Search

The interplay among the rank of optimized space-time code, the number of transmit diversity paths generated in the signal space and the amount of energy integrated along each path were explored to gain insight into a multiple-input multiple-output (MIMO) detection problem. The results confirmed the existence of an inherent tradeoff between diversity and integration and absence of uniformly optimum waveform design strategy.

The general problem of joint sequential target detection and estimation is considered for multiframe surveillance radar systems. Numerical experiments are performed in order to understand the interplay between sensor-target parameters and system performances and also to quantify the gain with respect to other fixed-sample procedures.

This paper addresses the problem of early detection of K [greater than or equal to] 1 multiple moving targets in radar systems through the use of track-before-detect (TBD) techniques. At first, assuming prior knowledge of K, a binary generalized likelihood ratio test (GLRT) is derived, which shows that the multi-target TBD problem can be regarded as a K-path trellis search. Since optimal implementation of the GLRT has a nonlinear complexity either in the number of targets or in the number of integrated frames, suboptimum algorithms are investigated which allow to trade better estimation and tracking accuracy for a much lower implementation complexity. Next, the TBD problem with K unknown is discussed and a novel multi-hypothesis test strategy is derived as the solution to a constrained optimization problem, which subsumes the conventional binary GLRT as the special case of known K. Finally, numerical examples are provided to assess and compare the performances of the proposed TBD procedures.

This paper considers the problem of multiple-input multiple-output (MIMO) radars employing space-time coding (STC) to achieve diversity. To this end, after briefly outlining the model of the received echo, a suitable detection structure is derived, and its performance is expressed in closed form as a function of the clutter statistical properties and of the space-time code matrix. Interestingly, this receiver requires prior knowledge of the clutter covariance, but the detection threshold is functionally independent thereof. At the transmitter design stage, we give two criteria for code construction: the first is based on the classical Chernoff bound, the second is an information-theoretic criterion. Interestingly, the two criteria lead to the same condition for code optimality, which in turn specializes, under the assumption of uncorrelated clutter and square code matrix, in some well-known full-rate space-time codes. A thorough performance assessment is also given, so as to establish the optimum achievable performance for MIMO radar systems.

The performance of user cooperation in the uplink of a synchronous direct-sequence (DS) code-division multiple-access (CDMA) cellular network is analyzed by using nonorthogonal spreading codes. A performance assessment is undertaken to analyze the impact of the multiple-access interference on the proposed cooperative strategies under different scenarios and system assumptions.

A new class of receivers based on widely linear data processing is proposed for data detection in communication systems affected by improper complex noise. It is shown that the improved receivers outperform the conventional ones both in terms of the error probability and of the capacity to cope with the power disparities that the fading channel induces on the data streams transmitted by different antennas.

In this paper we present a family of track-before-detect (TBD) procedures for early detection of moving targets from airborne radars. Upon a sectorization of the coverage area, the received echoes are jointly processed in the azimuth-range-Doppler domain and in the time domain through a Viterbi-like algorithm that exploits the physically admissible target transitions between successive illuminations, in order to collect all of the energy back-scattered during the time on target (TOT). A reduced-complexity implementation is derived assuming, at the design stage, that the target does not change resolution cell during the TOT in each scan. The constant false alarm rate (CFAR) constraint is also englobed in the proposed procedures as well as the possibility of working with quantized data. Simulation results show that the proposed algorithms have good detection and tracking capabilities even for high target velocities and low quantization rates.

Formulas for the modified Cramer-Rao bounds (CRBs) are obtained under the assumption that the spreading codes can be modeled as random nuisance parameters. Numerical examples showing the impact of the training length, signal-to-noise ratio (SNR) and the number of active users on the CRB are also reported and commented upon.

The problem of blind multiuser detection in a direct sequence code division multiple access (DS/CDMA) multiantenna systems is discussed. The design strategy and performance evaluation technique to space-time coded system are proposed.

In iterative data-detection and channel-estimation algorithms, the channel estimator and the data detector recursively exchange information in order to improve the system performance. While a vast bulk of the available literature demonstrates the merits of iterative schemes through computer simulations, in this paper analytical results on the performance of an iterative detection/estimation scheme are presented. In particular, this paper focus is on uncoded systems and both the situations that the receiver and the transmitter are equlpped with either a single antenna or multiple antennas are considered. With regard to the channel estimator, the analysis considers both the minimum mean square error and the maximum likelihood channel estimate, while, with regard to the data detector, linear receiver interfaces are considered. Closed-form formulas are given for the channel-estimation mean-square error and for its Cramer-Rao bound, as well as for the error probability of the data detector. Moreover, the problem of the optimal choice of the length of the training sequence is also addressed. Overall, results show that the considered iterative strategy achieves excellent performance and permits, at the price of some complexity increase, the use of very short training sequences without incurring any performance loss. Finally, computer simulations reveal that the experimental results are in perfect agreement with those predicted by the theoretical analysis. Index Terms--Channel estimation, Cramer-Rao bound (CRB), data detection, multiantenna systems, wireless communication.

