Distributed Target Tracking with Fading Channels over Underwater Wireless Sensor Networks

This paper investigates the problem of distributed target tracking via underwater wireless sensor networks (UWSNs) with fading channels. The degradation of signal quality due to wireless channel fading can significantly impact network reliability and subsequently reduce the tracking accuracy. To address this issue, we propose a modified distributed unscented Kalman filter (DUKF) named DUKF-Fc, which takes into account the effects of measurement fluctuation and transmission failure induced by channel fading. The channel estimation error is also considered when designing the estimator and a sufficient condition is established to ensure the stochastic boundedness of the estimation error. The proposed filtering scheme is versatile and possesses wide applicability to numerous real-world scenarios, e.g., tracking a maneuvering underwater target with acoustic sensors. Simulation results demonstrate the effectiveness of the proposed filtering algorithm. In addition, considering the constraints of network energy resources, the issue of investigating a trade-off between tracking performance and energy consumption is discussed accordingly.Comment: 12 pages, 6 figures, 6 table

A new approach to distributed fusion filtering for networked systems with random parameter matrices and correlated noises

This paper is concerned with the distributed filtering problem for a class of discrete-time stochastic systems over a sensor network with a given topology. The system presents the following main features: (i) random parameter matrices in both the state and observation equations are considered; and (ii) the process and measurement noises are one-step autocorrelated and two-step cross-correlated. The state estimation is performed in two stages. At the first stage, through an innovation approach, intermediate distributed least-squares linear filtering estimators are obtained at each sensor node by processing available output measurements not only from the sensor itself but also from its neighboring sensors according to the network topology. At the second stage, noting that at each sampling time not only the measurement but also an intermediate estimator is available at each sensor, attention is focused on the design of distributed filtering estimators as the least-squares matrix-weighted linear combination of the intermediate estimators within its neighborhood. The accuracy of both intermediate and distributed estimators, which is measured by the error covariance matrices, is examined by a numerical simulation example where a four-sensor network is considered. The example illustrates the applicability of the proposed results to a linear networked system with state-dependent multiplicative noise and different network-induced stochastic uncertainties in the measurements; more specifically, sensor gain degradation, missing measurements and multiplicative observation noises are considered as particular cases of the proposed observation model.This research is supported by Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional FEDER (grant no. MTM2014- 52291-P, MTM2017-84199-P)

Intelligent antenna sharing in cooperative diversity wireless networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (p. 143-152).Cooperative diversity has been recently proposed as a way to form virtual antenna arrays that provide dramatic gains in slow fading wireless environments. However, most of the proposed solutions require simultaneous relay transmissions at the same frequency bands, using distributed space-time coding algorithms. Careful design of distributed space-time coding for the relay channel is usually based on global knowledge of some network parameters or is usually left for future investigation, if there is more than one cooperative relay. We propose a novel scheme that eliminates the need for space-time coding and provides diversity gains on the order of the number of relays in the network. Our scheme first selects the best relay from a set of M available relays and then uses this "best" relay for cooperation between the source and the destination. Information theoretic analysis of outage probability shows that our scheme achieves the same diversity-multiplexing gain tradeoff as achieved by more complex protocols, where coordination and distributed space-time coding for M relay nodes is required. Additionally, the proposed scheme increases the outage and ergodic capacity, compared to non-cooperative communication with increasing number of participating relays, at the low SNR regime and under a total transmission power constraint.(cont.) Coordination among the participating relays is based on a novel timing protocol that exploits local measurements of the instantaneous channel conditions. The method is distributed and allows for fast selection of the best relay as compared to the channel coherence time. In addition, a methodology to evaluate relay selection performance for any kind of wireless channel statistics is provided. Other methods of network coordination, inspired by natural phenomena of decentralized time synchronization, are analyzed in theory and implemented in practice. It was possible to implement the proposed, virtual antenna formation technique in a custom network of single antenna, half-duplex radios.by Aggelos Anastasiou Bletsas.Ph.D

Predicting Types of Failures in Wireless Sensor Networks Using an Adaptive Neuro-fuzzy Inference System

