Search

The design problem of Infinite Impulse Response (IIR) digital filters is usually expressed as the minimization problem of the complex magnitude error that includes both the magnitude and phase information. However, the group delay of the filter obtained by solving such design problem may be far from the desired group delay. In this paper, we propose a design method of stable IIR digital filters with prespecified maximum group delay errors. In the proposed method, the approximation problems of the magnitude-phase and group delay are separately defined, and these two approximation problems are alternately solved using successive projections. As a result, the proposed method can design the IIR filters that satisfy the prespecified allowable errors for not only the complex magnitude but also the group delay by alternately executing the coefficient update for the magnitude-phase and the group delay approximation. The usefulness of the proposed method is verified through some examples. Keywords--Filter design, Group delay approximation, Stable IIR filters, Successive projection method., I. INTRODUCTION Finite-impulse response (FIR) digital filters find many applications in image processing, waveform transmission, etc. in which phase distortion becomes a problem, because they can easily realize an exactly [...]

A new approach is presented for assessing the effectiveness of noncoherent integrations in Global Navigation Satellite System (GNSS) signal acquisition. In the light of the renewed interest in weak signal detection and considering the limitations of coherent integration, it is critical to possess a tool in order to predict and evaluate the impact of noncoherent integrations on signal detection performance. The challenge is the statistic of the noise component, preventing the computation of exact signal-to-noise (SNR) ratios when combinations of coherent and noncoherent integrations are utilized. An original approach is presented to enable this comparison through an equivalent area criterion based on the popular receiver operating characteristic (ROC) curves. The equivalent area approach is compared with past techniques, and the performance of each method is analyzed for highlighting the effectiveness of the proposed criterion.

In this contribution, we derive exact closed-form expressions for the average symbol error probability (SEP) of arbitrary rectangular quadrature amplitude modulation (QAM) for single--and multichannel diversity reception over independent but not-necessarily identically distributed Nakagami-m fading channels. The diversity branches may hence exhibit identical or distinctive power levels and their associated Nakagami indexes need not be the same. Our work extends previous results pertaining to nondiversity reception of M-ary rectangular QAM over Rayleigh fading channels and multichannel reception of M-ary square QAM over Nakagami-m fading channels. For a given number L of diversity branches and a corresponding set of arbitrary real-valued Nakagami indexes not less than 1/2, our SEP results are expressed in terms of Gauss's hypergeometric function [sub.2][F.sub.1] and Lauricelia's multivariate hypergeometric function [F.sup.(L).sub.D] of L variables, both of which can be efficiently evaluated using standard numerical softwares. Index Terms--Rectangular QAM, Gaussian Q-function, Nakagami fading, maximal-ratio combining, symbol error rate.

The problem of detection and possible estimation of a signal generated by a dynamic system when a variable number of noisy measurements can be taken is here considered. Assuming a Markov evolution of the system (in particular, the pair signal-observation forms a hidden Markov model (HMM)), a sequential procedure is proposed, wherein the detection part is a sequential probability ratio test (SPRT) and the estimation part relies upon a maximum a posteriori probability (MAP) criterion, gated by the detection stage (the parameter to be estimated is the trajectory of the state evolution of the system itself). A thorough analysis of the asymptotic behavior of the test in this new scenario is given, and sufficient conditions for its asymptotic optimality are stated, i.e., for almost sure minimization of the stopping time and for (first-order) minimization of any moment of its distribution. An application to radar surveillance problems is also examined. Index Terms--Asymptotic optimality, hidden Markov models (HMM), sequential detection and estimation, sequential probability ratio test (SPRT).

We consider the problem of decentralized detection in a network consisting of a large number of nodes arranged as a tree of bounded height, under the assumption of conditionally independent and identically distributed (i.i.d.) observations. We characterize the optimal error exponent under a Neyman-Pearson formulation. We show that the Type II error probability decays exponentially fast with the number of nodes, and the optimal error exponent is often the same as that corresponding to a parallel configuration. We provide sufficient, as well as necessary, conditions for this to happen. For those networks satisfying the sufficient conditions, we propose a simple strategy that nearly achieves the optimal error exponent, and in which all non-leaf nodes need only send 1-bit messages. Index Terms--Decentralized detection, error exponent, sensor networks.

