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.     

Acoustic emission location on aluminum alloy structure by using FBG sensors and PSO method

Acoustic emission location is important for finding the structural crack and ensuring the structural safety. In this paper, an acoustic emission location method by using fiber Bragg grating (FBG) sensors and particle swarm optimization (PSO) algorithm were investigated. Four FBG sensors were used to form a sensing network to detect the acoustic emission signals. According to the signals, the quadrilateral array location equations were established. By analyzing the acoustic emission signal propagation characteristics, the solution of location equations was converted to an optimization problem. Thus, acoustic emission location can be achieved by using an improved PSO algorithm, which was realized by using the information fusion of multiple standards PSO, to solve the optimization problem. Finally, acoustic emission location system was established and verified on an aluminum alloy plate. The experimental results showed that the average location error was 0.010 m. This paper provided a reliable method for aluminum alloy structural acoustic emission location.     

Improved GNSS Cooperation Positioning Algorithm for Indoor Localization

For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range single point positioning, and the positioning performance of cooperative node is analyzed, therefore the information of pseudo-range and position of node 1 is obtained. Secondly, the distance between cooperative nodes is obtained by using the baseline method with double-difference carrier phase. Finally, the cooperative location algorithms are studied. The Extended Kalman Filtering (EKF), Unscented Kalman Filtering (UKF) and Particle Filtering (PF) are used to fuse the pseudo-range, ranging information and location information respectively. Due to the mutual influences among the cooperative nodes in cooperative positioning, the EKF, UKF and PF algorithms are improved by resetting the error covariance matrix of the cooperative nodes at each update time. Experimental results show that after being improved, the influence between the cooperative nodes becomes smaller, and the positioning performance of the nodes is better than before.     

基于端点检测的精确时延提取方法及其定位精度分析

针对脉冲声源定位中时延误差大的问题,提出了一种基于端点检测的精确时延提取方法。该方法首先对信号进行滤波处理和端点检测,截取有效信号段运用广义互相关法估计时延,然后利用端点检测得到的信息提取出精确的时延值,最后用单纯形替换法求解声源位置。根据精确时延提取方法,设计了声源定位方案。实验证明,该方法能有效减弱非高斯白噪声和室内混响的影响,定位精度可达到分米甚至厘米级,并且具有较好的鲁棒性。     

一种声速-位置联合估计的水声导航定位方法

长基线水声导航定位方法利用各信标到水下航行器的信号传播时间和等效声速来估计水下航行器的位置,但各信标到水下航行器的等效声速估计存在误差,导致定位误差较大,且随着导航距离的增加,定位误差呈增长趋势。针对这一问题,提出了一种基于粒子滤波的水声导航定位方法,将等效声速和水下航行器的位置作为估计状态参量,通过测量信标信号到水下航行器的传播时间,建立粒子滤波模型对其位置进行估计,准确地估计并跟踪等效声速变化,从而提高定位精度,减小估计误差。仿真结果表明,在水下航行器初始位置未知的情况下,与常规方法相比,文中所提方法的定位精度提高了4倍左右。     

基于时频分析和改进差分进化的多点泄漏定位方法

当管道同时发生多个泄漏点时,多个泄漏点的声波信号出现混叠,从而影响泄漏声信号的传播和衰减规律。在多点泄漏声波信号混叠的情况下,传统的泄漏定位方法无法对多个泄漏点进行有效定位。为此,提出了一种基于时频分析和改进差分进化的多点泄漏定位方法。由于变分模态分解(variational mode decomposing, VMD)的分解模态个数对特征提取有影响,因此采用能量函数估计分解模态个数,从而对VMD改进。然后采用改进VMD对多点泄漏声波信号进行处理。另外,通过时频分析(time-frequency analysis, TFA)估计多个泄漏点数量,从而得到多点泄漏的定位函数。差分进化(differential evolution, DE)算法易陷入局部最优,在进化后期收敛速度较慢,采用粒子群优化(particle swarm optimization, PSO)算法提高DE的全局收敛速度,并通过改进的差分进化算法估计多个泄漏点的位置。在管道现场进行多点泄漏的模拟试验,试验结果表明该方法能够准确地估计多点泄漏位置,泄漏定位的最小误差为18 m。     

Effective Form Error Assessment Using Improved Particle Swarm Optimization

This paper presents an improved variant of particle swarm optimization (MPSO) algorithm for the form error evaluation, from a set of coordinate measurement data points. In classical particle swarm optimization (PSO), new solution is updated by the existing one without really comparing which one is better. This behaviour is considered to be caused by lack in exploitation ability in the search space. The proposed algorithm generates new swarm position and fitness solution employing an improved and modified search equation. In this step, the swarm searches in proximity of the best solution of previous iteration to improve the exploitation behaviour. The particle swarm employs greedy selection procedure to choose the best candidate solution. A non-linear minimum zone objective function is formulated mathematically for each form error and consequently optimized using proposed MPSO algorithm. Five benchmark functions are used to prove the efficiency of the proposed MPSO algorithm, by comparing the proposed algorithm with established PSO and genetic algorithm. Finally, the results of the proposed MPSO algorithm are compared with previous literature and with other nature inspired algorithms on the same problem. The results validate that proposed MPSO algorithm is more efficient and accurate as compared to other conventional methods and is well suited for effective form error evaluation using CMMs.     

