Passive Localization Using Time Difference of Arrival and Frequency Difference of ArrivalWC

In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.

Joint TDOA and AOA location algorithm

For the joint time difference of arrival（TDOA） and angle of arrival（AOA） location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location.On the condition of rectangular coordinates,first of all,it figures out the radial range between target and reference stations,then calculates the location of the target.In the case of polar coordinates,first of all,it figures out the azimuth between target and reference stations,then figures out the radial range between target and reference stations,finally obtains the location of the target.Simultaneously,simulation analyses show that the theoretical analysis is correct,and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.

Practical constrained least-square algorithm for moving source location using TDOA and FDOA measurements

By utilizing the time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements of signals received at a number of receivers, a constrained least-square （CLS） algorithm for estimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates could be exploited to constrain the solution. And without requiring apriori knowledge of TDOA and FDOA measurement noises, the proposed algorithm can satisfy the demand of practical applications. Additionally, on basis of con- volute and polynomial rooting operations, the Lagrange multipliers can be obtained efficiently and robustly allowing real-time imple- mentation and global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least square （WLS） approach especially for higher measurement noise level.

BFGS quasi-Newton location algorithm using TDOAs and GROAs

With the emergence of location-based applications in various fields, the higher accuracy of positioning is demanded. By utilizing the time differences of arrival （TDOAs） and gain ratios of arrival （GROAs）, an efficient algorithm for estimating the position is proposed, which exploits the Broyden-Fletcher-Goldfarb-Shanno （BFGS） quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error. Although the accuracy of two-step weighted-least-square （WLS） method based on TDOAs and GROAs is very high, this method has a high computational complexity. While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio （SNR） is high, especially it can achieve better accuracy and smaller bias at a lower SNR. The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance. Simulation results show that with a good initial guess to begin with, the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound （CRLB） accuracy for both near-field and far-field sources.

COMPARISON OF TDOA LOCATION ALGORITHMS WITH DIRECT SOLUTION METHOD

For Time Difference Of Arrival(TDOA) location based on multi-ground stations scene,two direct solution methods are proposed to solve the target position in TDOA location.Therein,the solving methods are realized in the rectangular and polar coordinates.On the condition of rectangular coordinates,first of all,it solves the radial range between the target and reference station,then cal-culates the location of the target.In the case of polar coordinates,the azimuth between the target and reference station is solved first,then the radial range between the target and reference station is figured out,finally the location of the target is obtained.Simultaneously,the simulation and comparison analysis are given in detail,and show that the polar solving method has the better fuzzy performance than that of rectangular coordinate.

A PSO microseismic localization method based on group waves' time difference information

Aiming at the lower microseismic localization accuracy in underground shallow distributed burst point localization based on time difference of arriva（TDOA）,this paper presents a method for microseismic localization based on group waves’ time difference information Firstly, extract the time difference corresponding to direct P wavers dominant frequency by utilizing its propagation characteristics. Secondly, construct TDOA model with non-prediction velocity and identify objective function of particle swarm optimization （PSO）. Afterwards, construct the initial particle swarm by using time difference information Finally, search the localization results in optimal solution space. The results of experimental verification show that the microseismic localization method proposed in this paper effectively enhances the localization accuracy of microseismic explosion source with positioning error less than 50 cm, which can satisfy the localization requirements of shallow burst point and has definite value for engineering application in underground space positioning field.