In this paper, the problem of subspace-based blind adaptive multi-user detection in multi-rate direct-sequence code-division multiple-access (DS.CDMA) systems adopting short (periodic) spreading codes is considered. The solution that we propose is based on the well-known formulation of the linear minimum mean-squared error and decorrelating detectors in terms of signal subspace parameters. Since in a multi-rate scenario the correlation properties of the observable (and, hence, the signal subspace parameters) are periodically time-varying, classical subspace tracking algorithms, which assume that the subspace to be tracked is time-invariant or slowly time-varying, are shown to be not useful in this situation. A new recursive cyclic subspace tracking algorithm is thus developed. This procedure, which is based on a generalization of the PASTd algorithm, is able to capture the periodical variations of the signal subspace, and thus enables subspace-based blind adaptive multi-user detection in multi-rate CDMA systems. The proposed algorithm has a smaller computational complexity than the recently developed cyclic recursive-least-squares procedure, and, as numerical results confirm, is capable of providing very satisfactory performance. Index Terms--Blind adaptive multi-user detection, cyclic algorithms, direct-sequence code-division multiple-access (DS-CDMA) systems, multi-rate CDMA, subspace tracking.

The problem of blind adaptive joint multiuser detection and equalization in direct-sequence code division multiple access (DS/CDMA) systems operating on fading dispersive channels is examined and discussed.

Radar detection of coherent pulse trains embedded in compound-Gaussian disturbance with partially known statistics is discussed. We first give a thorough derivation of two recently proposed adaptive detection structures. Next, we derive a different detection scheme exploiting the assumption that the clutter is wide-sense stationary. Resorting to the theory of circulant matrices, in fact, we demonstrate that the estimation of the structure of the clutter covariance matrix can be reduced to the estimation of its eigenvalues, which in turn can be (efficiently) done via fast Fourier transform codes. After a thorough performance assessment, mostly carried on via computer simulations, the results show that the newly proposed detector achieves better performance than the two previously introduced adaptive detectors. Moreover, a sensitivity analysis shows that, even though this detector does not strictly guarantee the constant false alarm rate property with respect to the clutter covariance matrix, it is robust, in the sense that its performance is only slightly affected by variations in the clutter temporal correlation.

The problem of constant false-alarm rate (CFAR) detection of possibly range-spread targets in clutter-dominated environment, whether Weibull or lognormal is presented. The proposed scheme is a member of the clutter-map CFAR family, which relies on a combination of space and time processing as well as on the relevant properties of the location-scale distributions; it ensures CFAR against noise with biparametric variations without incurring masking effects from slow, extended targets or multiple interferers. We also give guidelines for designing the system parameters, along with approximate formulas for setting the appropriate threshold multipliers to achieve a given false-alarm rate (FAR) under Weibull and lognormal clutter.

The performance assessment of the clutter map constant false-alarm rate (CFAR) procedure presented in Part I [1] is introduced. At first, the performance in the presence of point targets is investigated, subject to both Weibull and lognormal clutter, so as to elicit the influence of the system parameters. The study essentially relies on Monte-Carlo simulations, but approximations for the detection rate are also developed. Admittedly, a global figure of performance, the Average Threshold Deviation (ATD), is introduced and its worth as a design tool is validated. Next, the effect of extended as well as multiple targets is considered, showing that the system can be designed so as to avoid self-masking from either range-spread targets persisting on the same map cell, or spurious targets in close spatial proximity to the cell under test. Finally, the system robustness is demonstrated through a sensitivity study, aimed at investigating the effect of a possible mismatch between the design and the actual clutter distribution, that of the clutter correlation and of a thermal noise component in the overall disturbance.

In a decentralized detection scheme, several sensors perform a binary (hard) decision and send the resulting data to a fusion center for the final decision. If each local decision has a constant false alarm rate (CFAR), the final decision is ensured to be CFAR. We consider the case that each local decision is a threshold decision, and the threshold is proportional, through a suitable multiplier, to a linear combination of order statistics (OS) from a reference set (a generalization of the concept of OS thresholding). We address the following problem: given the fusion rule and the relevant system parameters, select each threshold multiplier and the coefficients of each linear combination so as to maximize the overall probability of detection for constrained probability of false alarm. By a Lagrangian maximization approach, we obtain a general solution to this problem and closed-form solutions for the AND and OR fusion logics. A performance assessment is carried on, showing a global superiority of the OR fusion rule in terms of detection probability (for operating conditions matching the design assumptions) and of robustness (when these do not match). We also investigate the effect of the hard quantization performed at the local sensors, by comparing the said performance to those achievable by the same fusion rule in the limiting case of no quantization.

