Efficient Two-Dimensional Direction-of-Arrival Estimation for a Mixture of Circular and Noncircular Sources

In this paper, the two-dimensional (2-D) direction-of-arrival (DOA) estimation problem for a mixture of circular and noncircular sources is considered. In particular, we focus on a 2-D array structure consisting of two parallel uniform linear arrays and build a general array model with mixed circular and noncircular sources. The received array data and its conjugate counterparts are combined together to form a new data vector, based on which a series of 2-D DOA estimators is derived. Compared with existing methods, the proposed one has three main advantages. First, it can give a more accurate estimation in situations, where the number of sources is within the traditional limit of high-resolution methods. Second, it can still work effectively when the number of mixed signals is larger than that of the array elements. Finally, the paired 2-D DOAs of the proposed method can be obtained automatically without the complicated 2-D spectrum peak search and, therefore, has a much lower computational complexity

Beamforming and Direction of Arrival Estimation Based on Vector Sensor Arrays

Array signal processing is a technique linked closely to radar and sonar systems. In communication, the antenna array in these systems is applied to cancel the interference, suppress the background noise and track the target sources based on signals'parameters. Most of existing work ignores the polarisation status of the impinging signals and is mainly focused on their direction parameters. To have a better performance in array processing, polarized signals can be considered in array signal processing and their property can be exploited by employing various electromagnetic vector sensor arrays. In this thesis, firstly, a full quaternion-valued model for polarized array processing is proposed based on the Capon beamformer. This new beamformer uses crossed-dipole array and considers the desired signal as quaternion-valued. Two scenarios are dealt with, where the beamformer works at a normal environment without data model errors or with model errors under the worst-case constraint. After that, an algorithm to solve the joint DOA and polarisation estimation problem is proposed. The algorithm applies the rank reduction method to use two 2-D searches instead of a 4-D search to estimate the joint parameters. Moreover, an analysis is given to introduce the difference using crossed-dipole sensor array and tripole sensor array, which indicates that linear crossed-dipole sensor array has an ambiguity problem in the estimation work and the linear tripole sensor array avoid this problem effectively. At last, we study the problem of DOA estimation for a mixture of single signal transmission (SST) signals and duel signal transmission (DST) signals. Two solutions are proposed: the first is a two-step method to estimate the parameters of SST and DST signals separately; the second one is a unified one-step method to estimate SST and DST signals together, without treating them separately in the estimation process

Optimizing Techniques and Cramer-Rao Bound for Passive Source Location Estimation

This work is motivated by the problem of locating potential unstable areas in underground potash mines with better accuracy more consistently while introducing minimum extra computational load. It is important for both efficient mine design and safe mining activities, since these unstable areas may experience local, low-intensity earthquakes in the vicinity of an underground mine. The object of this thesis is to present localization algorithms that can deliver the most consistent and accurate estimation results for the application of interest. As the first step towards the goal, three most representative source localization algorithms given in the literature are studied and compared. A one-step energy based grid search (EGS) algorithm is selected to address the needs of the application of interest. The next step is the development of closed-form Cram´er-Rao bound (CRB) expressions. The mathematical derivation presented in this work deals with continuous signals using the Karhunen-Lo`eve (K-L) expansion, which makes the derivation applicable to non-stationary Gaussian noise problems. Explicit closed-form CRB expressions are presented only for stationary Gaussian noise cases using the spectrum representation of the signal and noise though. Using the CRB comparisons, two approaches are proposed to further improve the EGS algorithm. The first approach utilizes the corresponding analytic expression of the error estimation variance (EEV) given in [1] to derive an amplitude weight expression, optimal in terms of minimizing this EEV, for the case of additive Gaussian noise with a common spectrum interpretation across all the sensors. An alternate noniterative amplitude weighting scheme is proposed based on the optimal amplitude weight expression. It achieves the same performance with less calculation compared with the traditional iterative approach. The second approach tries to optimize the EGS algorithm in the frequency domain. An analytic frequency weighted EEV expression is derived using spectrum representation and the stochastic process theory. Based on this EEV expression, an integral equation is established and solved using the calculus of variations technique. The solution corresponds to a filter transfer function that is optimal in the sense that it minimizes this analytic frequency domain EEV. When various parts of the frequency domain EEV expression are ignored during the minimization procedure using Cauchy-Schwarz inequality, several different filter transfer functions result. All of them turn out to be well known classical filters that have been developed in the literature and used to deal with source localization problems. This demonstrates that in terms of minimizing the analytic EEV, they are all suboptimal, not optimal. Monte Carlo simulation is performed and shows that both amplitude and frequency weighting bring obvious improvement over the unweighted EGS estimator