A new test is proposed for determining the stationarity length of a locally wide sense stationary Gaussian random process. Computer simulation results have demonstrated its effectiveness and have verified the asymptotic theoretical performance of the test, which can be applied to spectral analysis, noise estimation and time series modeling.

In this paper, we consider the detection of binary (antipodal) signals transmitted in a spatially multiplexed fashion over a fading multiple-input--multiple-output (MIMO) channel and where the detection is done by means of semidefinite relaxation (SDR). The SDR detector is an attractive alternative to maximum-likelihood (ML) detection since the complexity is polynomial rather than exponential. Assuming that the channel matrix is drawn with independent identically distributed (i.i.d.) real-valued Gaussian entries, we study the receiver diversity and prove that the SDR detector achieves the maximum possible diversity. Thus, the error probability of the receiver tends to zero at the same rate as the optimal ML receiver in the high signal-to-noise ratio (SNR) limit. This significantly strengthens previous performance guarantees available for the semidefinite relaxation detector. Additionally, it proves that full diversity detection is also possible in certain scenarios when using a noncombinatorial receiver structure. Index Terms--Detection, diversity, multiple-input--multiple-output (MIMO), semidefinite relaxation (SDR).

An explicit expression is obtained for the probability density function (pdf) of the square magnitude of the normalized cross wavelet spectrum for the self-normalized Morlet cross wavelet spectrum (NCM) detector considered for Plett. This expression has involved the Gauss hypergeometric function.

The problem of estimating the parameters in continuous-time stochastic signals, represented by continuous-time autoregressive moving average (CARMA) processes, from discrete-time data is analyzed. It is shown that the variances are close to the Cramer-Rao bound for certain choices of the sampling interval and the number of covariance elements used in the criterion function.

A locally optimum estimator (LOE) is described by considering a wireless sensor network (WSN) engaged in a decentralized estimation problem. The local maximum-likelihood (ML) estimator is implemented, whose canonical structure and asymptotic properties are used for designing the quantizers.

The Chase family of detectors is introduced for multiple-input multiple-output (MIMO) channels. The B-chase detector has outperformed the BLAST-ordered decision-feedback detector by 4.4 dB while increasing complexity by only 17%.

In this paper, novel methods for detecting steady-state visual evoked potentials using multiple electroencephalogram (EEG) signals are presented. The methods are tailored for brain-computer interfacing, where fast and accurate detection is of vital importance for achieving high information transfer rates. High detection accuracy using short time segments is obtained by finding combinations of electrode signals that cancel strong interference signals in the EEG data. Data from a test group consisting of 10 subjects are used to evaluate the new methods and to compare them to standard techniques. Using 1-s signal segments, six different visual stimulation frequencies could be discriminated with an average classification accuracy of 84%. An additional advantage of the presented methodology is that it is fully online, i.e., no calibration data for noise estimation, feature extraction, or electrode selection is needed. Index Terms--BCI, EEG, signal detection, SSVEP, subspace, VEP.

