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.

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。

一种基于加权质心的TOF与TDOA联合定位算法

在大噪声环境或者标签位于基站附近等定位场景中,UWB TDOA定位模式下的定位算法存在精度低且发散等问题。针对此问题,引入飞行时间差(TOF)测距和加权质心算法,构建了一种新的TOF与到达时间差(TDOA)联合定位算法。首先,利用TOF测距,得到TDOA双曲线定位方程,与传统的TOA测距相比,所提算法不需要严格的时间同步;其次,为解决大噪声环境多个定位圆不相交而无法定位的问题,引入TOF加权质心算法得到标签的初始粗定位置,并代入TDOA双曲线方程组;最后,采用Taylor迭代思想计算出标签坐标。仿真实验对比分析其他方法和所提算法在不同噪声环境和不同标签位置下的定位精度、算法复杂度以及标签定位散点图,结果表明:与TOF、TOF-TDOA、TOA-TDOA算法相比,本文算法能够在大噪声环境下提供较高的定位精度和定位范围;当噪声方差等于0.75时,本文算法定位精度分别提升了30.1%、25.6%和25.8%;不管标签远离双曲渐近线或者靠近基站,本文算法均能够提供稳定的定位性能,且满足UWB实时定位的需求。

Hybrid TDOA/FDOA and track optimization of UAV swarm based on A-optimality

The source location based on the hybrid time difference of arrival(TDOA)/frequency difference of arrival(FDOA) is a basic problem in wireless sensor networks, and the layout of sensors in the hybrid TDOA/FDOA positioning will greatly affect the accuracy of positioning. Using unmanned aerial vehicle(UAV) as base stations, by optimizing the trajectory of the UAV swarm, an optimal positioning configuration is formed to improve the accuracy of the target position and velocity estimation. In this paper, a hybrid TDOA/FDOA positioning model is first established, and the positioning accuracy of the hybrid TDOA/FDOA under different positioning configurations and different measurement errors is simulated by the geometric dilution of precision(GDOP) factor. Second, the Cramer-Rao lower bound(CRLB) matrix of hybrid TDOA/FDOA location under different moving states of the target is derived theoretically, the objective function of the track optimization is obtained, and the track of the UAV swarm is optimized in real time. The simulation results show that the track optimization effectively improves the accuracy of the target position and velocity estimation.

High-Precision Time Delay Estimation Based on Closed-Form Offset Compensation

To improve the estimation accuracy,a novel time delay estimation(TDE)method based on the closed-form offset compensation is proposed.Firstly,we use the generalized cross-correlation with phase transform(GCC-PHAT)method to obtain the initial TDE.Secondly,a signal model using normalized cross spectrum is established,and the noise subspace is extracted by eigenvalue decomposition(EVD)of covariance matrix.Using the orthogonal relation between the steering vector and the noise subspace,the first-order Taylor expansion is carried out on the steering vector reconstructed by the initial TDE.Finally,the offsets are compensated via simple least squares(LS).Compared to other state-of-the-art methods,the proposed method significantly reduces the computational complexity and achieves better estimation performance.Experiments on both simulation and real-world data verify the efficiency of the proposed approach.

未知信号传播速度的TDOA定位方法研究

研究了未知信号传播速度时的到达时间差(Time-Difference-Of-Arrival,TDOA)定位问题,提出两种联合估计信号传播速度和目标位置的定位方法。第一种方法为两步加权最小二乘方法。在该方法中,首先不考虑变量之间关系,得到一个关于未知变量的初始加权最小二乘估计。为改进第一步估计的性能,第二步考虑第一步估计中变量之间的关系,将其转换为一个标准的广义信赖域子问题,最终获得更高精度的估计性能。第二种方法为半正定松弛方法,通过构建非线性非凸加权最小二乘问题,然后利用半正定松弛技术将其松弛为凸的半正定规划问题,容易求解。仿真结果表明,所提两种方法均能够在高斯噪声下,且噪声不太大时达到克拉美-罗界。

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。

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。

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.

Novel method for radial velocity difference estimation of moving targets with wideband signals

For the frequency difference of arrival （FDOA） esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve a high accuracy due to the mismatch between the sampling period and the pulse repetition interval. The proposed algorithm firstly estimates the point-in-time that each pulse arrives at two receivers accurately. Secondly two time of arrival （TOA） sequences are subtracted. And final y the radial ve-locity difference of a target relative to two stations with the least square method is estimated. This algorithm only needs accurate estimation of the time delay between pulses and is not influenced by parameters such as frequency and modulation mode. It avoids transmitting a large amount of data between two stations in real time. Simulation results corroborate that the performance is bet-ter than the arithmetic average of the Cramer-Rao lower bound （CRLB） for monopulse under suitable conditions.

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。

TDOA estimation of dual-satellites interference localization based on blind separation

The time difference of arrival(TDOA)estimation plays a crucial role in the accurate localization of the satellite interference source.In the dual-satellites interference source localization system,the target signal from the adjacent satellite is likely to be interfered by the normal communication signal with the same frequency.Therefore,the signal to noise ratio(SNR)of the target signal would become too low,and the TDOA estimation through cross-correlation processing would be unreliable or even unattainable.This paper proposes a technique based on blind separation to solve the co-channel interference problem,where separation of the mixed signal can be carried out by the particle filter(PF)algorithm.The experimental results show that the proposed method could achieve more accurate TDOA estimation.The measured data obtained by using the software radio platform at 915 MHz and 2 GHz respectively verify the effectiveness of the proposed method.