I/Q Imbalance in Multiantenna Systems: Modeling, Analysis and RF-Aware Digital Beamforming

Wireless communications has experienced an unprecedented increase in data rates, numbers of active devices and selection of applications during recent years. However, this is expected to be just a start for future developments where a wireless connection is seen as a fundamental resource for almost any electrical device, no matter where and when it is operating. Since current radio technologies cannot provide such services with reasonable costs or even at all, a multitude of technological developments will be needed. One of the most important subjects, in addition to higher bandwidths and flexible network functionalities, is the exploitation of multiple antennas in base stations (BSs) as well as in user equipment (UEs). That kind of multiantenna communications can boost the capacity of an individual UE-BS link through spatial antenna multiplexing and increase the quality as well as robustness of the link via antenna diversity. Multiantenna technologies provide improvements also on the network level through spatial UE multiplexing and sophisticated interference management. Additionally, multiple antennas can provide savings in terms of the dissipated power since transmission and reception can be steered more efficiently in space, and thus power leakage to other directions is decreased. However, several issues need to be considered in order to get multiantenna technologies widely spread. First, antennas and the associated transceiver chains are required to be simple and implementable with low costs. Second, size of the antennas and transceivers need to be minimized. Finally, power consumption of the system must be kept under control. The importance of these requirements is even emphasized when considering massive multiple-input multiple-output (MIMO) systems consisting of devices equipped with tens or even hundreds of antennas.In this thesis, we consider multiantenna devices where the associated transceiver chains are implemented in such a way that the requirements above can be met. In particular, we focus on the direct-conversion transceiver principle which is seen as a promising radio architecture for multiantenna systems due to its low costs, small size, low power consumption and good flexibility. Whereas these aspects are very promising, direct-conversion transceivers have also some disadvantages and are vulnerable to certain imperfections in the analog radio frequency (RF) electronics in particular. Since the effects of these imperfections usually get even worse when optimizing costs of the devices, the scope of the thesis is on the effects and mitigation of one of the most severe RF imperfection, namely in-phase/quadrature (I/Q) imbalance.Contributions of the thesis can be split into two main themes. First of them is multiantenna narrowband beamforming under transmitter (TX) and receiver (RX) I/Q imbalances. We start by creating a model for the signals at the TX and RX, both under I/Q imbalances. Based on these models we derive analytical expressions for the antenna array radiation patterns and notice that I/Q imbalance distorts not only the signals but also the radiation characteristics of the array. After that, stemming from the nature of the distortion, we utilize widely-linear (WL) processing, where the signals and their complex conjugates are processed jointly, for the beamforming task under I/Q imbalance. Such WL processing with different kind of statistical and adaptive beamforming algorithms is finally shown to provide a flexible operation as well as distortion-free signals and radiation patterns when being under various I/Q imbalance schemes.The second theme extends the work to wideband systems utilizing orthogonal frequency-division multiplexing (OFDM)-based waveforms. The focus is on uplink communications and BS RX processing in a multiuser MIMO (MU-MIMO) scheme where spatial UE multiplexing is applied and further UE multiplexing takes place in frequency domain through the orthogonal frequency-division multiple access (OFDMA) principle. Moreover, we include the effects of external co-channel interference into our analysis in order to model the challenges in heterogeneous networks. We formulate a flexible signal model for a generic uplink scheme where I/Q imbalance occurs on both TX and RX sides. Based on the model, we analyze the signal distortion in frequency domain and develop augmented RX processing methods which process signals at mirror subcarrier pairs jointly. Additionally, the proposed augmented methods are numerically shown to outperform corresponding per-subcarrier method in terms of the instantaneous signal-to-interference-and-noise ratio (SINR). Finally, we address some practical aspects and conclude that the augmented processing principle is a promising tool for RX processing in multiantenna wideband systems under I/Q imbalance.The thesis provides important insight for development of future radio networks. In particular, the results can be used as such for implementing digital signal processing (DSP)-based RF impairment mitigation in real world transceivers. Moreover, the results can be used as a starting point for future research concerning, e.g., joint effects of multiple RF impairments and their mitigation in multiantenna systems. Overall, this thesis and the associated publications can help the communications society to reach the ambitious aim of flexible, low-cost and high performance radio networks in the future