A study of indoor positioning systems using iBeacons with different transmission power levels

Abstract

The prevalence of smartphones has increased the demand for and application of location-based services. However, the Global Positioning System, currently the most widely used positioning technology, cannot provide accurate positioning services when obstructed by obstacles. Consequently, this system can only provide outdoor application services such as outdoor navigation and tracking. In 2013, Apple Inc. released iBeacon, a positioning technology based on Bluetooth low energy (BLE). This device transmits Bluetooth signals within a specific range, in which the signals are received by other smartphones to calculate distances for providing indoor positioning-related services. In this study, the iBeacon transmission power level is adjusted to significantly increase Bluetooth signal differences in indoor environments. Therefore, it can reduce received signal strength indicators (RSSI) similarity for some reference points by adjusting the power level. Subsequently, radio frequency signals are filtered using a modified moving average filter to reduce signal variations after reception. Next, pattern matching and the K-Nearest Neighbors (KNNs) algorithm are integrated to facilitate positioning. The integration of the modified moving average filter with the KNNs algorithm increases the positioning accuracy by 23.08% during the online phase. This finding can thus improve location-based services.     

Position Vectors Based Efficient Indoor Positioning System

With the advent and advancements in the wireless technologies, Wi-Fi fingerprinting-based Indoor Positioning System (IPS) has become one of the most promising solutions for localization in indoor environments. Unlike the outdoor environment, the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efficient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things (IoTs) and green computing. In this paper, we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors. Initially, in the database development phase, Motley Kennan propagation model is used with Hough transformation to classify, detect, and assign different attenuation factors related to the types of walls. Furthermore, important parameters for system accuracy, such as, placement and geometry of Access Points (APs) in the coverage area are also considered. New algorithm for deployment of an additional AP to an already existing infrastructure is proposed by using Genetic Algorithm (GA) coupled with Enhanced Dilution of Precision (EDOP). Moreover, classification algorithm based on k-Nearest Neighbors (k-NN) is used to find the position of a stationary or mobile user inside the given coverage area. For k-NN to provide low localization error and reduced space dimensionality, three APs are required to be selected optimally. In this paper, we have suggested an idea to select APs based on Position Vectors (PV) as an input to the localization algorithm. Deducing from our comprehensive investigations, it is revealed that the accuracy of indoor positioning system using the proposed technique unblemished the existing solutions with significant improvements.     

Epoch-by-epoch GPS ambiguity processing for local network-based positioning

When processing code- and carrier-phase ranges sampled at individual epochs, the control baseline of a pair of reference receivers can bring forth relative integer-valued ambiguities and tropospheric delays. The estimates are usually so accurate that they may act as constraints, when a roving user who operates in the network of references requires instantaneous position solutions. This paper has the objective of taking advantage of a tropospheric zenith delay surface for the user’s ranging corrections. A local network of six reference stations was used to study the single-epoch position estimation, which revealed that with the increased reliability of ambiguity resolution on both L1 and L2 carriers, global positioning system-derived height accuracy was refined by more than 60%.     

基于声学脉冲响应的室内建图算法研究

由于室内环境下噪声及混响干扰造成声学脉冲响应(Acoustic Impulse Response,AIR)的波达时间(Time of Arrival,TOA)模糊,导致现有室内空间几何建图技术存在计算复杂等缺点,提出一种基于AIR可信度判断与霍夫变换结合的定位和建图一步完成的方法。该方法基于到达时间差(Time Difference of Arrival,TDOA)迭代估计声源位置并计算准确的TOA,随后基于声收发设备与一阶反射TOA关于反射面的椭圆约束关系,结合可信度判断与霍夫变换,筛选可信低阶TOA以实现室内反射面的二维位置估计。蒙特卡洛仿真结果表明,在混响时间T60为0.1347 s、AIR误差标准差为22.7×10^-3 ms、大小为10 m×8 m×4 m复杂室内环境下,墙面定位平均距离误差为10.1 cm,平均角度误差为2.7958°。在大小为5.26 m×3.5 m×3.35 m的真实房间中,该方法可以实现声源与墙体位置的同时定位,完成规则盒型房间的二维地图重构,且墙面定位平均距离误差为2.6 cm,平均角度误差为2.17°。     

Cooperative SLAM using fuzzy Kalman filtering for a collaborative air-ground robotic system

ABSTRACT

This paper presents a three-dimensional (3D) cooperative simultaneous location and mapping (SLAM) method for a collaborative air-ground robotic system, designed to manage an indoor quadrotor flying done together with a Mecanum-wheeled omnidirectional robot (MWOR) in indoor unknown and no GPS environments. An ORB (Oriented Fast and Rotated BRIEF)-SLAM 2.0 (ORB- SLAM 2.0) approach is used to produce a 3D map and discover the position of the indoor quadrotor simultaneously, and a particle-filter SLAM (FastSLAM 2.0) approach is employed to build the 2D map of the global environment for the MWOR. A more accurate 3D quadrotor position estimation (QPE) method for the quadrotor is proposed with the assistance of the MWOR. A cooperative SLAM using fuzzy Kalman filtering is proposed to fuse the outputs of the ORB-SLAM 2.0, FastSLAM 2.0, and QPE approaches, in order to localize the quadrotor more accurately. Both SLAM approaches, quadrotor position estimation method and cooperative SLAM have been implemented in the robotic operation system (ROS) environment. Moreover, the cooperative SLAM method is exploited to achieve landing of the quadrotor atop the MWOR. Five experiments are conducted to show the effectiveness and superiority of the proposed cooperative SLAM method.     