Can a device that can perform hyperacuity vision tasks be built? In this paper, a feasibility study based on separation discrimination is conducted. Two types of ideal detectors are considered. The first is the stimulus defined statistically (SDS) detector by Geisler and Davilla. The second is one that estimates the uncertainty and then takes out its effect. In the first method, an array of many ideal stimulus defined exactly (SDE) detectors covers uncertainties and forms the ideal SDS detector. When the separation distance between the SDE detectors is around 1 arcmin, the SDS detector can achieve nearly optimal performance. To cover the motion uncertainty with nearly optimal performance, the SDE detector at each position needs to cover 16 directions, and at each direction, it needs to cover speeds with an increment of 0.5[degrees]/s. Typically, the SDS detector needs 7776 SDE detectors to deal with a speed up to 2[degrees]/s stimulus movement with a randomly selected direction and a 9 min x 9 min position uncertainty region. This ideal observer can achieve a hyperacuity threshold of 2-4 arcsec. Its threshold is almost constant over the range of speeds covered by the SDS detector. Using the second method, position estimation and motion tracking capability is examined. With perfect position estimation and motion tracking, the SDS detector can be reduced to a single SDE detector that is tuned to correct position and motion direction and speed. Two lower bounds on the estimation variance are examined, namely: 1) the Cramer-Rao bound and 2) the Ziv-Zakai bound. The results showed that if an estimation algorithm that can achieve the performance of bounds can be found, then the second method could achieve a hyperacuity capability of 1 s or less. The human visual system may more likely adopt the first method, but the second is simpler to use in building up a device using microprocessors. In this paper, dot-pair templates are used, which precisely match to dot-pair stimuli, to compute the likelihood and make a decision. The main difference between this paper and that of Geisler and Davilla lies in using a discrete sum over an array of SDE detectors to closely approximate continuous integration over the uncertain region, which makes it much easier in hardware implementation. Index Terms--Distributed detection, image resolution, signal detection, visual system.

Burst-mode receivers are key components of optical transmission systems, including passive optical networks, and have received much attention in recent years. We present new, efficient methods for burst optical signal detection in burst-mode data transmission using a modified K-means clustering technique. We also develop a data-aided feedforward symbol-timing recovery method based on a polynomial interpolation and maximum-likelihood estimation theory. A performance criterion considering the error caused by the interpolation approximation is derived for this method. The proposed detection and timing recovery approaches can be implemented effectively and rapidly; therefore, they are very suitable for burst-mode receivers. We also provide some numerical examples to demonstrate the performance of the proposed methods. Index Terms--Burst-mode receiver, K-means clustering, polynomial interpolation, signal detection, symbol-timing recovery.

We propose computationally inexpensive and efficient solutions for signal activity detection of phase-shift keying (PSK) signals in additive white Gaussian noise. We consider the complex amplitude of the signal, as well as the information sequence, as the unknown parameters. In addition, the noise variance is assumed unknown. We derive the generalized likelihood ratio test (GLRT) and suggest a computationally efficient implementation thereof. Furthermore, we develop a new inexpensive detector for binary PSK signals, which we will refer to as the generalized energy detector. To evaluate the performance of these detectors, we attempt to derive a uniformly most powerful invariant (UMPI) test as an optimal detector. It turns out that the UMPI test exists only if the signal-to-noise ratio is known. We use this UMPI test in order to obtain an upper-bound performance for the evaluation of invariant detectors, such as the GLRT. Simulation results illustrate and compare the performance and the efficiency of the proposed signal activity detectors. Index Terms--Additive Gaussian noise, binary detection problem, detection algorithms, generalized energy detector, generalized likelihood ratio (GLR), GLR detectors, invariances, invariant detectors, invariant hypothesis testing, matched filter detectors, maximal invariant statistic, maximum-likelihood (ML) detection, phase-shift keying (PSK), signal activity detection, signal classification, signal detection, uniformly most powerful invariant (UMPI) test.

Exact evaluation of bit- and symbol-error rates in a 2-D constellation is a fundamental problem of digital communications, which only for particular modulations and/or bits-to-symbol mapping has closed-form solutions. Here, we propose a general, numerically efficient algorithmic method, which yields the exact results for arbitrary modulation symbols' set and arbitrary bits-to-symbol mapping, and which deals with the case of nonuniform signaling. These three conditions define any digital transmission using memoryless modulation, so the proposed method is a general tool solving all problems tackled in the literature under constraints imposed on one or more of the parameters defining the modulation or signaling type. Such an evaluation tool is of practical importance during the design of the modulation. Our analysis and numerical simulations show the advantages offered by the new method when compared with the bounding techniques. Index Terms--Bit-error rate (BER), labeling, maximum a posteriori (MAP) detection, signaling, symbol-error rate (SER), uncoded transmission.

