Multi-cluster-center based filtering algorithm and its application to WLAN indoor positioning

Wireless local area network(WLAN) is developing to a ubiquitous technique in daily life.As a related product,WLAN based indoor positioning system is attracting more and more concern.Fingerprint is a mainstream method of wireless indoor positioning.However,it still has some shortcomings of that received signal strength(RSS) is multi-modal and sensitive to environmental factors.These characters would have a negative effect on the performance of positioning system.In this paper,a filtering algorithm based on multi-cluster-center is proposed.We make full use of this algorithm to optimize the training samples at off-line phase to improve the performance of non-linear fitting with the fingerprint feature,and further enhance the positioning accuracy.Finally,we use multiple sets of original WLAN signal samples and signal samples after filtering as the training input of positioning system respectively.After that,the results analysis is demonstrated.Simulation results show that it is a reliable algorithm to enhance the performance of WLAN indoor positioning.     

一种改进的位置指纹智能手机室内定位算法

为了减小智能手机现有室内定位算法的时间复杂度和空间复杂度,提出一种将确定型算法和概率分布算法融合的智能手机室内定位新方法。利用最近邻算法选出K个最相近的位置点,然后采用贝叶斯算法将K个位置点中匹配概率最大的点作为最终的估计位置。在Android手机上分别采用3种方法进行20组室内对比定位实验,并随机选取10个位置进行定位误差对比实验,结果表明,新方法比贝叶斯算法的复杂度降低了Ο(4n/5),比最近邻算法的定位准确率提高了约4%,且定位误差较小。     

面向移动终端的室内定位技术探讨及应用研究

随着“互联网+”概念的提出,移动互联网飞速发展,国内数据业务和移动网络服务在用户中越来越普及,室内定位技术显现出了极大的应用价值。文章从室内定位的当前技术背景出发,分析了目前行业内主要的室内定位算法并进行详细介绍,然后针对当前主流的几种室内定位技术在其技术特点和应用限制方面进行了比较分析,同时以大型商超为主要切入点,对室内定位技术现在的应用状况及瓶颈问题进行了归纳总结。     

基于改进MSCKF的无人机室内定位方法

针对无人机室内定位容易出现漂移的问题,提出基于改进多状态约束卡尔曼滤波器（MSCKF）的无人机（UAV）室内定位方法. 该方法在MSCKF的框架下,提出高鲁棒性、低时延的标志点检测方法. 利用在世界坐标系下坐标已知的标志点计算得到无人机位姿,实现惯性测量单元(IMU)信息与单目视觉信息融合以及无人机位姿修正. 对提出的定位方法进行测试. 测试结果表明,该方法的定位误差小于0.266 m,与OpenVins和LARVIO开源算法相比,定位精度提高了54.6%以上.     

WiFi指纹定位中改进的加权k近邻算法

针对WiFi指纹定位中传统的信号欧氏距离不能很好地反映各位置点间物理距离的问题,提出了改进的加权k近邻定位算法。首先,在信号距离的计算中引入接收信号强度的方差;然后,根据接收信号强度和物理距离之间的非线性关系引入加权系数,设计了一种信号加权欧氏距离;最后,利用信号加权欧氏距离进行指纹匹配和位置估计,改进了加权k近邻算法。在真实环境下的实验结果表明,信号加权欧氏距离能够更准确地衡量各点之间的物理距离并选择更合理的最近邻参考点。与现有的加权k近邻算法相比,改进的加权k近邻算法能够明显地提高WiFi指纹定位的精度。     

基于扩展卡尔曼滤波算法的室内定位跟踪系统

为了解决无线室内定位系统实时跟踪位置坐标误差较大问题,提出一种基于扩展卡尔曼滤波(EKF)算法的室内定位方法。系统采用基于WiFi信号指纹定位,然后利用扩展卡尔曼滤波对估算的位置进行滤波,以改善WiFi指纹定位方法的精度,达到对目标实时跟踪。仿真和实验结果表明,该算法有效地改善了系统定位精度,能较好地满足室内定位的需求。     

