Cramer-Rao bounds in the estimation of time of arrival in fading channels

This paper computes the Cramer-Rao bounds for the time of arrival estimation in a multipath Rice and Rayleigh fading scenario, conditioned to the previous estimation of a set of propagation channels, since these channel estimates (correlation between received signal and the pilot sequence) are sufficient statistics in the estimation of delays. Furthermore, channel estimation is a constitutive block in receivers, so we can take advantage of this information to improve timing estimation by using time and space diversity. The received signal is modeled as coming from a scattering environment that disperses the signal both in space and time. Spatial scattering is modeled with a Gaussian distribution and temporal dispersion as an exponential random variable. The impact of the sampling rate, the roll-off factor, the spatial and temporal correlation among channel estimates, the number of channel estimates, and the use of multiple sensors in the antenna at the receiver is studied and related to the mobile subscriber positioning issue. To our knowledge, this model is the only one of its kind as a result of the relationship between the space-time diversity and the accuracy of the timing estimation.Peer ReviewedPostprint (published version

Adaptive AOA-Aided TOA Self-Positioning for Mobile Wireless Sensor Networks

Location-awareness is crucial and becoming increasingly important to many applications in wireless sensor networks. This paper presents a network-based positioning system and outlines recent work in which we have developed an efficient principled approach to localize a mobile sensor using time of arrival (TOA) and angle of arrival (AOA) information employing multiple seeds in the line-of-sight scenario. By receiving the periodic broadcasts from the seeds, the mobile target sensors can obtain adequate observations and localize themselves automatically. The proposed positioning scheme performs location estimation in three phases: (I) AOA-aided TOA measurement, (II) Geometrical positioning with particle filter, and (III) Adaptive fuzzy control. Based on the distance measurements and the initial position estimate, adaptive fuzzy control scheme is applied to solve the localization adjustment problem. The simulations show that the proposed approach provides adaptive flexibility and robust improvement in position estimation

Super-resolved localisation in multipath environments

In the last few decades, the localisation problems have been studied extensively. There are still some open issues that remain unresolved. One of the key issues is the efficiency and preciseness of the localisation in presence of non-line-of-sight (NLoS) path. Nevertheless, the NLoS path has a high occurrence in multipath environments, but NLoS bias is viewed as a main factor to severely degrade the localisation performance. The NLoS bias would often result in extra propagation delay and angular bias. Numerous localisation methods have been proposed to deal with NLoS bias in various propagation environments, but they are tailored to some specif ic scenarios due to different prior knowledge requirements, accuracies, computational complexities, and assumptions. To super-resolve the location of mobile device (MD) without prior knowledge, we address the localisation problem by super-resolution technique due to its favourable features, such as working on continuous parameter space, reducing computational cost and good extensibility. Besides the NLoS bias, we consider an extra array directional error which implies the deviation in the orientation of the array placement. The proposed method is able to estimate the locations of MDs and self-calibrate the array directional errors simultaneously. To achieve joint localisation, we directly map MD locations and array directional error to received signals. Then the group sparsity based optimisation is proposed to exploit the geometric consistency that received paths are originating from common MDs. Note that the super-resolution framework cannot be directly applied to our localisation problems. Because the proposed objective function cannot be efficiently solved by semi-definite programming. Typical strategies focus on reducing adverse effect due to the NLoS bias by separating line-of-sight (LoS)/NLoS path or mitigating NLoS effect. The LoS path is well studied for localisation and multiple methods have been proposed in the literature. However, the number of LoS paths are typically limited and the effect of NLoS bias may not always be reduced completely. As a long-standing issue, the suitable solution of using NLoS path is still an open topic for research. Instead of dealing with NLoS bias, we present a novel localisation method that exploits both LoS and NLoS paths in the same manner. The unique feature is avoiding hard decisions on separating LoS and NLoS paths and hence relevant possible error. A grid-free sparse inverse problem is formulated for localisation which avoids error propagation between multiple stages, handles multipath in a unified way, and guarantees a global convergence. Extensive localisation experiments on different propagation environments and localisation systems are presented to illustrate the high performance of the proposed algorithm compared with theoretical analysis. In one of the case studies, single antenna access points (APs) can locate a single antenna MD even when all paths between them are NLoS, which according to the authors’ knowledge is the first time in the literature.Open Acces

Smart Passive Localization Using Time Difference of Arrival

A smart passive localization system using time difference of arrival (TDoA) measurements is designed and analyzed with the goal of providing the position information for the construction of frequency allocation maps