TDOA and track optimization of UAV swarm based on D-optimality

To solve the problem of time difference of arrival(TDOA)positioning and tracking of targets by the unmanned aerial vehicles(UAV)swarm in future air combat,this paper adopts the TDOA positioning method and uses time difference sensors of the UAV swarm to locate target radiation sources.Firstly,a TDOA model for the target is set up for the UAV swarm under the condition that the error variance varies with the received signal-to-noise ratio.The accuracy of the positioning error is analyzed by geometric dilution of precision(GDOP).The D-optimality criterion of the positioning model is theoretically derived.The target is positioned and settled,and the maximum value of the Fisher information matrix determinant is used as the optimization objective function to optimize the track of the UAV in real time.Simulation results show that the track optimization improves the positioning accuracy and stability of the UAV swarm to the target.

TDOA Localization Algorithm with Compensation of Clock Offset for Wireless Sensor Networks

This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.

Aviation multi-station collaborative detecting based on time-frequency correlation of data-link

As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.

基于TDOA的无人机集群协同单目标定位

无源定位作为现代信息化战场中电子侦察的重要技术,可以在自身不辐射电磁波的情况下实现对敌方目标的精确定位。以高灵活性、高安全性的无人机(unmanned aerial vehicle,UAV)集群为接收站,研究基于到达时差测量的辐射源定位方法。作为高机动平台,UAV集群的位置误差更大,基于该情况对Chan算法、Taylor算法进行改进,并提出了一种粒子群泰勒协同的解算方法。与其他方法的定位结果进行对比,仿真结果表明所提的方法定位精度接近克拉美罗下界(Cramer-Rao lower bound,CRLB),解决了Taylor算法的初值问题。

布局方式对TDOA室内定位精度影响分析

针对到达时间差(TDOA)室内定位方法存在多基站布局方式对定位精度的影响问题,基于TDOA的几何精度因子(GDOP)方法仿真分析不同布局方式、主基线长度及基站高度对室内定位精度的影响。在三维多基站条件下,对正方形、圆形、蜂窝形布局方式进行仿真。得出不同的布局方式下的GDOP的分布图,仿真分析得出正方形布局方式室内定位精度最高,并以正方形布局为例,仿真分析不同主基线和高度下的GDOP分布图,得出最合理的布局方式,为实际室内定位应用中多基站布局提供了理论参考。

适用于声源定位的气体绝缘输电线路超声导波传播特性研究

基于到达时间差(TDOA)的声源定位方法是当前气体绝缘输电线路(GIL)故障定位的主要方式,声波在GIL结构上的传输特性深刻影响着定位结果的准确性。为进一步提升故障定位精度,该文提出了考虑导波频散与多模态特性的GIL壳体声传输分析模型,以典型220 kV GIL管段为研究对象,建立声波传输有限元模型,研究了导波特性对故障定位的影响,确定了适用于故障定位的超声导波模态以及GIL非直管结构对该模态导波的衰减与时延量,通过现场定位试验验证了分析模型的可行性,为GIL声源故障定位系统的传感器配置与定位阈值设置提供了计算依据。结果表明,在20~60 kHz频带内,F(1,1)模态导波具有能量高、波形形状稳定、抗干扰能力强等特点,使用该模态导波进行故障定位精度较高。GIL非直管结构会对F(1,1)模态导波造成较大的幅值衰减与一定程度的时延,在故障定位中考虑非直管结构衰减与时延影响可以使定位误差降低60%以上。

基于短基线传感器网络的远场声源TDoA定位组合算法

针对远场声源定位问题,提出到达时间差(TDoA)定位的短基线传感器网络方案.通常有一类定位算法无需估计初始点,而另一类算法则依赖初始估计值,提出将这2类方法相结合,设计出几种组合定位算法.主要思想是扬长避短,由第1类定位算法实现粗定位和输出初始估计位置,将其作为初始点输入给定位精度高和依赖初始值的第2类算法.提出利用蒙特卡洛法和简化的几何配置案例,计算定位算法的概率误差圆,论证了这种性能评估准则的可行性.通过对组合算法的概率误差圆进行数值分析,得出球形插值法与最小二乘方程差法的有机组合具有最优性能的结论,并分析了这种组合算法的盒图特性.根据不同的距离和声程差标准偏差进行模拟,以及采用野外真实场景下获得的声源数据进行试验,验证了结论.

基于TOA和TDOA的三维无源目标定位方法

提出了一种基于到达时间(time of arrival,TOA)和到达时间差(time difference of arrival,TDOA)的空中运动平台对目标高精度三维定位的无源定位方法。该方法使用3个辅站信号到空中运动平台的TOA以及辅站位置确定空中运动平台自身的位置,然后依据目标散射回波到达各个辅站与空中运动平台的TDOA确定目标的位置。分析了三维TDOA目标定位模糊产生的原因,提出了一种无模糊的高精度TDOA目标位置求解算法。仿真结果表明,该算法比经典的TDOA定位算法精度高,而且不存在定位模糊,从而验证了该空中运动平台对目标进行无源定位方法的有效性以及正确性。