A chaotic image cryptosystem based on Toeplitz and Hankel matrices

Abstract

Because of properties in chaos system such as the sensitive dependence on initial conditions, system parameters, pseudorandom property and ergodicity, chaotic image encryption algorithm can suggest a new and efficient way of encryption scheme, which has been studied more and more in recent years. A novel chaotic image encryption algorithm based on Toeplitz matrix and Hankel matrix is proposed in this paper. We shuffle totally the positions of image pixels to confuse the relationship between the plain image and cipher image combined with Toeplitz matrix, Hankel matrix and logistic chaotic system. Another hyper-chaos system of Chen's chaotic system is taken to change the grey values of image pixels to enhance the security further. Experimental results in Sections 3 and 4 demonstrate that the key space is large enough and the key is sensitive to initial conditions to resist the brute force attack in the proposed algorithm. Additionally, the distribution of grey values in encrypted image has a random-like behaviour to resist statistical analysis.     

基于KFCM-LMC-LSSVM算法的WLAN室内定位方法

针对WLAN室内定位采集指纹点工作量大且定位精度不高的问题,提出一种基于核模糊C均值聚类(kernelized fuzzy C-means,KFCM)、低秩矩阵填充(low-rank matrix completion,LMC)及最小二乘支持向量机(least squares support vector machine,LSSVM)的室内定位算法。首先将指纹点利用KFCM算法进行聚类,使待测点定位到一个区域内。在该区域里运用LMC理论,重构出具有高密度指纹点的指纹库。最后利用LSSVM定位出待测点的物理位置。实验结果表明,采用KFCM-LMC-LSSVM算法不仅减少了构建指纹库的工作量,而且提高了定位精度。     

A new modified fast fractal image compression algorithm

Abstract

In this paper, a new fractal image compression algorithm is proposed, in which the time of the encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with the use of innovative predefined values for contrast scaling factor, S, instead of searching it across. Only the domain blocks with entropy greater than a threshold are considered to belong to the domain pool. The algorithm has been tested for some well-known images and the results have been compared with the state-of-the-art algorithms. The experiments show that our proposed algorithm has considerably lower encoding time than the other algorithms giving approximately the same quality for the encoded images.     

基于反卷积的双线阵聚焦波束形成被动定位方法

为了提高双线阵聚焦波束形成在阵元数少或频率低时的定位精度,文章研究了一种基于反卷积的双线阵聚焦波束形成被动定位方法。首先在测量区内对双线阵接收信号进行球面波补偿,给出噪声源分布的声图信息。然后根据阵型的参数,计算双线阵的指向性函数。最后利用一种适用于移变阵列的二维扩展R-L反卷积算法,对声图波束输出和双线阵的指向性函数做反卷积,求解基于反卷积波束形成的源的分布。该方法旁瓣更低,分辨力更高,有效提高双线阵聚焦波束形成的定位精度和左右舷分辨能力,为后续的减振降噪、噪声检测等工作提供了参考。     

一种二分迭代实时声线修正算法

为提高对水下目标的定位精度,提出并实现了一种二分迭代实时声线修正算法。首先通过二分迭代法快速搜索出水下声源所发出的定位声信号传播声线的初始掠射角,然后以该初始掠射角对应的唯一声线为基础,根据斯涅耳(Snell)声线折射定理计算得到声源与水下接收阵元的距离值,最终利用与声线相符的三路测距值进行交汇解算,完成实时声线修正定位。湖上试验结果表明,该算法简单易行、运算速度快,能够满足实时修正处理的要求,在复杂水文条件下提高了水声定位系统的定位精度。该算法具有良好的工程实用性和通用性,可推广应用于同类水声跟踪定位系统。     

Video enhancement through image registration based on structural similarity

Abstract

It is commonly known that the mean square error (MSE) does not accurately reflect the subjective image quality for most video enhancement tasks. Among the various image quality metrics, structural similarity (SSIM) metric provides remarkably good prediction of the subjective scores. In this paper, a new registration method based on contribution of structural similarity measurement to the well known Lucas–Kanade (LK) algorithm has been proposed. The core of the proposed method is contributing the SSIM in the sum of squared difference of images along with the Levenberg–Marquardt optimisation approach in LK algorithm. Mathematical derivation of the proposed method, based on the unified framework of Baker et al., is given. The proposed registration algorithm is applied to a video enhancement successfully. Various objective and subjective comparisons show the superior performance of the proposed method.     

