Department Publications

Real Time Location Estimation systems (RTLS) developed for outdoor environments have shown significant errors due to changes in atmospheric conditions, multipath propagation and inherent signal strength variations. In this paper, we present an improved Wi-Fi based RTLS solution for the outdoors that reduces the above impacts. In addition this paper presents the development of a portable device for implementing the above RTLS solution. The research makes use of Euclidean, standard deviation based and probabilistic algorithms. Data smoothening is done to reduce the multipath propagation issues. The different algorithm combinations are compared via their error cumulative distribution functions.

Novel single-integral representations for the multivariate probability density functions and cumulative distribution functions of Gaussian class distributions (Rayleigh, Rician, Weibull, Nakagami- m , and generalized Rician) are derived. The solutions are expressed in terms of well-known functions which are available in common mathematical software. The marginal random variables are not necessarily identically distributed as is the case for some past solutions. A generalized correlation structure based on a special linear transformation of independent Gaussian random variables is used in this study. The advantage of the new representation is that only a single-integral computation is needed to compute an N -dimensional distribution.

A novel approach is introduced for the analysis of energy detection of unknown deterministic signals, where the energy detector uses dual diversity reception. The energy detector is assumed to employ a low complexity diversity technique, namely square-law combining. A general case where the two diversity branches are correlated is treated by the analysis. Detection and false alarm probabilities for the energy detector are derived for correlated Rayleigh and Rician fading channels.

Novel single-integral representations for the bivariate probability density function and cumulative distribution function of two correlated Rician random variables are derived. The solutions are expressed in terms of well known functions which are available in common mathematical software. The two random variables are not necessarily identically distributed as required by some past solutions. The new form of the bivariate Rician cumulative distribution function is applied to give a new expression for the outage probability of dual selection combining diversity operating in correlated Rician fading.

Novel representations for the multivariate probability density function and cumulative distribution function of the non-central chi-square distribution are derived. The solutions are expressed in terms of well known functions which are available in common mathematical software. When the number of degrees of freedom, m, is even, the new representation has the advantage that only a single-integral computation is needed to compute a N-dimensional distribution. The new representations are used to numerically evaluate the outage probability of multiple input multiple output systems with receiver antenna selection, operating in correlated Rician fading. The well known equal correlation model, which is considered to be a useful model for a closely placed set of antennas, is used for the analysis.

Novel single-integral representations for the multivariate probability density functions (PDFs) and cumulative distribution functions (CDFs) of the Gaussian class Weibull distribution are derived. The solutions are expressed in terms of familiar mathematical functions which are available in common mathematical software. The well known equal (constant) correlation model is considered. A special linear transformation of independent Gaussian random variables is used to generate correlated Weibull random variables. The advantage of the new representation is that only a single integral computation is needed to compute a N-dimensional distribution. The new representation of the CDF is used for the performance evaluation of a selection diversity combiner operating in equally correlated Weibull fading channels. The new PDF representation is also used for an analysis of the moments of the output signal-to-noise ratio …

Novel representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of the equi-correlated non-central chi-square (χ 2 ) distribution are derived. The new representations are given as single integral solutions in terms of well known mathematical functions which are available in common mathematical software packages. The advantage of the new representations is that only a single integral computation is needed to evaluate the PDF and CDF for an arbitrary number of dimensions. The new representations are used to numerically evaluate the outage probability of a single user multiple input multiple output system with receiver antenna selection diversity, operating in correlated Rician fading channels. The well known constant (equal) correlation model, which is considered to be a useful model for a closely placed set of antennas, is used for the analysis in this paper. A …

This paper describes the synthesis and evaluation of a "virtual odometer" for a Quadrotor Micro Aerial Vehicle. Availability of a velocity estimate has the potential to enhance the accuracy of mapping, estimation and control algorithms used with quadrotors, increasing the effectiveness of their applications. As a result of the unique dynamic characteristics of the quadrotor, a dual axis accelerometer mounted parallel to the propeller plane provides measurements that are directly proportional to vehicle velocities in that plane. Exploiting this insight, we encapsulate quadrotor dynamic equations which relate acceleration, attitude and the aerodynamic propeller drag in an extended Kalman filter framework for the purpose of state estimation. The result is a drift free estimation of lateral and longitudinal components of translational velocity and roll and pitch components of attitude of the quadrotor. Real world data sets gathered from two different quadrotor platforms, together with ground truth data from a Vicon system, are used to evaluate the effectiveness of the proposed algorithm and demonstrate that drift free estimates for the velocity and attitude can be obtained.

