5G Positioning and Mapping with Diffuse Multipath

5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters(delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods breakdown or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach

Two-dimensional angular parameter estimation for noncircular incoherently distributed sources based on an L-shaped array

In this paper, a two-stage reduced-rank estimator is proposed for two-dimensional (2D) direction estimation of incoherently distributed (ID) noncircular sources, including their center directions of arrival (DOAs) and angular spreads, based on an L-shaped array. Firstly, based on the first-order Taylor series approximation, a noncircularity-based extended generalized array manifold (GAM) model is established. Then, the 2D center DOAs of incident ID signals are obtained separately with the noncircularity-based generalized shift-invariance property of the array manifold and the reduced-rank principle. The pairing of the two center DOAs is completed by searching for the minimum value of a cost function. Secondly, the 2D angular spreads can be obtained in closed-form solution from the central moments of the angular distribution. The proposed estimator achieves higher accuracy in angle estimation that manages more sources and shows promising results in the general scenario, where different sources possess different angular distributions. Furthermore, the approximate noncircular stochastic Cramer-Rao bound (CRB) of the concerned problem is derived as a benchmark. Numerical analysis proves that the proposed algorithm achieves better estimation performance in both 2D center DOAs and 2D angular spreads than an existing estimator

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Multiple-Input Multiple-Output Communications Systems Using Reconfigurable Antennas

RÉSUMÉ Depuis les années 1990, l'utilisation des systèmes de communications sans-fil à entrées multiples-sorties multiples (MIMO) a été introduit pour fournir des transmissions fiables à grande vitesse. Cette thèse porte sur l'application et l’étude des systèmes MIMO avec des antennes reconfigurables, qui sont ajustable électroniquement pour produire différents diagrammes de rayonnement d'un seul élément d'antenne et ainsi offrir une diversité de diagrammes de rayonnement. En particulier, nous étudions le comportement de la capacité de canal des systèmes MIMO à sélection de diagrammes de rayonnement (PS-MIMO), et nous proposons aussi des algorithmes de sélection du diagramme de rayonnement atteignant la capacité maximale. Tout d'abord, nous étudions l'application des antennes reconfigurables dans l'estimation des statistiques spatiales à long terme de canaux spatiaux avec grappes de multi-trajets (cluster). Nous proposons un estimateur de spectre de type Capon et une technique d'adaptation de la covariance (COMET) pour estimer conjointement l'angle moyen et l’étalement angulaire de la grappe spatiale avec des antennes reconfigurables. En second lieu, sur la base des statistiques à long terme du canal MIMO, nous proposons des algorithmes de sélection de diagramme de rayonnement MIMO (SPS-MIMO) pour atteindre la capacité maximale de canal ergodique. L'analyse de la maximisation de la capacité ergodique du système SPS-MIMO indique que le modèle statistique de sélection fournit des gains supplémentaires en améliorant la puissance du signal reçu et en décorrélant les signaux reçus avec différents diagrammes de rayonnement directionnels. Troisièmement, nous nous concentrons sur le modèle de sélection instantanée des diagrammes de rayonnement MIMO (IPS-MIMO) basé sur des informations instantanées d'état de canal (CSI) afin de maximiser la capacité instantanée pour chaque réalisation de canal. Nous démontrons que l’ordre de diversité des systèmes MIMO peut être multipliée par le nombre de diagrammes de rayonnement avec sélection de diagramme instantanée. Afin d'évaluer la capacité moyenne de l'IPS-MIMO, nous proposons un nouvel algorithme qui permet d’approximer étroitement la moyenne de la valeur maximale de la capacité du canal MIMO avec des trajets arbitrairement corrélés. Nous proposons également un algorithme pour sélectionner instantanément les diagrammes de rayonnement pour atteindre la capacité moyenne. En outre, sur la base d'une simple expression en forme fermée de la capacité coefficient de corrélation, nous sommes en mesure de proposer un algorithme de sélection de sous-ensemble de diagrammes qui offre un compromis entre performances et la complexité de l’algorithme de sélection. En conclusion, des gains de performance importants peuvent être obtenus grâce à la combinaison de l'utilisation d’antennes reconfigurables et de systèmes MIMO avec soit des algorithmes de sélection de diagramme de rayonnement statistique ou instantanée. La capacité des systèmes PS-MIMO à améliorer les performances du système, y compris la capacité et de l'ordre de la diversité, est démontrée par l'analyse théorique et des simulations numériques.----------ABSTRACT Since the 1990s, the use of multiple-input multiple-output (MIMO) systems has been introduced to modern wireless communications to provide reliable transmission at high data rates. This thesis focuses on the application of MIMO systems with reconfigurable antennas, which are electronically tunable to produce a number of radiation patterns at a single antenna element and provide pattern diversity. In particular, we investigate the capacity performance of the pattern selection MIMO (PS-MIMO) systems, and we also present maximum capacity achieving algorithms for radiation pattern selection. First, we investigate the application of reconfigurable antennas in estimating long term spatial statistics of spatial clustered channels. We propose a Capon-like spectrum estimator and a covariance matching technique (COMET) to jointly estimate the mean angle and the angular spread of the spatial cluster with reconfigurable antennas. Second, based on the long term statistics of the MIMO channel, we propose statistical pattern selection MIMO (SPS-MIMO) algorithms to achieve maximum ergodic channel capacity. Analysis of the ergodic capacity maximization of the SPS-MIMO indicates that the statistical pattern selection provides additional gains by enhancing received signal power and decorrelating received signals with different directional radiation patterns. Third, we focus on the instantaneous pattern selection MIMO (IPS-MIMO) based on instantaneous channel state information (CSI) in order to maximize the instantaneous capacity for every channel realization. We prove that the diversity order of MIMO systems can be multiplied by the number of radiation patterns with instantaneous pattern selection. In order to evaluate the mean capacity of the IPS-MIMO, we propose a novel algorithm which closely approximates the mean of the maximum of the channel capacity of arbitrarily correlated MIMO channels. We also propose an algorithm for instantaneously selecting radiation patterns to achieve the mean capacity. In addition, based on a simple closed-form approximation to the capacity correlation coefficient, we are able to propose a subset pattern selection algorithm which enables the trade-off between performances and complexity. In conclusion, important extra gains can be obtained as a result of combining the use of reconfigurable antennas and MIMO systems with either statistical or instantaneous radiation pattern selection. The capability of the PS-MIMO to improve system performances, including capacity and diversity order, is demonstrated through theoretical analysis and numerical simulations