This paper proposes a strategy for the fast simulation of eddy current testing signals due to a conductive crack of arbitrary width. To cope with a crack of width less than that selected for establishing the database, which is necessary in the fast-forward analysis scheme proposed by authors, a new finite element is introduced to treat the case when the crack boundary is contained in the element. By using such a new element, the fast-forward analysis scheme becomes suitable for the reconstruction of both the shape and width of a planar crack. It is verified that such a multiple material element is efficient for an ECT sensor inducing eddy current parallel with the crack surface. For the case with perpendicular eddy current component, however, the approach is not valid because of a scalar potential jump at the crack surface. Finally, the reason of such a singularity is investigated through numerical simulations. Index Terms--Crack width, eddy current testing (ECT), fast simulation method, forward analysis, inverse analysis, new element.

This paper proposes a novel solution to two-dimensional (2-D) frequency estimation problems. The solution is applicable to the cases where the data length is much larger in one dimension than the other. The method estimates 2-D frequencies based on several one-dimensional (l-D) frequency estimation processes and hence has a low computational complexity. To avoid resolving close frequencies in 1-D processing, we construct matrices to estimate the linear combinations of the 2-D frequencies. Performance evaluation of this method is presented based on the comparison of the Cramer-Rao bound (CRB) and numerical simulations. Index Terms--Frequency estimation, multidimensional systems, signal detection, spectral analysis.

An algorithm to detect and estimate a linear mixture of deterministic signals corrupted by white Gaussian noise is presented. The number of signals is assumed to be unknown, and the noise power can be either known or unknown. The algorithm is based on an information-theoretic criterion in which the probability of false alarm can be adjusted; typical information criteria, such as the Akaike (AIC) and the minimum description length (MDL) criteria, can be regarded as particular cases of it for given probabilities of false alarm. The proposed approach includes the use of the atomic decomposition and the expectation maximization (EM) algorithms to efficiently approximate the signal maximum likelihood estimate. For the first time, upper-bounds for the probabilities of underestimation and overestimation of the number of signals are obtained. In addition, the constant false-alarm rate (CFAR) characteristic is shown, and the statistical efficiency of the signal parameter estimation is discussed and illustrated by simulation. Numerical experiments show the suitability of the algorithm for signal interception by using synthetic and real-life radar signals.

There are known phase-coded (two-valued or polyphase) CW radar signals that exhibit perfect periodic autocorrelation function (PACF). A PACF is perfect when all its out-of-phase autocorrelation values are identically equal to zero. This paper investigates periodic, two-valued, frequency-coded signals. While none could be found with perfect PACE we present examples with nearly perfect PACF. Their relationship to binary phase-coded signals is also considered. These signals should be attractive for CW radars because of their simple implementation, clean spectrum, and the favorable range response of their matched receiver.

In this contribution, we study a reduced-complexity multiuser detection aided multicarrier direct-sequence code-division multipleaccess (MC DS-CDMA) scheme, which employs both time (T)-domain and frequency (F)-domain spreading. We investigate the achievable detection performance in the context of synchronous TF-domain spread MC DS-CDMA when communicating over an additive white Gaussian noise (AWGN) channel. Five detection schemes are investigated, which include the single-user correlation based detector, the joint TF-domain decorrelating multiuser detector (MUD), the joint TF-domain MMSE MUD, the separate TF-domain decorrelating/MMSE MUD, and the separate TF-domain MMSE/decorrelating MUD. Our simulation results show that the separate TF-domain MUD schemes are capable of achieving a similar bit error rate (BER) performance to that of the significantly more complex joint TF-domain MUD schemes. Index Terms--Code-division multiple-access (CDMA), decorrelating, frequency-domain spreading, joint detection, minimum mean square error (MMSE), multicarrier (MC), multiuser detection, separate detection, time-domain spreading.