Carrier phase indoor positioning using pseudolites and relative movements

Abstract

In many previous indoor pseudolite‐positioning methods, the initial rover position needed to be assumed known in the ambiguity resolution process. In this paper a new ambiguity resolution method for indoor pseudolites positioning is proposed. Instead of assuming the initial rover position is known, the algorithm uses relative movement information to solve for the initial rover position iteratively. Also, a suitable integrity check criterion is proposed to determine when the estimated ambiguity values have converged to the true values. Simulation results based on realistic indoor positioning environments demonstrate the validity of the algorithm, and the convergence behaviors of the algorithm are also studied.     

微创外科机器人导航系统空间映射精度分析与仿真

论文分析了微创外科机器人导航系统空间映射误差的主要来源,定义了空间映射中的四种误差类型。并对每种误差都做了详细的介绍,同时也简要介绍了其他误差源。通过仿真分析标记点定位误差即基准点定位误差对基于仿射坐标系的空间映射精度的影响,得出基准点定位误差与靶点映射误差成正比,基准点在两个空间的定位误差变化范围的差距较小时靶点映射误差较小的结论;通过仿真分析标记点的分布方式对基于仿射坐标系的空间映射精度的影响,得出对空间映射精度影响较大的两种标记点分布方式:共面分布和不能将靶点包围在其分布范围内的标记点分布。共面分布会导致利用仿射坐标系求解映射矩阵时发生畸变,导致映射误差发生突变;靶点在标记点包围区域外时,与靶点在标记点包围区域内时的空间映射相比也会产生很大的靶点映射误差。     

基于自适应混合近似模型的顶置武器站多柔体系统动力学优化研究

针对顶置武器站结构优化设计存在计算量大、优化效率低等问题,提出一种基于自适应混合近似模型的优化策略,引入分层设计空间缩减思想,在优化迭代过程中依次在构造的全局空间、聚类空间和重点空间内选取样本点更新混合近似模型,以同时提高模型的全局和局部预测能力。使用典型测试函数算例和某顶置武器站结构动力优化实例,验证了所提优化策略的有效性。顶置武器站结构动力优化结果表明:使用该方法获得的武器站炮口扰动目标函数减小了58.3%,各炮口扰动参数得到有效改善;与静态近似模型方法相比,该方法所得的炮口扰动目标函数优化结果降低了14.5%,所需调用武器站分析计算模型次数减少了47.4%。     

Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region division line, a modified signal collection device is used to measure RSS in two directions of each reference point. All RSS values are compared and the region where the RSS value has the relative largest signal strength is located as next candidate region. The location coordinate of the target Wi-Fi AP is obtained when the localization region of the target Wi-Fi AP is successively approximated until the candidate region is smaller than the accuracy threshold. There are 360 experiments carried out in this paper with 8 types of Wi-Fi APs including fixed APs and portable APs. The experimental results show that the average localization error of the proposed localization algorithm is 0.30 meters, and the minimum localization error is 0.16 meters, which is significantly higher than the localization accuracy of the existing typical indoor Wi-Fi access point localization methods.     

Application of the nonlinear, double-dynamic Taguchi method to the precision positioning device using combined piezo-VCM actuator

In this research, the nonlinear, double-dynamic Taguchi method was used as design and analysis methods for a high-precision positioning device using the combined piezo-voice-coil motor (VCM) actuator. An experimental investigation into the effects of two input signals and three control factors were carried out to determine the optimum parametric configuration of the positioning device. The double-dynamic Taguchi method, which permits optimization of several control factors concurrently, is particularly suitable for optimizing the performance of a positioning device with multiple actuators. In this study, matrix experiments were conducted with L9(3(4)) orthogonal arrays (OAs). The two most critical processes for the optimization of positioning device are the identification of the nonlinear ideal function and the combination of the double-dynamic signal factors for the ideal function's response. The driving voltage of the VCM and the waveform amplitude of the PZT actuator are combined into a single quality characteristic to evaluate the positioning response. The application of the double-dynamic Taguchi method, with dynamic signal-to-noise ratio (SNR) and L9(3(4)) OAs, reduced the number of necessary experiments. The analysis of variance (ANOVA) was applied to set the optimum parameters based on the high-precision positioning process.     

Research on the Signal Reconstruction of the Phased Array Structural Health Monitoring Based Using the Basis Pursuit Algorithm

The signal processing problem has become increasingly complex and demand high acquisition system, this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal. The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals. According to the principles of the compressive sensing and signal processing method, non-sparse ultrasonic signals are converted to sparse signals by using sparse transform. The sparse coefficients are obtained by sparse decomposition of the original signal, and then the observation matrix is constructed according to the corresponding sparse coefficients. Finally, the original signal is reconstructed by using basis pursuit algorithm, and error analysis is carried on. Experimental research analysis shows that the signal reconstruction method can reduce the signal complexity and required the space efficiently.     