Target localization in MIMO radar systems

MIMO (Multiple-Input Multiple-Output) radar systems employ multiple antennas to transmit multiple waveforms and engage in joint processing of the received echoes from the target. MIMO radar has been receiving increasing attention in recent years from researchers, practitioners, and funding agencies. Elements of MIMO radar have the ability to transmit diverse waveforms ranging from independent to fully correlated. MIMO radar offers a new paradigm for signal processing research. In this dissertation, target localization accuracy performance, attainable by the use of MIMO radar systems, configured with multiple transmit and receive sensors, widely distributed over an area, are studied. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and noncoherent processing. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the noncoherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. It is shown that optimization over the sensors\u27 positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE\u27s utility is in providing a closed-form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area. Coherent processing advantage for target localization relies on time and phase synchronization between transmitting and receiving radars. An analysis of the sensitivity of the localization performance with respect to the variance of phase synchronization error is provided by deriving the hybrid CRLB. The single target case is extended to the evaluation of multiple target localization performance. Thus far, the analysis assumes a stationary target. Study of moving target tracking capabilities is offered through the use of the Bayesian CRLB for the estimation of both target location and velocity. Centralized and decentralized tracking algorithms, inherit to distributed MIMO radar architecture, are proposed and evaluated. It is shown that communication requirements and processing load may be reduced at a relatively low performance cost

A novel array signal processing technique for multipath channel parameter estimation

Cataloged from PDF version of article.Many important application areas such as mobile communication, radar, sonar and remote sensing make use of array signal processing techniques. In this thesis, a new array processing technique called Cross Ambiguity Function - Direction Finding (CAF-DF) is developed. CAF-DF technique estimates direction of arrival (DOA), time delay and Doppler shift corresponding to each impinging signals onto a sensor array in an iterative manner. Starting point of each iteration is CAF computation at the output of each sensor element. Then, using incoherent integration of the computed CAFs, the strongest signal in the delay-Doppler domain is detected and based on the observed phases of the obtained peak across all the sensors, the DOA of the strongest signal is estimated. Having found the DOA, CAF of the coherently integrated sensor outputs is computed to find accurate delay and Doppler estimates for the strongest signal. Then, for each sensor in the array, a copy of the strongest signal that should be observed at that sensor is constucted and eliminated from the sensor output to start the next iteration. Iterations continue until there is no detectable peak on the incoherently integrated CAFs. The proposed technique is compared with a MUSIC based technique on synthetic signals. Moreover, performance of the algorithm is tested on real high-latitude ionospheric data where the existing approaches have limited resolution capability of the signal paths. Based on a wide range of comparisons, it is found that the proposed CAF-DF technique is a strong candidate to define the new standard on challenging array processing applications.Güldoğan, Mehmet BurakM.S