基于广义互相关时延估计(TDOA)算法的声源定位跟踪系统设计与实现

为实现在二维平面内对声源进行实时定位和动态跟踪,运用时延估计(TDOA)互相关算法设计一种原声监听头阵列的CC-TDOA声源定位跟踪系统,实现对多个原声监听头进行同步采样,再进行信号放大及运算处理,运用LCD屏实时显示目标声源的距离和方位角度,同时运用二维云台控制激光笔对准声源,并持续动态跟踪声源。模拟仿真及真实环境实验测试表明,采用基于到达时间差的互相关定位算法,计算量小,精度较高,测试角度误差小于2o,距离误差小于1.2%,可以满足多种智能应用场合中声源实时定位与跟踪的要求。

一种改进组合加权的TDOA室内二维定位算法

针对现有组合加权算法对定位区域边缘的目标定位时精度较低的问题,在现有组合加权算法的基础上提出了一种改进算法。首先,将基站分组,以到达时差算法得到目标位置的多个估计结果;其次,计算各估计结果之间距离值并排序,以滑动窗口法判断是否存在基站组出现异常定位估计;最后,当任意基站组的定位结果发生异常时,使用目标位置估计结果及其估计克拉美罗下界值设计两个加权步骤的权值,通过二步组合加权算法得到最终定位结果。仿真结果表明,所提算法有效减少了原组合加权算法对定位区域边缘的目标定位时的误差,当测量噪声标准差为0.8 m时,所提算法相较于原算法在正方形边缘区域定位均方根误差减小了0.35 m;在定位狭窄矩形区域时,所提算法平均定位均方根误差减小了0.11 m。

Direct solution for fixed source location using well-posed TDOA and FDOA measurements

Based on the time differences of arrival(TDOA) and frequency differences of arrival(FDOA) measurements of the given planar stationary radiation source, the joint TDOA/FDOA location algorithm which solves the location of the target directly is proposed. Compared with weighted least squares(WLS) methods,the proposed algorithm is also suitable for well-posed conditions,and gets rid of the dependence on the constraints of Earth's surface. First of all, the solution formulas are expressed by the radial range. Then substitute it into the equation of the radial range to figure out the radial range between the target and the reference station. Finally use the solution expression of the target location to estimate the location of the target accurately. The proposed algorithm solves the problem that WLS methods have a large positioning error when the number of observation stations is not over-determined. Simulation results show the effectiveness of the proposed algorithm, including effectively increasing the positioning accuracy and reducing the number of observatories.

Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

Fire rescue challenges and solutions have evolved from straightfor-ward plane rescue to encompass 3D space due to the rise of high-rise city buildings.Hence,this study facilitates a system with quick and simplified on-site launching and generates real-time location data,enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue.Auto-positioning with step-by-step instructions is proposed when launching the locating system,while no extra measuring instrument like Total Station(TS)is needed.Real-time location tracking is provided via a 3D space real-time locating system(RTLS)constructed using Ultra-wide Bandwidth technology(UWB),which requires electromagnetic waves to pass through concrete walls.A hybrid weighted least squares with a time difference of arrival(WLS/TDOA)positioning method is proposed to address real path-tracking issues in 3D space and to meet RTLS requirements for quick computing in real-world applications.The 3D WLS/TDOA algorithm is theoretically constructed with the Cramer-Rao lower bound(CRLB).The computing complexity is reduced to the lower bound for embedded hardware to directly compute the time differential of the arriving signals using the time-to-digital converter(TDC).The results of the experiments show that the errors are controlled when the positioning algorithm is applied in various complicated situations to fulfill the requirements of engineering applications.The statistical analysis of the data reveals that the proposed UWB RTLS auto-positioning system can track target tags with an accuracy of 0.20 m.

传感器位置误差下TDOA-DOA水下目标被动定位算法

针对水下目标被动定位中传感器位置误差带来的定位精度不高的问题,提出了一种基于两步最小二乘的到达时间差波达方向(time difference of arrival-direction of arrival,TDOA-DOA)目标定位算法。首先,构建TDOA-DOA理想化无误差模型,并利用最小二乘算法对目标位置进行粗估计。其次,考虑测量误差和传感器位置误差,构建目标定位误差和传感器位置的联合方程,并利用加权最小二乘求解。最后,利用目标定位误差对目标位置粗估计值进行修正,得到更精确的定位结果。仿真实验表明,所提算法可对目标位置和传感器位置进行联合估计,相较于已有算法具有更高的定位精度,更适用于传感器位置存在误差情况下的水下目标定位。