An improved algorithm for finding efficient schedules with respect to total flowtime and maximum tardiness

Abstract

This paper presents a new algorithm for finding efficient schedules with respect to total flowtime and maximum tardiness. A detailed comparison is made between this algorithm and the well‐known Van Wassenhove and Gelders’ algorithm (VGA) on a variety of problem sizes, up to 100 jobs. Computational results show that the proposed algorithm is of considerable value, especially for large problems. In particular, for the 10‐job problem the proposed algorithm requires roughly one‐half the computation time of VGA, and for the 100‐job problem the ratio reduces to one to sixteen.     

New creep law

Abstract

In the present paper, a new creep law describing the high temperature strain rate of materials, which is applicable to both high and low values of stresses, is proposed. In a similar way to the known hyperbolic sine law, the proposed equation guarantees a potential behaviour for low stress values (in accordance to the power law of creep) and a pure exponential behaviour for high stress values, according to the power breakdown law of creep. The differences and possible advantages of the proposed equation are analysed in comparison with the hyperbolic sine law.     

基于最大似然估计的辐射噪声源近场定位方法性能分析

如何利用较少的阵元个数得到比较理想的空间分辨力,准确找到噪声源位置,一直是人们比较关心的问题,因此介绍了基于最大似然估计的辐射噪声源近场定位方法,并利用遗传算法寻求最大似然估计的全局最优解,从而实现噪声源近场定位,其具有比常规聚焦波束形成更高的空间分辨力,且可以有效实现相干声源近场定位。通过计算机仿真详细分析了信噪比、测量距离及基阵孔径对本文算法定位性能的影响,说明了仅利用小孔径基阵就可实现辐射噪声源近场高分辨定位,最后通过湖试实验验证了该方法的有效性,具有一定的工程应用价值。     

Modelling of dynamical system and generalised circulant matrix in image encryption

Abstract

In this paper, a modelled image encryption scheme is presented, of which generalised circulant matrix is employed together with dynamical chaotic system. The strong correlations among adjacent pixels in plain-image can be declined greatly by the proposed scheme. Meanwhile, the diffusion transform is considered simultaneously to avoid statistical analysis, known plaintext and chosen plaintext attack. The experimental results show that the proposed scheme can suggest an efficient way to hide the image information, and has the advantages of large key space, sensitive to initial conditions and zero correlation between adjacent pixels in cipher-image. Moreover, the grey values in the cipher-image are distributed symmetrically. The proposed image scheme can be applied to practical image information transmission and protection in the public.     

Scheduling flexible manufacturing cells using Tabu Search

Scheduling is an important aspect in the overall control of a flexible manufacturing system. The research presented focuses on production scheduling of jobs within a flexible manufacturing cell (FMC)–one type of flexible manufacturing system. Due to the complexity of the FMC scheduling problem, a 0–1 mixed-integer linear programming (MILP) model is formulated for M machines and N jobs with alternative routings. Although small instances of the problem can be solved optimally with MILP models, a two-stage Tabu Search (TS² ) algorithm that minimises the manufacturing makespan (MS) is proposed to solve medium-to-large-scale problems more efficiently. During Stage I (construction phase), two heuristics are utilised to generate an initial feasible sequence and an initial MS solution. In Stage II (improvement phase), the acquired initial solutions from Stage I are combined with a Tabu Search meta-heuristic procedure that provides improved MS solutions. The TS² algorithm provides tremendous savings in computational time for medium/large-sized multi-machine FMC problems.     

Soil parameter determination for deep excavation analysis by optimization

Abstract

This paper presents an efficient method of determining soil parameters for finite element analysis of deep excavation. Due to the limitation of soil tests, field measurements are often used to calibrate in‐situ soil properties. This process is time consuming and computationally cumbersome. In this paper, nonlinear optimization techniques are applied to determine the unknown parameters of an objective function, which is defined as the sum of the square of differences between observed and predicted values. The convergence and stability of the optimization algorithm are confirmed by three well‐known mathematical functions and a hypothetical excavation case under varied ground conditions. Finally, a case study is presented to show the reliability of the proposed soil parameter determination procedure.     

Image tracking of motorcycles and vehicles on urban roads and its application to traffic monitoring and enforcement

Abstract

Image tracking has increasingly gained attention for use in vision‐based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real‐time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.     

Binocular self-calibration performed via adaptive genetic algorithm based on laser line imaging

Abstract

An accurate technique to perform binocular self-calibration by means of an adaptive genetic algorithm based on a laser line is presented. In this calibration, the genetic algorithm computes the vision parameters through simulated binary crossover (SBX). To carry it out, the genetic algorithm constructs an objective function from the binocular geometry of the laser line projection. Then, the SBX minimizes the objective function via chromosomes recombination. In this algorithm, the adaptive procedure determines the search space via line position to obtain the minimum convergence. Thus, the chromosomes of vision parameters provide the minimization. The approach of the proposed adaptive genetic algorithm is to calibrate and recalibrate the binocular setup without references and physical measurements. This procedure leads to improve the traditional genetic algorithms, which calibrate the vision parameters by means of references and an unknown search space. It is because the proposed adaptive algorithm avoids errors produced by the missing of references. Additionally, the three-dimensional vision is carried out based on the laser line position and vision parameters. The contribution of the proposed algorithm is corroborated by an evaluation of accuracy of binocular calibration, which is performed via traditional genetic algorithms.