new fast adaptive beamforming algorithms which are based on the internal model principle, to deal with fast fading environment to track the desired signal changes and suppress the interfer...
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ISBN:
(纸本)1424403081
This paper is concerned with new fast adaptive beamforming algorithms which are based on the internal model principle, to deal with fast fading environment to track the desired signal changes and suppress the interferences. The LMS and RLS algorithms for constructing nulls are derived by incorporating an AR model into the weight dynamics, and then can track fast fading environment. The convergence analysis of mean and mean-square error of the weight vector are also investigated and stability condition is clarified. Numerical simulation results show that the proposed algorithms can improve tracking ability and BER performance in DS-CDMA systems.
By taking the third-order statistical information of processes into account, the bispectrum is a useful tool in digital signalprocessing and statistics. The paper proposes a nonparametric approach of estimating the b...
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ISBN:
(纸本)1424403081
By taking the third-order statistical information of processes into account, the bispectrum is a useful tool in digital signalprocessing and statistics. The paper proposes a nonparametric approach of estimating the bispectrum, using tapers designed to achieve maximal bifrequency concentration. Bispectra are functions of two frequencies plus their sum, so the optimum tapers are not products of Slepian sequences. The new tapers minintize the sixth-moment "energy" leakage in the estimate, and thus the new multiple window bispectrum estimator (MWBE) can be interpreted as minimizing the broad-band bias. Alternatively, the MWBE can be viewed as a solution of an integral inverse problem using an eigenfunction expansion. This approach can be extended to estimate higher-order polyspectra. Numerical simulations use moving average (MA) data with non-Gaussian white driving noise. Simulation results with small sample sizes show that this new MWBE is feasible and mean-squared error (MSE) optimal.
A wide range of applications involve matrix decompositions which can be computed using Givens rotations. A programmable processor for Givens rotations offers more flexibility than highly tailored systolic array hardwa...
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ISBN:
(纸本)1424403081
A wide range of applications involve matrix decompositions which can be computed using Givens rotations. A programmable processor for Givens rotations offers more flexibility than highly tailored systolic array hardware implementations. The programmable processor design presented in this paper employs an approximate rotations method to compute Givens rotations. Instantiations of this programmable processor can then be arranged/configured (i.e. in arrays of varying size and dimension) according to the requirements of the target application. Another advantage of this approach is that the processor can be programmed to compute different algorithms (e.g. QR decomposition, singular-value decomposition or a combination of both).
(1) In this paper we review performance bounds, as well as some current trends, in time delay estimation (TDE). Research over several decades reveals that a few key parameters determine TDE performance. The most basic...
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ISBN:
(纸本)1424403081
(1) In this paper we review performance bounds, as well as some current trends, in time delay estimation (TDE). Research over several decades reveals that a few key parameters determine TDE performance. The most basic are the signal-to-noise ratio (SNR), and the signal time-bandwidth (TB) product;larger values for each are desirable. The Cramer-Rao bound (CRB) reveals asymptotic maximum-likelihood estimation (MLE) behavior with respect to TB and SNR. At moderate to lower SNR, TDEs generally break down as ambiguities arise due to increased noise and the cross-correlation of the signal, causing the TDE to deviate (often quite sharply) away from the CRB. Because it is a local bound, the CRB does not indicate the threshold behavior, and Ziv-Zakai and other bounds have been developed to handle this. When TD is measured between multiple sensors, the coherence between them can fundamentally limit the result, an effect that occurs in acoustics due to the turbulent atmosphere. We discuss modifications to the classical bounds that accommodate the coherence loss, and reveal a threshold coherence phenomenon. When communications and other signals are utilized for TDE, they may have significant nuisance parameters, including carrier uncertainty, unknown symbols, as well as effects due to an unknown channel. Recent TDE performance limits reveal the effect of these parameters for various signal models, including the impact of diversity channels on TDE.
The optimal array for detecting the signal from a desired direction but contaminated by receiver noise and strong interference from different sources with unknown arriving-angles is re-examined. The well-known optimal...