A new family of constant false alarm rate (CFAR) processors is introduced. An Ll-CFAR forms its noise power estimate by linearly filtering ranked samples from the reference set; the weights of this combination, however, depend not only on the rank, but also on the relative proximity of the sample to the cell under test. From the class of Ll-CFARs may be chosen members which effectively censor spurious targets; members which exhibit impressive control of false alarm in the presence of a clutter edge; and members which are robust against both such inhomogeneities. While the design of such schemes is involved, their implementation is not significantly more burdensome than that of plain ordered statistic CFAR (OS- CFAR). After a discussion of the stochastic training of Ll-CFAR, the performance is thoroughly assessed under the most commonly encountered instances of environmental conditions, and compared with those of classical CFAR techniques.

We consider procedures for constant false alarm rate in Lognormal clutter, accounting for variations of both a scale and a shape parameter of the clutter. Adaptivity to both parameters is obtained through biparametric estimation based on a sliding window surrounding the radar cell under test. We present some new procedures exploiting best linear unbiased estimation (BLUE) and compare them to a previous procedure called Log-t which uses maximum likelihood estimation. The comparison is carried on under homogeneous clutter environment and under instances of inhomogeneous environment (clutter edges and spurious targets). In the latter instances, some advantages of BLUE procedures are highlighted which stem from the opportunity of censoring.

Abstract The number of active users, their timing offsets, and their (possibly dispersive) channels with the access point are performance-critical parameters for wireless code division multiple access (CDMA). Estimating them as accurately as possible using as short as possible training sequences can markedly improve error performance as well as the capacity of CDMA systems. The fresh look advocated here permeates benefits from recent advances in variable selection and compressive sampling approaches to multiuser communications by casting estimation of these parameters as a sparse linear regression problem. Novel estimators are developed by exploiting two forms of sparsity present: the first emerging from user (in)activity, and the second from the uncertainty on user delays and channel taps. Simulated tests demonstrate a large gain in performance when sparsity-aware estimators of CDMA parameters are compared to sparsity-agnostic standard least-squares-based alternatives.

This paper handles the simultaneous suppression of narrow-band and multiaccess interference in asynchronous CDMA networks. We consider both linear one-shot detection and block-detection, showing that, in both cases, the presence of an external narrow-band interferer generally results in the need for time-varying processing. As to the linear one-shot detectors, we derive both a zero-forcing and a minimum mean square error detector, showing that they are members of an only family, wherein the optimization criterion is the constrained minimization of a suitably defined output interference energy. We also present a comparative performance assessment between the various detection strategies, studying the impact of both the optimization criterion and other system parameters, such as the oversampling ratio and the length of the observation window. We also handle the problem of blind and adaptive detection. At first we show that the linear one-shot receivers are readily amenable to a blind implementation, upon off-line estimation of the covariance matrix of the observables. Next, we consider the problem of an adaptive implementation of a periodically time-varying minimum mean square error receiver, introducing and assessing a new cyclic recursive least squares (RLS) algorithm: we show that, unlike the conventional RLS algorithms, the new algorithm is capable of tracking the periodically time-varying variation of the receiver structure, induced by the presence of a data-like narrow-band interferer. Index Terms--Blind receiver, interference suppression, recursive least squares (RLS) algorithm, spread spectrum.

The problem of M signal detection over a single input multiple output channel affected by fading dispersive is examined.

The detection of incoherent pulse trains in compound-Gaussian disturbance with known spectral density is dealt with here. Two alternative approaches are investigated. The first, assuming perfect knowledge of the signal fluctuation law and implementing the Neyman-Pearson test on the observed waveform, turns out to be not applicable to the radar problem. The second, instead, relying on the generalized likelihood ratio optimization strategy, leads to a canonical detector, whose structure is independent of the clutter amplitude probability density function. Interestingly, this detector turns out to be constant false-alarm rate in the sense that threshold setting does not require any knowledge as to the clutter distribution. Moreover, since such a processor is not implementable in real situations, we also present an FFT-based (fast Fourier transform) suboptimum structure. Finally, we give closed-form formulas for the detection performance of both receivers, showing that both of them largely outperform the square-law detector, especially in the presence of very spiky clutter.