Kalman滤波在GPS非差相位精密单点定位中的应用

阐述单台双频GPS非差相位精密单点定位的数学模型,在最小二乘估计基础上,导出卡尔曼滤波算法。提出采用迭代扩展卡尔曼滤波算法解决非差相位非线性方程在线性化过程中产生的线性误差问题,并将其应用于GPS数据实时处理,不仅很好地降低非线性方程线性化产生的误差,而且能够精确推算到用户的三维位置。     

Spatially localized and joint access point selection for Wi-Fi indoor positioning

Wi-Fi indoor positioning system has received increasing interest in pervasive computing applications due to its low cost and satisfactory accuracy. To obtain high positioning accuracy based on source limited devices, various AP selection strategies have been proposed to select the most discriminant APs for positioning. In this paper, we propose a spatially localized AP selection method based on joint location information gain. In contrast to traditional AP selection methods which measure the discriminant ability of APs independently, we consider choosing APs jointly. By considering the correlation of the discriminant ability between different APs, more accurate measure of the discriminant ability of APs can be taken. Furthermore, since the optimal AP selection solution varies spatially, we incorporate a location clustering method to localize AP selection and subsequent positioning process. Finally, support vector regression (SVR) algorithm is combined to estimate the location. Experiments are carried in a realistic Wi-Fi indoor environment. Experimental results show that, by using the localized joint AP selection strategy, the proposed positioning method achieves a high-level accuracy while reducing the energy consumption on client devices significantly.     

基于分段线性模型的卡尔曼滤波非均匀校正算法

为了降低探测器响应的漂移以及非线性对非均匀性校正的影响,提出了一种基于分段线性模型的卡尔曼滤波红外焦平面阵列非均匀性校正算法。该算法引入探测器响应曲线的分段线性模型,对基于卡尔曼滤波器的红外焦平面非均匀性校正算法进行了扩展和改进,不仅能减小探测器的偏置和增益随时间漂移对校正的影响,而且还能消除探测器响应非线性对非均匀性校正性能的影响。一组利用真实红外图像序列进行的实验验证了该算法可获得较好的校正性能。     

自组网中节点位置推测算法的研究

为了在自组网上开展基于位置的服务 ,以及提高自组网的网络性能 ,有必要使网络节点知道自己的位置 .设计了一种自组网中的节点位置推测算法 ,该算法利用部分节点的已知位置和节点间的距离 ,推测出其余节点的位置 .通过实例计算 ,验证了该算法的有效性     

观测噪声时间相关的动态定位算法

在动态定位数据处理中,动态定位的精度和可靠性除受观测偶然误差和系统误差的影响外,还受时间相关的观测噪声的影响.在观测噪声不满足时间不相关的假设情况下,卡尔曼滤波将达不到最优滤波效果,并且其误差协方差阵也是错误的.分析了测量噪声时间相关对卡尔曼滤波结果的影响,给出了观测噪声时间相关时的卡尔曼滤波递推公式.实例计算结果表明,采用该算法能够有效地消除测量噪声相关性对滤波结果的影响.     

混合卡尔曼滤波的非均匀校正算法

提出了一种基于混合卡尔曼滤波的非均匀校正算法,可以用于解决参数漂移为非线性的问题．该方法首先根据给定状态空间模型的特点,使用无迹卡尔曼滤波技术和传统卡尔曼滤波技术分别处理非线性的状态转移模型和线性的观测模型,然后把估计结果用于非均匀校正．使用仿真的一维和二维数据验证算法性能,实验结果表明,所提算法扩展了传统卡尔曼滤波算法的使用范围,并且与扩展卡尔曼滤波算法相比,具有较高的稳定性和估计精度．     

管道内检测导航定位技术

针对管道内检测器在管道运行中的定位问题,提出了一种利用导航定位系统进行管道内检测器定位的辅助方法.当管道内检测器进行管道检测时,在管道内检测器上加装惯性导航器件（IMU）构成导航定位系统,将获得的导航定位信息和速度修正信息存储在存储器中.利用导航算法对数据进行处理,采用卡尔曼滤波器对误差进行修正,分析得出管道内检测器的姿态变化和位置变化信息.实验结果表明,通过计算能够获得实验模型运行的姿态变化信息,描绘出实验模型的行进轨迹,分析出实验模型对于初始位置的地理坐标变化情况,为工程实验提供了更多的参考信息.     

