Distributed estimation over a low-cost sensor network: a review of state-of-the-art

Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive review of the state-of-the-art solutions in this research area, exploring their characteristics, advantages, and challenging issues. Additionally, several open problems and future avenues of research are highlighted

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

Audio Fingerprinting for Multi-Device Self-Localization

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/K007491/1

DISTRIBUTED CONSENSUS-BASED CALIBRATION OF NETWORKED CONTROL SYSTEMS

In this paper a new algorithm for distributed blind macro-calibration of Networked Control Systems is presented. It is assumed that the measured signal is stochastic and unknown. The algorithm is in the form of recursions of gradient type for estimation of the correction parameters for sensor gains and offsets. The recursion for gain correction is autonomous, derived from the measurement increments. The recursion for offset correction is based on differences between local measurements and utilizes the results of gain correction. It is proved that the algorithm provides asymptotic convergence to consensus in the sense that the corrected gains and offsets are equal for all sensors. It is demonstrated that the adopted structure of the algorithm enables obtaining high convergence rate, superior to the algorithms existing in the literature. Simulation results are provided illustrating the proposed algorithm properties

Self-Localization of Ad-Hoc Arrays Using Time Difference of Arrivals

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/K007491/1

Randomized and efficient time synchronization in dynamic wireless sensor networks: a gossip-consensus-based approach

This paper proposes novel randomized gossip-consensus-based sync (RGCS) algorithms to realize efficient time correction in dynamic wireless sensor networks (WSNs). First, the unreliable links are described by stochastic connections, reflecting the characteristic of changing connectivity gleaned from dynamicWSNs. Secondly, based on the mutual drift estimation, each pair of activated nodes fully adjusts clock rate and offset to achieve network-wide time synchronization by drawing upon the gossip consensus approach. The converge-to-max criterion is introduced to achieve a much faster convergence speed. The theoretical results on the probabilistic synchronization performance of the RGCS are presented. Thirdly, a Revised-RGCS is developed to counteract the negative impact of bounded delays, because the uncertain delays are always present in practice and would lead to a large deterioration of algorithm performances. Finally, extensive simulations are performed on the MATLAB and OMNeT++ platform for performance evaluation. Simulation results demonstrate that the proposed algorithms are not only efficient for synchronization issues required for dynamic topology changes but also give a better performance in term of converging speed, collision rate, and the robustness of resisting delay, and outperform other existing protocols