A robust TDOA based solution for source location using mixed Huber loss

This paper proposes a source localization solution robust to measurement outliers in time differences of arrivals(TDOA)measurements.The solution uses a piecewise loss function named as mixed Huber loss(MHL)proposed based on the classical Huber loss(HL)and its refined version.The MHL is able to effectively mitigate the impact of all levels of measurement outliers by setting two triggering thresholds.In practice,appropriate triggering threshold values can be obtained through simulation given the level of measurement noise and a rough range of potential measurement outliers.A clustering based approach is proposed to further improve the robustness of localization solution against reference sensor related outliers.Simulations are included to examine the solution's performance and compare it with several benchmarks.The proposed MHL based solution is shown to be superior to the classical solution and the benchmarks.The solution is shown to be even robust to multiple measurement outliers.Furthermore,the influence of range measurement outliers in the reference sensor can be effectively mitigated by the clustering based approach.

A Quadratic Constraint Total Least-squares Algorithm for Hyperbolic Location

A novel algorithm for source location by utilizing the time difference of arrival (TDOA) measurements of a signal received at spatially separated sensors is proposed. The algorithm is based on quadratic constraint total least-squares (QC-TLS) method and gives an explicit solution. The total least-squares method is a generalized data fitting method that is appropriate for cases when the system model contains error or is not known exactly, and quadratic constraint, which could be realized via Lagrange multipliers technique, could constrain the solution to the location equations to improve location accuracy. Comparisons of performance with ordinary least-squares are made, and Monte Carlo simulations are performed. Simulation results indicate that the proposed algorithm has high location accuracy and achieves accuracy close to the Cramer-Rao lower bound (CRLB) near the small TDOA measurement error region.

基于TDOA算法的基建现场施工人员定位研究

为了解决当前存在的受大量多径干扰和视距干扰的影响而导致定位精度不足的问题,提出基于到达时间差(TDOA)算法的基建现场施工人员定位方法。利用层叠样式表单技术,搭建三维图像定位基本框架。使用统一的定位服务器,根据基建现场面积确定定位节点数量。创新性地将TDOA算法部署到定位引擎中,从三维图像中提取施工人员特征信息和位置特征信息并进行匹配,得到基建现场施工人员三维特征集合。利用TDOA算法计算待测目标的三维坐标信息,实现施工人员三维图像定位。对比试验结果表明:所提方法的定位数据与实际位置坐标的绝对误差在0.2 m以内;在非视距环境下,连续定位轨迹与模拟的真实轨迹基本一致;在定位距离测试中,测得的距离与真实结果更接近。在视距和非视距环境下,所提方法的定位误差小、测距结果准确、定位精度较高,满足实际定位需求。该研究可以较大程度地消除事故隐患,从而建立相对安全的施工环境、降低基建现场施工中出现事故的概率。

基于多波束/TDOA技术的双星干扰源定位

单星多波束干扰源定位方法需要在3个以上的同频波束都能接收到干扰源信号的情况下才能实现定位。由于同频波束的数量有限以及干扰源位置的随机性,往往会出现能接收到干扰源信号的同频波束少于3个,或接收增益过低影响定位精度的情况。【目的】针对只有两个可用波束的定位问题以及进一步提高干扰源的定位精度,提出了通过邻星与主星建立基于多波束天线与到达时间差(TDOA)技术的双星联合定位模型。【方法】通过建立双星联合定位模型,并联立出定位方程组证明了该模型的可行性。同时,基于定位几何稀疏精度因子(GDOP)对定位模型的接收增益误差、波束指向误差、到达时间差误差以及位置预测误差4个方面进行了定位误差分析,并使用Matlab进行仿真对比。【结果】仿真实验表明,基于多波束天线与TDOA技术的双星联合定位方法的定位精度明显优于传统的单星多波束定位方法。【结论】基于多波束天线与TDOA技术的双星联合定位方法利用了TDOA对定位精度影响较小的优势,使其代替部分波束参与到卫星定位中,不仅减少了对定位波束数量的需求,而且减少了测量增益的误差与波束指向的误差,大大提高了定位的精度并提升了可靠性,较单星多波束定位更具优势。

