Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

Adaptive Synchronization of Robotic Sensor Networks

The main focus of recent time synchronization research is developing power-efficient synchronization methods that meet pre-defined accuracy requirements. However, an aspect that has been often overlooked is the high dynamics of the network topology due to the mobility of the nodes. Employing existing flooding-based and peer-to-peer synchronization methods, are networked robots still be able to adapt themselves and self-adjust their logical clocks under mobile network dynamics? In this paper, we present the application and the evaluation of the existing synchronization methods on robotic sensor networks. We show through simulations that Adaptive Value Tracking synchronization is robust and efficient under mobility. Hence, deducing the time synchronization problem in robotic sensor networks into a dynamic value searching problem is preferable to existing synchronization methods in the literature.Comment: First International Workshop on Robotic Sensor Networks part of Cyber-Physical Systems Week, Berlin, Germany, 14 April 201

Collaborative Estimation in Distributed Sensor Networks

Networks of smart ultra-portable devices are already indispensable in our lives, augmenting our senses and connecting our lives through real time processing and communication of sensory (e.g., audio, video, location) inputs. Though usually hidden from the user\u27s sight, the engineering of these devices involves fierce tradeoffs between energy availability (battery sizes impact portability) and signal processing / communication capability (which impacts the smartness of the devices). The goal of this dissertation is to provide a fundamental understanding and characterization of these tradeoffs in the context of a sensor network, where the goal is to estimate a common signal by coordinating a multitude of battery-powered sensor nodes. Most of the research so far has been based on two key assumptions -- distributed processing and temporal independence -- that lend analytical tractability to the problem but otherwise are often found lacking in practice. This dissertation introduces novel techniques to relax these assumptions -- leading to vastly efficient energy usage in typical networks (up to 20% savings) and new insights on the quality of inference. For example, the phenomenon of sensor drift is ubiquitous in applications such as air-quality monitoring, oceanography and bridge monitoring, where calibration is often difficult and costly. This dissertation provides an analytical framework linking the state of calibration to the overall uncertainty of the inferred parameters. In distributed estimation, sensor nodes locally process their observed data and send the resulting messages to a sink, which combines the received messages to produce a final estimate of the unknown parameter. In this dissertation, this problem is generalized and called collaborative estimation , where some sensors can potentially have access to the observations from neighboring sensors and use that information to enhance the quality of their messages sent to the sink, while using the same (or lower) energy resources. This is motivated by the fact that inter-sensor communication may be possible if sensors are geographically close. As demonstrated in this dissertation, collaborative estimation is particularly effective in energy-skewed and information-skewed networks, where some nodes may have larger batteries than others and similarly some nodes may be more informative (less noisy) compared to others. Since the node with the largest battery is not necessarily also the most informative, the proposed inter-sensor collaboration provides a natural framework to route the relevant information from low-energy-high-quality nodes to high-energy-low-quality nodes in a manner that enhances the overall power-distortion tradeoff. This dissertation also analyzes how time-correlated measurement noise affects the uncertainties of inferred parameters. Imperfections such as baseline drift in sensors result in a time-correlated additive component in the measurement noise. Though some models of drift have been reported in the literature earlier, none of the studies have considered the effect of drifting sensors on an estimation application. In this dissertation, approximate measures of estimation accuracy (Cramer-Rao bounds) are derived as a function of physical properties of sensors -- namely the drift strength, correlation (Markov) factor and the time-elapsed since last calibration. For stationary drift (Markov factor less than one), it is demonstrated that the first order effect of drift is asymptotically equivalent to scaling the measurement noise by an appropriate factor. When the drift is non-stationary (Markov factor equal to one), it is established that the constant part of a signal can only be estimated inconsistently (with non-zero asymptotic variance). The results help quantify the notions that measurements taken sooner after calibration result in more accurate inference

An Exploratory Analysis Of A Time Synchronization Protocol For UAS

This dissertation provides a numerical analysis of a Receiver Only Synchronization (ROS) protocol which is proposed for use by Unmanned Aircraft Systems (UAS) in Beyond Visual Line of Sight (BVLOS) operations. The use of ROS protocols could reinforce current technologies that enable transmission over 5G cell networks, decreasing latency issues and enabling the incorporation of an increased number of UAS to the network, without loss of accuracy. A minimum squared error (MSE)-based accuracy of clock offset and clock skew estimations was obtained using the number of iterations and number of observations as independent parameters. Although the model converged after only four iterations, the number of observations needed was considerably large, of no less than about 250. The noise, introduced in the system through the first residual, the correlation parameter and the disturbance terms, was assumed to be autocorrelated. Previous studies suggested that correlated noise might be typical in multipath scenarios, or in case of damaged antennas. Four noise distributions: gaussian, exponential, gamma and Weibull were considered. Each of them is adapted to different noise sources in the OSI model. Dispersion of results in the first case, the only case with zero mean, was checked against the Cramér-Rao Bound (CRB) limit. Results confirmed that the scheme proposed was fully efficient. Moreover, results with the other three cases were less promising, thus demonstrating that only zero mean distributions could deliver good results. This fact would limit the proposed scheme application in multipath scenarios, where echoes of previous signals may reach the receiver at delayed times. In the second part, a wake/sleep scheme was imposed on the model, concluding that for wake/sleep ratios below 92/08 results were not accurate at p=.05 level. The study also evaluated the impact of noise levels in the time domain and showed that above -2dB in time a substantial contribution of error terms disturbed the initial estimations significantly. The tests were performed in Matlab®. Based on the results, three venues confirming the assumptions made were proposed for future work. Some final reflections on the use of 5G in aviation brought the present dissertation to a close