The Bell Labs layered space-time (BLAST) architecture is a simple and efficient multiantenna coding structure that can achieve high spectral efficiency. Many BLAST detectors require more receiver antennas than transmitter antennas. We propose two novel turbo-processing BLAST detectors that can operate in systems with fewer receiver antennas than transmitter antennas. Both detectors are based on the group-detection strategy. The first proposed detector, the reduced-dimension maximum a posteriori (RDMAP) detector uses a dynamically formed group for each bit decision, while the second proposed detector, the group maximum a posteriori (GMAP) uses a static grouping. For both detectors, a maximum a posteriori (MAP) decision is made using a group of transmitted symbols, and the remaining signal contribution is treated as interference. The interference is characterized as nonzero mean colored-noise source that is whitened before a decision is made. Both proposed detectors are generalizations of the MAP detector and the turbo-processing minimum mean-squared error (MMSE) detector in Sellathurai and Haykin, and Abe and Matsumoto. An uncoded bit-error rate analysis for an independent Rayleigh fading environment is also presented. Simulated results are presented which show that both the RDMAP and GMAP detectors have a performance improvement over the MMSE detector, especially in systems having an excess number of transmitter antennas. Index Terms--Iterative methods, multidimensional signal detection, multiple-input multiple-output (MIMO) systems, nonlinear detection.

We consider the problem of designing optimal probing signals for finite-hypothesis testing. Equivalently, we cast the problem as the design of optimal channel input sequences for identifying a discrete channel under observation from a finite set of known channels. The optimality criterion that we employ is the exponent of the Bayesian probability of error. In our study, we consider a feedforward scenario where there is no feedback from the channel output to the signal selector at the channel input and a feedback scenario where the past channel outputs are revealed to the signal selector. In the feedforward scenario, only the type of the input sequence matters and our main result is an expression for the error exponent in terms of the limiting distribution of the input sequence. In the feedback case, we show that when discriminating between two channels, the optimal scheme in the first scenario is simultaneously the optimal time-invariant Markov feedback policy of any order. Index Terms--Bayesian hypothesis testing, classification, detection theory, Chernoff's theorem, error exponent, feedback, method of types, sequential detection, signal selection, waveform selection.

We demonstrate the effect of the spectral shape of broadband light sources in a task-based approach for assessment of signal detection and resolution in optical coherence tomography. We define two binary tasks: The signal is either present or absent and the signal can be either resolved or not. In a transparent sample bounded by two uniform interfaces we study the minimum detectable change in the index of refraction as well as the minimum resolvable distance between the layers in correlation with the source spectral shape and power. Results show that the area under the receiver operating curve (AUC) for a signal-detection task is not affected by the shape of the spectrum but solely by its optical power, whereas spectral shaping has an effect, which we quantify, on the AUC for the resolution task. Moreover, the AUC is demonstrated in relation to the concept of system sensitivity for a signal-detection task. OCIS codes: 000.5490, 030.6600, 170.4500.

A channel subspace post-filtering algorithm is described, which treats the least-squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error. The improvement of the performance is demonstrated using both stimulation and experimental data.

The problems of detecting and estimating multiple radar targets, present in the same range-azimuth resolution cell of a surveillance radar system with a mechanically rotating antenna, are discussed. A test called generalized likelihood ratio test (GLRT) was conducted to trace these problems with asymptotical analysis and Monte Carlo simulation.

The analytical performance of the subspace-based blind linear minimum mean-square error (MMSE) multiuser detection algorithm in general multipath multi-antenna code-division multiple-access (CDMA) system is investigated. In blind multiuser detection, the linear MMSE detector of a given user is estimated from the received signals, based on the knowledge of only the spreading sequence of that user.

The problem of designing optimum memoryless detectors for known signals in long-range dependent (LRD) noise is considered. Simulations show that the proposed detector outperforms the locally optimal detector for LRD non-Gaussian noise.

The objective of the beamforming with the exploitation of a sensor array is to enhance the signals of the sources from desired directions, and to suppress the noises and the interfering signals from other directions. A higher order cumulant-based beamforming algorithm, namely, the super-exponential blind adaptive beamforming algorithm is presented.

The problem of detecting a random spatially distributed signal source by an array of sensors is explained. A detection performance behaves differently under different scenarios. A comparison between the GLR detectors and conventional beamforce detectors is made by computer simulations.