Localization Assistance for Mobile Robot Navigation in Real, Populated Environments - Shibaura Institute of Technology Skip to main navigation Skip to search Skip to main content Shibaura Institute of Technology Home Shibaura Institute of Technology Logo English 日本語 Home Profiles Research units Research output Activities Press/Media Prizes Search by expertise, name or affiliation Localization Assistance for Mobile Robot Navigation in Real, Populated Environments Peshala Jayasekara, Takeshi Sasaki, Hideki Hashimoto Functional Control Systems Research output: Contribution to journal › Article › peer-review Overview Original language English Pages (from-to) 2P1-Q13(1)-2P1-Q13(2) Journal Default journal Publication status Published - 2011 May 28 Cite this APA Standard Harvard Vancouver Author BIBTEX RIS Powered by Pure, Scopus & Elsevier Fingerprint Engine™ All content on this site: …

Developingautonomous mobile robots thatcan coexist with human in populatedenvironments isstill considered a bigchallenge, Tb address thisproblemwe propose, a novel scheme to assist mobile robots by providing localizationinformationexternally Thisscheme eombines the autonomous navigation and target tracking research fieldsto arrive at a structured assistance system for autonomous mobile robots. In the proposed scheme, the environment issensed using a laserrange finder and camera based sensor unit. Using Rao-Blackwellizecl panicle filtertechnique, the robots that need assistance are continuously tracked, tncontrast with conventional laserrange finderbasedtrackingsystems, the placementof sensor ischanged to a levelabove average human heightand the mobile robots are medified by attaching a cylindrical pole. The experiments show the validity of the proposed scheme forsimultaneous localization assistance formultiple mobile robots. IXvomobile robots were simultaneously navigated ingiventrajectoriesusing assistance data, successfully

Autonomous personal vehicle systems face many challenges due to complex and unpredictable environments. Thus, much of such platforms' computational resources are wasted on trying to localize in a given environment, slowing down the navigation phase. To overcome this problem we propose intelligent assistance, a novel scheme to assist autonomous mobile platforms by providing localization information externally. In the proposed scheme, the moving targets are detected using a laser range finder and camera based sensor unit and tracked using particle filter based technique. Calculated localization is fed back to the mobile platform as assistance information. The preliminary experiments show the validity of the proposed scheme for mobile robots.

In this paper, a new algorithm for indoor localization using WLAN signal strengths is proposed. The objective of the work was to design a simple and efficient indoor positioning algorithm with good accuracy. The proposed algorithm uses the fingerprinting technique as a pre-processing step. The second step is the application of trilateration within the nearest neighbours found during the first step. The paper describes the algorithm, the environment used to test the algorithm and results obtained. The results show that the proposed algorithm has 44% better accuracy compared to basic fingerprinting technique and the accuracy is 73% better compared to basic trilateration technique. The algorithm has been demonstrated to be independent of the propagation environment and works with no knowledge of the positions and the transmit powers of the WLAN access points in the vicinity. Thus, it is a simple and effective …

This paper analyzes the performance of an Extended Kalman Filter (EKF) based attitude estimator for a Quad Rotor Unmanned Aerial Vehicle (QRUAV). A non-linear dynamic model of the QRUAV, simulated in Matlab was complemented with an EKF based attitude estimator. The estimator fuses measurements obtained from simulated accelerometers and gyroscopes onboard the QRUAV. It is then shown that this estimator only results in adequate representation of the attitude when the translational velocity is large. This behavior is explained considering the dynamics of the vehicle and the onboard accelerometers. Also a possible method of exploiting this behavior for improving the estimation accuracy is suggested.

Novel single integral representations for the multivariate probability density function and cumulative distribution function of Rayleigh and Rician distributions are derived. A generalized correlation structure is used in this analysis. The derived novel representations are used to evaluate the outage probability of N-branch selection diversity operating in correlated Rayleigh and Rician fading channels modeled by the generalized correlation model.

Novel simple forms for the probability density function (PDF) and the cumulative distribution function (CDF) of two correlated Rician random variables (RVs) are derived. The new representations for the bivariate Rician PDF and CDF are given in the form of single integral solutions in terms of well known functions that are available in common mathematical software packages. The general case of non-identically distributed Rician RVs is considered in this analysis. The new form of the bivariate Rician cumulative distribution function is applied to give a new expression for the outage probability of dual selection combining diversity operating in correlated Rician fading.

In this paper we first analyze the effects of least square based parameter estimation for a autoregressive stochastic model of inertial sensor errors. We then proceed to develop the recursive least squares (RLS) estimation of the autoregressive model parameters and also discuss a fast update method for recursive least square estimation to reduce the computation complexity. This reduction leads to an efficient online dynamic estimation of inertial sensor error model which can then augment a navigation system based on such sensors. Simulation results and actual inertial sensor data are analyzed and it is shown that the RLS estimate can achieve a 20% reduction in forward prediction error as compared to the non-recursive estimate.

Novel single integral representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of the Nakagami-m distribution with integer and identical fading severity parameter m are derived. A generalized correlation structure is used in this model. The single integral solutions for the PDF and the CDF are given in terms of well known mathematical functions which are available in common mathematical software packages. The novel representation derived for multivariate CDF is used to evaluate the outage probability of N-branch selection diversity combining operating in correlated Nakagami-m fading modeled by the generalized correlation model.