Energy efficient coordinate establishment in wireless sensor networks

Wireless Sensor Networks (WSNs) refer to a group of spatially deployed devices which are used to monitor or detect phenomena, and have the ability to relay sensed data and signalling wirelessly. Positioning information in WSNs is absolutely crucial to perform tasks such as intelligent routing, data aggregation and data collection optimally. A need exists for localisation algorithms which are scalable, distributed, energy efficient and easy to deploy. This research proposes a beaconless Cluster-based Radial Coordinate Establishment (CRCE) positioning algorithm to locate sensor nodes relative to a local coordinate system. The system does not make use of Global Positioning System (GPS) or any other method to provide apriori position information for a set of nodes prior to the CRCE process. The objective of CRCE is to reduce energy consumption while providing a scalable coordinate establishment method for use in WSNs. To reduce energy consumption during the node positioning process, the research focuses on minimising the number of message exchanges in the network by implementing a cluster-based network topology and utilising the potential of geographically distributed processors. A radial coordinate convergence process is proposed to achieve scalability as the number of sensors in the network increases. Three other localisation algorithms are investigated and compared to CRCE to identify the one best suited for coordinate establishment in WSNs. Two of these comparison algorithms are published in the literature and the other is a modified version of one of the published algorithms. The results show a significant decrease in the number of messages that are necessary to establish a network-wide coordinate system successfully, ultimately making it more scalable and energy efficient. In addition, position based algorithms, such as location based routing, can be deployed on top of CRCE.Dissertation (MEng (Computer Engineering))--University of Pretoria, 2006.Electrical, Electronic and Computer Engineeringunrestricte

NLOS mitigation techniques in GNSS receivers based on Level Crossing Rates (LCR) of correlation outputs

Global Navigation Satellite Systems (GNSS) provide navigation services with a highly precise estimation of the position. First military influenced, the use of satellite-based positioning has gained a lot of interest also in civilian tasks nowadays. Because the GNSS performance has been improved over the years, the state-of-the-art GNSS navigation does include indoor positioning and moving autonomously with help of GNSS. The accuracy, which essentially has to be high, can be disturbed by multipath (e.g. diffraction, reflection, refraction or scattering). A possibility to detect multipath, and possibly to avoid those signals in the position solution, is totally necessary. A non-direct signal, namely Non-Light-of-Sight (NLOS), can lead to low accuracy of the positioning. Therefore, this thesis is dealing with the NLOS detection by using the Level Crossing Rate (LCR), which has been used in electronic communication such as Wifi. The thesis is divided in two parts, including a literature review part, following by a simulation of the developed detection technique. All basic knowledge about this work can be extracted from the literature part. In the simulation section, several tests will be provided, done by Matlab simulations. To perform a realistic GNSS signal, a dynamic Galileo Composite Binary Offset Carrier (CBOC) signal was produced

Towards the Next Generation of Location-Aware Communications

This thesis is motivated by the expected implementation of the next generation mobile networks (5G) from 2020, which is being designed with a radical paradigm shift towards millimeter-wave technology (mmWave). Operating in 30--300 GHz frequency band (1--10 mm wavelengths), massive antenna arrays that provide a high angular resolution, while being packed on a small area will be used. Moreover, since the abundant mmWave spectrum is barely occupied, large bandwidth allocation is possible and will enable low-error time estimation. With this high spatiotemporal resolution, mmWave technology readily lends itself to extremely accurate localization that can be harnessed in the network design and optimization, as well as utilized in many modern applications. Localization in 5G is still in early stages, and very little is known about its performance and feasibility. In this thesis, we contribute to the understanding of 5G mmWave localization by focusing on challenges pertaining to this emerging technology. Towards that, we start by considering a conventional cellular system and propose a positioning method under outdoor LOS/NLOS conditions that, although approaches the Cram\'er-Rao lower bound (CRLB), provides accuracy in the order of meters. This shows that conventional systems have limited range of location-aware applications. Next, we focus on mmWave localization in three stages. Firstly, we tackle the initial access (IA) problem, whereby user equipment (UE) attempts to establish a link with a base station (BS). The challenge in this problem stems from the high directivity of mmWave. We investigate two beamforming schemes: directional and random. Subsequently, we address 3D localization beyond IA phase. Devices nowadays have higher computational capabilities and may perform localization in the downlink. However, beamforming on the UE side is sensitive to the device orientation. Thus, we study localization in both the uplink and downlink under multipath propagation and derive the position (PEB) and orientation error bounds (OEB). We also investigate the impact of the number of antennas and the number of beams on these bounds. Finally, the above components assume that the system is synchronized. However, synchronization in communication systems is not usually tight enough for localization. Therefore, we study two-way localization as a means to alleviate the synchronization requirement and investigate two protocols: distributed (DLP) and centralized (CLP). Our results show that random-phase beamforming is more appropriate IA approach in the studied scenarios. We also observe that the uplink and downlink are not equivalent, in that the error bounds scale differently with the number of antennas, and that uplink localization is sensitive to the UE orientation, while downlink is not. Furthermore, we find that NLOS paths generally boost localization. The investigation of the two-way protocols shows that CLP outperforms DLP by a significant margin. We also observe that mmWave localization is mainly limited by angular rather than temporal estimation. In conclusion, we show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error, which asserts that mmWave will play a central role in communication network optimization and unlock opportunities that were not available in the previous generation