The quantitative model for interferogram is used for geometry of the interferometer, Poisson noise and the parameterization of the mean of the noise in incident optical signal. The advantages and disadvantages of the spectrum estimation algorithms in different signal-to-noise ratio (SNR) regimes are discussed.

The baseline design for an Advanced Laser Interferometer Gravitational-Wave Observatory (Advanced LIGO) is a dual-recycled Michelson interferometer with cavities in each of the Michelson interferometer arms. We describe one possible length-sensing and control scheme for such a dual-recycled, cavity-enhanced Michelson interferometer. We discuss the principles of this scheme and derive the first-order sensing signals. We also present a successful experimental verification of our length-sensing system using a prototype tabletop interferometer. Our results demonstrate the robustness of the scheme against deviations from the idealized design. We also identify potential weaknesses and discuss possible improvements. These results as well as other benchtop experiments that we present form the basis for a sensing and control scheme for Advanced LIGO. OCIS codes: 120.3180, 120.5050, 120.2230, 350.1270.

The air-gap transmission lines and inductors are developed by new multilayer process. The developed transmission lines are air-gap coaxial line, air-gap strip line, air-gap coplanar waveguides (CPW), and air-gap buried microstrip line (BMSL). The air-gap transmission lines show very low signal loss and very high isolation performances. The transmission line loss of the coaxial line is less than 0.08 dB/mm up to 40 GHz. Those of the CPW, strip line and BMSL are about 0.07, 0.15, and 0.13 dB/mm, respectively. The isolation characteristics of the coaxial line and BMSL are measured. In case of the coaxial line with 2-mm coupling length and 60-[micro]m distance between signal lines, the coupling is less than -52 dB up to 40 GHz. In case of the BMSL with the same conditions, the coupling is less than -43 dB. Therefore, the air-gap transmission line is very suitable structure for high performance and high-density RF application. Additionally, the air-gap inductors are monolithically fabricated using the same process of the transmission line. The fabricated inductors have very high quality factors, the maximum Q factor of 1.46-nH air-gap inductor is about 130. Using the developed multilayer process, we can realize various types of air-gap transmission lines (coaxial line, CPW, strip line and BMSL) and air-gap inductors simultaneously. Index Terms--Air-gap transmission line, multilayer RF passive device, RF micromachining device.

Traditional equalizers are very sensitive to carrier frequency offsets between the transmitter and receiver. Coherent receivers with frequency estimation algorithms can remove the offset to prevent the equalizer breakdown, but with a penalty in receiver complexity. On the other hand, noncoherent receivers such as differential detectors are inherently robust to the frequency offsets but cannot employ standard equalization techniques due to their nonlinear front-end. In this paper, we introduce a simple noncoherent equalizer receiver structure for fading channel environments with short memory (up to two-bit intervals). The receiver consists of a whitened matched filter followed by a differential detector and a maximum likelihood sequence estimation (MLSE) equalizer. We examine the performance of this noncoherent equalizer by both analysis and simulation. It is shown that despite the simplicity, this receiver structure is capable of significant performance improvement as compared to an ordinary differential detector while operating with receiver frequency offsets two orders of magnitude greater than a traditional MLSE equalizer. This structure offers an attractive solution for high-bit-rate cordless transmission systems such as Digital Enhanced Cordless Telecommunications (DECT) that use simple noncoherent receivers whose performance can be constrained by channel dispersion. Using DECT as a case study, we show that the equalizer's performance limits are caused by the receiver nonlinearity and can be improved by adaptation of this nonlinearity to channel conditions. Index Terms--Cordless telephony, differential-detection, Digital Enhanced Cordless Telecommunications (DECT), maximum likelihood sequence estimation (MLSE) equalization, noncoherent receivers.

Analytical expressions for per-unit-length parameters of finite-length transmission lines are derived and verified by the method of moment in this paper. The line can be a conductor with bends and varying sizes. The expressions are explicit in form and can be used to model and analyze the effects from ends and bends on the line effectively. Index Terms--Distributed parameters, method of moment, nonuniform transmission line, signal integrity.