基于卡尔曼滤波的水动力模型实时校正方法

提出交替卡尔曼滤波方法,即联立连续方程和动量方程,分别以水位、流量作为状态量建立滤波器方程进行两滤波器交替计算,较好地解决了校正过程中不同类型状态量之间共同校正的问题.对长江干流局部河段进行实例验证,采用三峡水库135 m蓄水阶段的水文资料预报6 h洪水过程,其结果表明本文校正预报方法对提高实时预报精度有效.     

室内可见光成像传感器定位系统的理论极限

针对室内可见光定位系统的参数优化问题,计算了基于成像传感器接收的接收机位置的估计理论极限,求出了估计量的克拉美罗下界.对于室内典型的应用场景,当接收机的成像点测量值受高斯白噪声影响时,计算出接收机位置的最大似然估计量,并推出克拉美罗下界.采用LED发射机和成像传感器接收机的真实参数进行数值仿真,结果表明:可实现精确的定位估计,定位精度一般处于毫米量级.定位误差取决于接收机距房顶的垂直距离、透镜焦距、成像传感器的像素大小以及帧速率等参数.     

Indoor positioning algorithm based on Markov Monte Carlo

The interference in the received power leads to the problem of the low estimation accuracy of WLAN indoor positioning, so a new method is proposed which constructs the maximum likelihood model and uses the Markov Chain Monte-Carlo sampling method to estimate position coordinates. The method considers taking the interference factor into the model, and uses the random sampling method to solve the estimation problem, which has the advantage of fast convergence and high estimate precision. Furthermore, the Cramer-Rao lower bound (CRLB) of the model is derived. In simulation experiment, the distribution of Cramer-Rao Bound in locating space is given. Finally, simulations show that the MCMC method can estimate the target location accurately. Under the same simulation conditions, the MCMC method achieves greater estimated precision and has a lower computational complexity than the Fletcher-Reeves Method (FR).     

车载导航系统精确定位算法的优化

针对车载导航系统下定位的点转换到实际电子地图的过程中存在误差,通过改善坐标转换模型来提高车载导航系统的定位精度,在经典的平面转换算法的基础上,首先利用高斯投影把全球定位系统接收的(B,L)坐标转化成平面坐标(X,Y);其次根据最小二乘法,确定转换参数;同时把公共点本身误差作为随机参数处理,将转换参数作为非随机参数,利用最小二乘法配置建立转换模型,以得到稳定的参数估值,避免了公共点因分布不均引起的误差．与传统算法相比,实验结果验证了该算法具有更高的实时性和稳定性．     

改进的室内三维模糊位置指纹定位算法

提出了改进的三维空间模糊指纹定位方法(ITF)。该方法首先采用高斯模型对样本节点和未知节点的RSSI值进行过滤,建立样本点的指纹数据库,并将传统的求解高次坐标问题转换成空间隶属度的问题。利用模糊匹配算法计算未知节点与指纹库中各个已知样本点的贴近度,通过贴近度权系数定位未知节点。实验结果表明该定位方法比传统定位算法在降低误差方面具有更高的性能。     

Traffic analysis on carrier accessing for WLAN indoor positioning system

Currently,the WLAN indoor positioning system attracts a lot of interests,not only because of the cheap implementation but also because of the high positioning accuracy comparing with other indoor posit...     

Barometric altimeter in wireless communication network indoor positioning system

A differential barometric altimetry technology based on the digital pressure sensors is put forward by using the existing mobile phone base station as reference. The height of known base station is precise. The pressure and temperature of the known base station is measured by sensors and transmitted to users. The absolute height value of user will be calculated by combining the barometric pressure values and temperature values from the base station with the locally measured values. In order to decrease system errors caused by inconsistency between the measured pressure value at base station and the locally measured pressure value,weights correction is applied based on multiple reference stations. The calculated height value is accurate due to eliminating the measured errors caused by irregular changes of atmospheric pressure,with the error less than 1 m. Resolution of elevation positioning depends upon the resolution of the pressure sensor,the relationship between which is approximately linear. When the resolution of sensor is 0. 0 1 hPa,the resolution of elevation positioning is about 0. 1 m. In addition,the data frame format at base station is designed in this article. Experimental results show that the method is accurate,reliable,stable and has the ability to distinguish floors and stair steps.