Research in the areas of localization, mapping and path planning for single mobile robots has been carried out extensively. Nevertheless, relatively little of its work is applied to multiple robot systems. Moreover, when these robots coexist with human, complex and unpredictable human environments make the above navigational tasks even more challenging. To address this problem we propose intelligent assistance, a novel scheme to assist mobile robots by providing localization information externally. This scheme aims to combine the research fields of autonomous mobile robot navigation and target tracking. The mobile robots are detected using a laser range finder and camera based sensor unit. Using Rao-Blackwellized particle filter technique, the sensory information is integrated in a probabilistic manner and the mobile robots that need assistance are continuously tracked. We maneuver the non-holonomic …

Novel single integral representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of Gaussian class Weibull distributions are derived. A special linear transformation of independent Gaussian random variables is used to generate correlated Weibull random variables. The solutions are expressed in terms of familiar functions which are available in common mathematical software. The well known equal (constant) correlation model is used in this paper. The advantage of the new representation is that only a single integral computation is needed to compute a L-dimensional distribution. Some applications of the new distribution representations are also given.

Multivariate statistics play an important role in performance analysis of wireless communication systems in correlated fading channels. This thesis presents a framework which can be used to derive easily computable mathematical representations for some multivariate statistical distributions, which are derivatives of the Gaussian distribution, and which have a particular correlation structure. The new multivariate distribution representations are given as single integral solutions of familiar mathematical functions which can be evaluated using common mathematical software packages. The new approach can be used to obtain single integral representations for the multivariate probability density function, cumulative distribution function, and joint moments of some widely used statistical distributions in wireless communication theory, under an assumed correlation structure. The remarkable advantage of the new …

Scintillation effect is a dominant atmospheric impairment among the various contributing factors for low fade margin communication systems operating on high frequency bands such as Ku. Empirical analysis of scintillations can be done using signal strength measurements which can be treated as a time series prediction problem in forecasting the short-term scintillation effect. This paper discusses the time series based statistical prediction analysis of tropospheric scintillation effect. The experiment was performed under clear sky conditions where the other attenuation contributions such as rain, dense clouds is minimum. The experiment was setup at the University of Moratuwa, Sri Lanka using a Ku band satellite downlink operating on a moderately high elevation angle of 45 degrees. The time series analysis was performed using linear, non-linear, fuzzy and neural prediction techniques. The results show that …

Intelligent Localization Assistance for Mobile Robots Using Rao-Blackwellized Particle Filter Based Target Tracking - Shibaura Institute of Technology Skip to main navigation Skip to search Skip to main content Shibaura Institute of Technology Home Shibaura Institute of Technology Logo English 日本語 Home Profiles Research units Research output Activities Press/Media Prizes Search by expertise, name or affiliation Intelligent Localization Assistance for Mobile Robots Using Rao-Blackwellized Particle Filter Based Target Tracking Peshala G. Jayasekara, Takeshi Sasaki, Leon Palafox, Hideki Hashimoto Functional Control Systems Research output: Contribution to journal › Article › peer-review Overview Original language English Pages (from-to) 346-349 Journal Default journal Publication status Published - 2010 Nov 26 Cite this APA Standard Harvard Vancouver Author BIBTEX RIS Powered by Pure, Scopus & …

Estimation of the location of a Mobile Station accurately is a key requirement to effectively provide a wide range of Location Based Services over mobile networks. Hence developing cellular positioning techniques has been a key research problem, with numerous localization solutions been proposed. These include technologies such as Cell ID, angle and time of arrival methods, statistical methods and fingerprinting methods. This paper presents fingerprinting based positioning techniques suitable for outdoor and indoor positioning. Multiple positioning techniques were proposed, implemented and evaluated with outdoor and indoor trials. The ultimate solution proposed in this paper is not a single positioning technique; rather it presents several positioning techniques that achieve optimum performance in each test environment. The results reports 67% positioning error as 112 m, 299 m and 221 m for urban …

The database correlation method (DCM) is a network based positioning technology which has shown superior in terms of accuracy. DCM is based on a pre-measured database of a location dependent variable such as received signal strength (RSS). Even though the technique has good potential, the practical difficulty in forming the database (fingerprints) using field measurements has become the major challenge in implementing this in large, dynamic networks. A remedy for this is to make use of propagation model predictions instead of field measurements to create the fingerprints. However, due to the considerable deviation between the predictions and the actual measurements, the positioning accuracy diminishes with this approach. In order to overcome this issue, tuning of the predictions using a small number of field measurements can be applied. The work presented in this paper proposes a technique for the correction of such deviations which would improve the performance of DCM. The proposed tuning process, Cell-wise Calibration, is based on artificial neural networks (ANN). Two different training algorithms, particle swarm optimization Algorithm (PSO) and BFGS Algorithm are applied for ANN training. The results of the trials carried out in urban, suburban and rural environments are presented. With the PSO algorithm, the level of accuracy is comparable to that obtained with a measured fingerprint database in urban and suburban environments, and is better in rural environment.

The paper proposes an improved network-based positioning technique based on database correlation and presents the application of the proposed technique to GSM. The fingerprint database is created using field measurements and a novel and a more practical method for gathering fingerprints is introduced. The authors propose a Weighted k-Nearest Neighbor (WkNN) method for location estimation and the trial results obtained in urban and suburban environments in Sri Lanka are presented. Comparison with the Geometrical method shows that the proposed method is a competitive alternative for GSM location.