Clock Synchronization in Wireless Sensor Networks: An Overview

The development of tiny, low-cost, low-power and multifunctional sensor nodes equipped with sensing, data processing, and communicating components, have been made possible by the recent advances in micro-electro-mechanical systems (MEMS) technology. Wireless sensor networks (WSNs) assume a collection of such tiny sensing devices connected wirelessly and which are used to observe and monitor a variety of phenomena in the real physical world. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization protocols for WSNs

Improving Channel Estimation and Tracking Performance in Distributed MIMO Communication Systems

This dissertation develops and analyzes several techniques for improving channel estimation and tracking performance in distributed multi-input multi-output (D-MIMO) wireless communication systems. D-MIMO communication systems have been studied for the last decade and are known to offer the benefits of antenna arrays, e.g., improved range and data rates, to systems of single-antenna devices. D-MIMO communication systems are considered a promising technology for future wireless standards including advanced cellular communication systems. This dissertation considers problems related to channel estimation and tracking in D-MIMO communication systems and is focused on three related topics: (i) characterizing oscillator stability for nodes in D-MIMO systems, (ii) the development of an optimal unified tracking framework and a performance comparison to previously considered sub-optimal tracking approaches, and (iii) incorporating independent kinematics into dynamic channel models and using accelerometers to improve channel tracking performance. A key challenge of D-MIMO systems is estimating and tracking the time-varying channels present between each pair of nodes in the system. Even if the propagation channel between a pair of nodes is time-invariant, the independent local oscillators in each node cause the carrier phases and frequencies and the effective channels between the nodes to have random time-varying phase offsets. The first part of this dissertation considers the problem of characterizing the stability parameters of the oscillators used as references for the transmitted waveforms. Having good estimates of these parameters is critical to facilitate optimal tracking of the phase and frequency offsets. We develop a new method for estimating these oscillator stability parameters based on Allan deviation measurements and compare this method to several previously developed parameter estimation techniques based on innovation covariance whitening. The Allan deviation method is validated with both simulations and experimental data from low-precision and high-precision oscillators. The second part of this dissertation considers a D-MIMO scenario with $N_t$ transmitters and $N_r$ receivers. While there are $N_t imes N_r$ node-to-node pairwise channels in such a system, there are only $N_t + N_r$ independent oscillators. We develop a new unified tracking model where one Kalman filter jointly tracks all of the pairwise channels and compare the performance of unified tracking to previously developed suboptimal local tracking approaches where the channels are not jointly tracked. Numerical results show that unified tracking tends to provide similar beamforming performance to local tracking but can provide significantly better nullforming performance in some scenarios. The third part of this dissertation considers a scenario where the transmit nodes in a D-MIMO system have independent kinematics. In general, this makes the channel tracking problem more difficult since the independent kinematics make the D-MIMO channels less predictable. We develop dynamics models which incorporate the effects of acceleration on oscillator frequency and displacement on propagation time. The tracking performance of a system with conventional feedback is compared to a system with conventional feedback and local accelerometer measurements. Numerical results show that the tracking performance is significantly improved with local accelerometer measurements

Time-based Location Techniques Using Inexpensive, Unsynchronized Clocks in Wireless Networks

The ability to measure location using time of flight in IEEE 802.11 networks is impeded by the standard clock resolution, imprecise synchronization of the 802.11 protocol, and the inaccuracy of available clocks. To achieve real-time location with accuracy goals of a few meters, we derive new consensus synchronization techniques for free-running clocks. Using consensus synchronization, we improve existing time of arrival (TOA) techniques and introduce new time difference of arrival (TDOA) techniques. With this common basis, we show how TOA is theoretically superior to TDOA. Using TOA measurements, we can locate wireless nodes that participate in the location system, and using TDOA measurements, we can locate nodes that do not participate. We demonstrate applications using off-the-shelf 802.11 hardware that can determine location to within 3m using simple, existing optimization methods. The synchronization techniques extend existing ones providing distributed synchronization for free-running clocks to cases where send times cannot be controlled and adjusted precisely, as in 802.11 networks. These location and synchronization techniques may be applied to transmitting wireless nodes using any communication protocol where cooperating nodes can produce send and receive timestamps