回转运动坐标定位精度的检测与误差补偿模型

在对回转运动坐标定位精度的干涉测量原理和方法进行深入研究的基础上，采用激光干涉法检测混联机床C轴的定位精度和重复定位精度，并做出了基于测量数据的混联机床C轴单向均位偏差特性曲线，推导出了C轴顺、逆时针旋转定位误差数学模型。利用最小二乘法拟合得到了机床回转运动坐标目标位置的均值误差补偿数学模型，提出了一种回转运动坐标定位精度的激光干涉测量方法和误差补偿模型的建模方法。     

基于改进粒子群算法的复杂曲面轮廓度误差评定及可视化

针对复杂曲面轮廓度误差的求解是一个复杂的非线性寻优问题,将改进的粒子群算法与细分曲面逐次逼近的方法相结合,实现了复杂曲面轮廓度误差值的精确计算和评定结果可视化。利用双3次B样条曲面进行理论廓面的拟合,从最小条件准则出发,建立了曲面轮廓度误差的数学模型;通过细分曲面逐次逼近的方法,计算出点到曲面的最小距离。在对基本粒子群算法分析的基础上,引入了非线性动态惯性权重系数和杂交算子,提高了算法的精度和效率。以VRML作为三维展示平台、Java Applet作为控制核心,实现了面轮廓度误差评定的可视化、网络化。     

Adaptive split spectrum processing using a neural network

The polarity thresholding algorithm for split spectrum processing (SSP) is known to work well once properly tuned. However, there are several problems related to the finding of the right split parameters such as the number of filters and the information carrying spectral range. Here we show that the polarity thresholding method can be formulated as a multilayer perceptron (MLP) neural network with binary neurons and binary input signals operating in feedforward mode. Then the method is generalized to process nonbinary data using an adaptive MLP with graded neurons. Experiments with real ultrasonic NDE signals are presented using the conventional backpropagation optimization algorithm (BP) and a second order optimization method (BFGS) with exact line search. Finally, alternative adaptive algorithms based on a decomposition of the network into single neurons or linear discriminants are briefly discussed.     

推料四杆机构参数优化与运动精度分析研究

目的 对于四杆机构在包装推料应用中,其运动轨迹与理论要求差别较大,不能很好地满足高精度包装产品需求的问题,拟采用改进蚁群算法来优化四杆机构几何参数。方法 引入二维坐标系建立四杆机构几何参数,通过数学关系式推导运动轨迹点的坐标方程式。分析四杆机构几何参数变量,构造多目标优化误差函数,添加四杆机构运动约束条件。引用改进蚁群算法对四杆机构几何参数进行多目标优化,采用数学软件Matlab对优化结果进行误差仿真验证。结果 仿真结果表明,四杆机构参数优化后,横向和纵向的平均误差、均方根误差降低,横向的平均误差和均方根误差分别降低了55.9%和59.1%,纵向的平均误差和均方根误差分别降低了56.7%和53.5%。结论 采用改进蚁群算法优化四杆机构几何参数,提高了四杆机构在包装中的定位精度。     

基于迭代递推的供水管道多泄漏点声定位方法

针对多泄漏点产生的声发射信号及环境噪声对供水管道泄漏定位的影响,进行供水管道多泄漏点声定位方法研究。发展了一种基于迭代递推的供水管道多泄漏点声定位方法,研究迭代递推中品质因数阈值、信噪比阈值、相位偏移量的寻优区间和泄漏相关时频点的判定阈值等参数选择对泄漏定位效果的影响,并优选出适合的参数值。在此基础上,进行供水管道多漏点检测实验;结果表明,该方法可以实现管道上多个泄漏检测和定位,且定位误差小于1 m。研究工作为实际供水管道多泄漏点检测及定位提供了可行的解决方案。     

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.     

Leveraging Logical Anchor into Topology Optimization for Indoor Wireless Fingerprinting

The indoor subarea localization has wide application space in dynamic hot zone identification, indoor layout optimization, store dynamic pricing and crowd flow trend prediction. The ubiquitous mobile devices provide the opportunity for wireless fingerprinting-based indoor localization services. However, there are two short board where the existing methods have been criticized. One is that a tagging approach requires a large number of professional surveys for wireless fingerprint construction, which weakens the scalability of the methods. The other is that the crowdsourcing-based methods encounter the cold boot problem in the system initial stage. To address these issues, the paper proposes a topology optimization approach leveraging the dynamic logical anchor selection into a subarea localization system. First of all, a new annular-based radio map construction strategy with the feedback selection of logic anchor is designed to release the pressure of site survey. The implementation of this strategy harnesses the characteristics of the indoor building structure and inter subarea overlapping recognition, without the topology and distribution of physical anchor (e.g., access points or POIs). Secondly, exploiting the probabilistic support vector machine algorithm, the target is localized in the corresponding subarea in a real-time pattern. Furthermore, the localization error is calibrated with an error recognition algorithm. Finally, massive experiments are implemented on a prototype system. The results show that the proposed method can decrease the overhead of the system initialization and achieve higher localization accuracy compared with the existing approaches.