In this paper, Adaptive Neuro-Fuzzy Interference System (ANFIS) technique is used to develop models to predict two conditions commonly found in a Wireless Sensor Network's deployment; these conditions are failure due to (i) poorly deployed environment and (ii) human movements. ANFIS models are trained using parameters obtained from actual ZigBee PRO nodes' Neighbour Table experimented under the influence of associated network challenges. These parameters are Mean RSSI, Standard Deviation RSSI, Average Coefficient of Variation RSSI and Neighbour Table Connectivity. The individual and combined effects of parameters are investigated in-depth. Results showed the mean RSSI is a critical parameter and the combination of mean RSSI, ACV RSSI and NTC produced the best prediction results (~92%) for all ANFIS models

Design and theoretical analysis of advanced power based positioning in RF system

Accurate locating and tracking of people and resources has become a fundamental requirement for many applications. The global navigation satellite systems (GNSS) is widely used. But its accuracy suffers from signal obstruction by buildings, multipath fading, and disruption due to jamming and spoof. Hence, it is required to supplement GPS with inertial sensors and indoor localization schemes that make use of WiFi APs or beacon nodes. In the GPS-challenging or fault scenario, radio-frequency (RF) infrastructure based localization schemes can be a fallback solution for robust navigation. For the indoor/outdoor transition scenario, we propose hypothesis test based fusion method to integrate multi-modal localization sensors. In the first paper, a ubiquitous tracking using motion and location sensor (UTMLS) is proposed. As a fallback approach, power-based schemes are cost-effective when compared with the existing ToA or AoA schemes. However, traditional power-based positioning methods suffer from low accuracy and are vulnerable to environmental fading. Also, the expected accuracy of power-based localization is not well understood but is needed to derive the hypothesis test for the fusion scheme. Hence, in paper 2-5, we focus on developing more accurate power-based localization schemes. The second paper improves the power-based range estimation accuracy by estimating the LoS component. The ranging error model in fading channel is derived. The third paper introduces the LoS-based positioning method with corresponding theoretical limits and error models. In the fourth and fifth paper, a novel antenna radiation-pattern-aware power-based positioning (ARPAP) system and power contour circle fitting (PCCF) algorithm are proposed to address antenna directivity effect on power-based localization. Overall, a complete LoS signal power based positioning system has been developed that can be included in the fusion scheme --Abstract, page iv

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Digital data transmission over an HF channel

The thesis is concerned with detection, estimation techniques and a method of the adaptive adjustment of the equaliser, for use in a 4800bit/sec synchronous digital transmission system operating over a voice-band time-varying HF channel. Two main impairments are additive Gaussian noise and inter-symbol interference (ISI), which can be very severe at times. All techniques considered here are algorithms or processes that operate on sequences of sample values. Modern digital modems normally operate in this way, and the techniques described are of direct application to practical systems, and could be implemented using the new technology of high speed real-time digital signal processing (DSP). The performance of the various systems that employ the above techniques are obtained using the computer simulated model of three types of HF channels. The ionospheric propagation medium, the characteristics of HF channel and the signal distortion introduced by the channel are first described. The thesis then presents a suitable base-band model of the HF channel for computer simulation of quadrature amplitude modulation systems. A suitable method for the adjustment of the receiver is described next. This method is suitable both for the adjustment of a conventional decision feedback equaliser (DFE), and also for the adjustment of a linear feedforward filter that is employed ahead of a near-maximum likelihood (NML) detector. This method uses a minimum phase (root-finding) algorithm (MPA) to convert the channel response from being non-minimum phase to at least approximately minimum phase. The results of computer simulation tests of this algorithm are then presented over different types of HF channel models. The results demonstrate the algorithm's capability to make the channel response minimum (or near-minimum) phase. Various NML detectors, derived from the Viterbi detector, are discussed. Each detector is here preceded by an adaptive linear filter that is adjusted adaptively using an MPA. The performance of these detectors is compared with the conventional DFE, whose tap-gains are adjusted adaptively using an MPA, and the detector which gives the best compromise between performance and complexity is selected for combined receivers. These results are obtained using perfect estimation of the channel response. The estimation techniques studied in this thesis include both new and conventional estiniators, which are based on the least- mean-square (LMS) algorithm or recursive least-square(RLS) algorithm. The estimator provides an estimate of the sampled impulse response (SIR) of the channel, necessary for the NML detector or MPA. The performances of these estimators are compared using computer simulation tests. The results also demonstrate that the simpler LMS algorithm with adaptive step size gives a comparable level of accuracy with the more complex RLS algorithm. Finally the most promising of the detectors and estimators are connected with an adaptive equaliser, using an MPA, to form a new combined receiver. The details of the combined system structure with its computational complexity are given. Extensive computer simulation tests have been carried out on the different arrangements of the combined system including DFE, when all the functions of detection, estimation and MPA are present, in order to find the most cost effective system in terms of performance and complexity. A considerable reduction in the equipment complexity can be achieved by allowing a long period between successive adjustment of the adaptive filter and estimator