TDOA目标模拟信号光子链路传输延时测量系统

在TDOA(time difference of arrival)目标模拟系统中,采用微波光子链路传输包含精确TDOA信息的多路多频段目标模拟信号,为保证TDOA信息的精度足够高,需要精确测量目标模拟信号经过光子链路的传输延时。从特定工程应用角度提出一种光子链路传输延时测量方法,通过专用延时测量芯片实现传输延时高分辨率、高精度测量,通过延时测量信号和目标模拟信号分时占用单根光纤的相同光传输波道,实现光子链路传输延时测量和目标模拟信号传输分时工作,从机理上满足了精确测量光子链路传输延时所需硬件条件。试验结果:表明该方法可精确测量目标模拟信号经过光子链路的传输延时,测量误差小于1 ns,比传感器的TDOA测量精度高一个数量级,满足系统对光子链路传输延时的测量精度要求。

视距环境下基于改进鸟群优化算法的TDOA定位方法

针对视距环境下到达时间差定位中遇到的非线性方程组解算复杂问题,提出了一种基于改进鸟群优化算法的到达时间差定位方法.利用Chebyshev混沌映射对算法进行初始化,提高了初始解的质量,增强了种群的多样性.实验结果表明,与采用其他混沌映射的鸟群优化算法相比,改进鸟群优化算法在求解到达时间差定位方法的非线性方程组最优解的问题上具有更低的定位误差.

High Performance of a TOA-TDOA Hybrid GSM Location System for Intelligent Transportation Systems

This paper illustrates the performance of a mobile positioning technique applicable to a GSM network.An experimental system of a network-based GSM positioning for ITS has been proposed, and the hybrid TOA-TDOA method based on GSM signaling has been analyzed and used. The performance of the proposed system is showed through simulations in urban and suburban environments. The accuracy for 67% mobile stations is 70 m in urban and 120 m in suburban. The accuracy, coverage and network load of positioning system are also analyzed.

面向TDOA定位的分布式雷达部署策略优化方法研究

针对到达时间差被动定位任务,研究了分布式雷达的部署策略优化问题,以提升系统的定位和监视性能。现有研究大多仅关注节点位置的优化,而未充分考虑节点法线指向与系统监视性能间的耦合关系。文中结合实际应用场景,考虑了节点位置与法线指向的联合优化策略,构建了面向定位任务的单目标优化问题以及兼顾定位和监视任务的多目标优化问题。由于这些优化问题具有复杂耦合约束和非凸特性,解析解难以获得。文中提出一种区域约束多目标粒子群算法(RC-MOPSO),用以求解最优部署策略。该算法通过在粒子初始化和更新过程中引入约束区域,确保粒子在迭代过程中始终满足复杂耦合约束条件。仿真结果表明,所提方案实现了定位和监视性能的最优平衡,相较于随机部署方案表现出显著优势,同时对辐射源发射功率估计误差表现出较强的鲁棒性。

基于自适应Levy飞行改进的TDOA三维定位算法

针对已有的算法在基于到达时间差(time difference of arrival,TDOA)测量方案中存在的搜索能力不均衡,导致三维定位区域局部存在定位精度低甚至求解失败的问题,提出了一种基于改进探路者优化算法(pathfinder algorithm,PFA)的TDOA定位算法,通过将自适应Levy飞行和改进后的PFA算法进行融合,增强了个体对定位区域复杂环境的适应性,解决算法早熟、易陷入局部最优等问题,提升了算法综合性能.通过仿真和实验,结果表明:与Taylor算法、LM算法相比,本文提出的算法(Levy-pathfinder algorithm,LPFA)可以提高定位精度;与PSO算法、PFA算法相比,LPFA算法可以在提高运算速度的同时得到更准确的定位结果.