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ISBN:
(纸本)1424403081
The optimal array for detecting the signal from a desired direction but contaminated by receiver noise and strong interference from different sources with unknown arriving-angles is re-examined. The well-known optimal array is obtained by inverting the covariance matrix of interference and noise to maximize the signal to interference and noise ratio (SINR). In practice, the covariance matrix is unknown and has to be estimated by a sample covariance matrix. The optimal array is thus estimated by inverting the sample covariance matrix. This procedure has been employed in optimal array research without challenge. However, it is shown in this paper that the estimated optimal array fails to yield the highest SINR in the case of unknown arriving-angles. Instead the highest SINR can be achieved by optimally estimating the arriving-angles of interference followed by a constrained matched filter, which maximizes the signal to noise ratio subject to canceling the interference from the estimated arriving-angles. In order to reduce the computational burden, an angle-tracking system for multiple targets is adopted to achieve the optimal estimation of arriving-angles. The resulting system of angle-tracking adaptive array offers the highest SINR at a computational burden only on the order of N . M-2 multiplications within a radar range-cell Delta tau, rather than N-3 multiplications in the well-known but questionable estimated optimal array. Here N is the number of sensors in the array and M the number of interference sources. Typically, N = 1,000 in a planar radar array, M = 2 similar to 10 and Delta tau = 1 mu S. Numerical simulations confirm the theoretical results.
Non-Gaussian noise poses a challenge to conventional detector techniques. In such a case it is possible to design a nonlinear detector that performs better than the optimal linear detectors. Locally optimal detector i...
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ISBN:
(纸本)1424403081
Non-Gaussian noise poses a challenge to conventional detector techniques. In such a case it is possible to design a nonlinear detector that performs better than the optimal linear detectors. Locally optimal detector is one that has good performance when the signal is weak and the probability density function (PDF) of noise is known precisely. This paper deals with a new nonlinear detector for binary signal detection in Gaussian mixture noise. This detector is optimal without any constraints on signal strength, and it is convenient for non-Gaussian even symmetric PDF's. furthermore, it does not require the knowledge of the exact noise PDF We use maximum likelihood (ML) and maximum entropy, that are two optimal criteria, in obtaining this new detector. The proposed detector consists of new nonlinear functions followed by an accumulator and threshold comparator. These new nonlinear functions are polynomials consisting of odd power terms. Simulation results confirm the superiority of the new detector with respect to the previously proposed methods.
A novel criterion for waveform selection in adaptive radar and other sensing applications is presented that is based on the information theoretic concept of mutual information. In addition, its application to the area...
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ISBN:
(纸本)1424403081
A novel criterion for waveform selection in adaptive radar and other sensing applications is presented that is based on the information theoretic concept of mutual information. In addition, its application to the area of waveform diversity for synthetic aperture radar (SAR) systems is examined. Mutual information is a measure of the information (in the sense of Shannon) in a random variable or vector about another random variable or vector. It is shown herein that such a framework provides the basis for a conceptually simple and powerful criterion for context-dependent evaluation of candidate waveforms, as well as context-dependent design of waveforms. Furthermore, in the special case of zero-mean Gaussian-distributed clutter, interference, and noise, the criterion attains an analytically simple form - a scalar function of the singular values of a specific cross-covariance matrix. The criterion can be used in distinct optimization contexts (minimization or maximization) as a function of the problem to be addressed. In addition, the criterion inherently includes the statistical information of the sensed parameters. More specifically, in the context of a SAR system the criterion includes the covariance matrix of the set of illuminated ground scatterers. The formulation and simulation-based results are presented in the context of a first-order radar system model for simplicity, but the approach can be extended in a straightforward manner to cover more complex models. Results presented show that the criterion is an effective means for waveform selection in an adaptive SAR system.
In this paper, we study the problem of MIMO channel tracking for communication systems that use orthogonal space-time block codes as the underlying space-time coding scheme. For such systems, we develop a two-step cha...
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ISBN:
(纸本)1424403081
In this paper, we study the problem of MIMO channel tracking for communication systems that use orthogonal space-time block codes as the underlying space-time coding scheme. For such systems, we develop a two-step channel tracking algorithm. As the first step, our proposed method uses Kalman filtering to obtain an initial channel estimate, for each block, based on the channel estimate obtained for the previous block. In the second step, we use an iterative decision-directed method to refine the initial channel estimate obtained in the first step. We show that due to specific structure of OSTBC, both steps can be significantly simplified. Simulation results show that, for a training repetition period of 10 blocks, this algorithm can have a performance within 1 dB, in terms of SNR, from the coherent ML receiver which has the perfect knowledge of the channel.
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