RSSI based self-adaptive algorithms targeting indoor localisation under complex non-line of sight environments

Location Based Services (LBS) are a relatively recent multidisciplinary field which brings together many aspects of the fields of hardware design, digital signal processing (DSP), digital image processing (DIP), algorithm design in mathematics, and systematic implementation. LBS provide indirect location information from a variety of sensors and present these in an understandable and intuitive way to users by employing theories of data science and deep learning. Indoor positioning, which is one of the sub-applications of LBS, has become increasingly important with the development of sensor techniques and smart algorithms. The aim of this thesis is to explore the utilisation of indoor positioning algorithms under complex Non-Line of sight (LOS) environments in order to meet the requirements of both commercial and civil indoor localisation services. This thesis presents specific designs and implementations of solutions for indoor positioning systems from signal processing to positioning algorithms. Recently, with the advent of the protocol for the Bluetooth 4.0 technique, which is also called Bluetooth Low Energy (BLE), researchers have increasingly begun to focus on developing received signal strength (RSS) based indoor localisation systems, as BLE based indoor positioning systems boast the advantages of lower cost and easier deployment condition. At the meantime, information providers of indoor positioning systems are not limited by RSS based sensors. Accelerometer and magnetic field sensors may also being applied for providing positioning information by referring to the users’ motion and orientation. With regards to this, both indoor localisation accuracy and positioning system stability can be increased by using hybrid positioning information sources in which these sensors are utilised in tandem. Whereas both RSS based sensors, such as BLE sensors, and other positioning information providers are limited by the fact that positioning information cannot be observed or acquired directly, which can be summarised into the Hidden Markov Mode (HMM). This work conducts a basic survey of indoor positioning systems, which include localisation platforms, using different hardware and different positioning algorithms based on these positioning platforms. By comparing the advantages of different hardware platforms and their corresponding algorithms, a Received Signal Strength Indicator (RSSI) based positioning technique using BLE is selected as the main carrier of the proposed positioning systems in this research. The transmission characteristics of BLE signals are then introduced, and the basic theory of indoor transmission modes is detailed. Two filters, the smooth filter and the wavelet filter are utilised to de-noise the RSSI sequence in order to increase localisation accuracy. The theory behind these two filter types is introduced, and a set of experiments are conducted to compare the performance of these filters. The utilisation of two positioning systems is then introduced. A novel, off-set centroid core localisation algorithm is proposed firstly and the second one is a modified Monte Carlo localisation (MCL) algorithm based system. The first positioning algorithm utilises BLE as a positioning information provider and is implemented with a weighted framework for increasing localisation accuracy and system stability. The MCL algorithm is tailor-made in order to locate users’ position in an indoor environment using BLE and data received by sensors locating user position in an indoor environment. The key features in these systems are summarised in the following: the capacity of BLE to compute user position and achieve good adaptability in different environmental conditions, and the compatibility of implementing different information sources into these systems is very high. The contributions of this thesis are as follows: Two different filters were tailor-made for de-nosing the RSSI sequence. By applying these two filters, the localisation error caused by small scale fading is reduced significantly. In addition, the implementation for the two proposed are described. By using the proposed centroid core positioning algorithm in combination with a weighted framework, localisation inaccuracy is no greater than 5 metres under most complex indoor environmental conditions. Furthermore, MCL is modified and tailored for use with BLE and other sensor readings in order to compute user positioning in complex indoor environments. By using sensor readings from BLE beacons and other sensors, the stability and accuracy of the MCL based indoor position system is increased further