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.

Study on the Influence of Airgun Excitation Conditions on Airgun Signals and Travel Time Variation Measurements

Because of the different excitation conditions of the airgun source,there will be subtle differences in airgun signals.Travel time variation of airgun signals often mix into source information which can’t fully reflect the evolution of the medium.This article uses the airgun signals from the Binchuan Transmitting Seismic Station to analyze the airgun signal′s characteristics of phase and correlation.We conducted a comparative analysis of the effects of the pair difference method and the deconvolution method on eliminating the influence of the excitation conditions in travel time variation.The results show that:(1)The pressure pulse and its subsequent wave of airgun source wavelet are less affected by excitation conditions that we can use it to obtain high-precision excitation moments.(2)Deconvolution can improve the correlation of the airgun signal.(3)The pair difference method can’t eliminate the influence of excitation conditions in travel time variation.Deconvolution can reduce excitation condition interference and the influence of the excitation condition in the travel time variation after deconvolution of the vertical signal is significantly reduced.

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.

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.

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.

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.

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.

OFDM系统中基于BP神经网络的定位算法

为了减小正交频分复用(OFDM)系统中多径干扰对定位精度的影响,提出一种基于后向传播(BP)神经网络的定位算法。该算法采用多重信号分类(MUSIC)算法估计OFDM信号首径的到达时间(TOA),再计算出到达时间差(TDOA),然后利用BP神经网络对其进行修正,最后使用Chan算法确定移动台的位置。在多径环境下对算法进行仿真,仿真结果表明该算法能够有效地降低多径干扰的影响,性能优于最小二乘(LS)算法、Chan算法和泰勒算法。

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.

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。

Passive Localization of Signal Source Based on UAVs in Complex Environment

For the influence caused by multipath fading and non-line-of-sight(NLOS)transmission,it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network(WSN)on the ground.In this paper,we establish a special WSN in the sky to address this challenge,where each sensor is loaded on an unmanned aerial vehicle(UAV)and the operation center of all the UAVs is fixed on the ground.Based on the analyzing of the optimal distribution and the position error calibration of all the sensors,we formulate the localization scheme to estimate the position of the target source,which combines the time difference of arrival(TDOA)method and the frequency difference of arrival(FDOA)method.Then by employing the semidefinite programming approach,we accurately obtain the position and velocity of the signal source.In the simulation,the validity of the proposed method is verified through the performance comparison.

Adaptive Cascaded High-Resolution Source Localization Based on Collaboration of Multi-UAVs

Effective information fusion is very important in hybrid source localization. In this paper, the performance analysis of conventional joint direction of arrival(DOA) and time difference of arrival(TDOA) system is derived and it is shown that this hybrid system may inferior to the single system when the ratio of angular measurements error to distance measurements error exceeds a threshold. To avoid this problem, an effective DOA/TDOA adaptive cascaded(DTAC) technique is presented. The rotation feature of UAVs and spatial filtering technique are applied to gain the signal-to-noise ratio(SNR), which leads to more accurate estimation of time delay by using DOAs. Nevertheless, the time delay estimation precision is still limited by the sampling frequency, which is constrained by the finite load of UAV. To break through the limitation, an enhanced self-delay-compensation(SDC) method is proposed, which aims at detecting the overlooked time delay within the sampling interval by adding a tiny time delay. Finally, the position of the source is estimated by the Chan algorithm. Compared to DOA-only algorithm, TDOA-only algorithm and joint DOA/TDOA(JDT) algorithm, the proposed method shows better localization accuracy regardless of different SNRs and sampling frequencies. Numerical simulations are presented to validate the effectiveness and robustness of the proposed algorithm.

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.

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.

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.

基于UWB的PDOA与TOF煤矿井下联合定位方法

煤矿井下人员和车辆精确定位是煤矿安全高效生产的重要保障。目前矿井人员和车辆精确定位主要采用超宽带(UWB)无线通信技术,其中仅采用飞行时间(TOF)的定位方法需2个定位分站或天线联合测距和定向,存在天线间距大、不便于安装维护、定位误差大等问题。针对上述问题,提出了应用于煤矿巷道一维定位场景的基于UWB的到达相位差(PDOA)与TOF煤矿井下联合定位方法。该方法通过TOF测量定位卡与定位分站之间的距离,通过PDOA判断定位卡的方位,再根据测得的定位卡与定位分站之间的距离和方位,对定位卡进行定位。该方法根据从定位卡发送的无线电信号到达定位分站的2根天线的相位差判断定位卡的到达角度(AOA),不需要很大的天线间距即可确定定位卡的方位,缩短了定位分站的2根天线之间的距离,可将2根天线一体化,便于安装维护,提高了定位精度。煤矿井下测试结果表明,该方法定位精度在15 cm以内;在200 m测试距离范围内,定位精度不受距离远近影响;TOF测距数值稳定在相对其均值±10 cm的范围内,具有很好的稳定性。

Theoretical research on intensity envelope function of strong ground motion

After the time history of seismic motion is represented by superposition of a series of narrow frequency band wave groups, we obtain a general relation between wave group arrival time and derivative of phase spectra in the paper. On the basis of the relation, frequency number distribution function of wave group arrival time is completely equivalent to that of phase difference spectra. Under the assumption that phase angles of seismic motionobey uniform distribution ranged from 0 to ─ 2π, a quantitative relation between intensity envelope function of seismic motion and energy distribution function with wave group arrival time has been derived in this paper. The relation illuminates inner links among Fourier amplitude spectra and derivative of phase spectra and intensity envelope function. Some examples given by the paper support the conclusions mentioned above.

OFDM子载波相位差TOA测距方法的抗多径性能

目前,大量物联网终端都具有Wi-Fi或蜂窝网接入能力。Wi-Fi网络或蜂窝网提供通信功能的同时确定终端在室内的位置的研究得到学术界以及工业界的重视。但是,高精度定位通常需要高精度测距的支持,而受制于严重的多径反射,室内的测距精度有限。而目前广泛部署的Wi-Fi和蜂窝网均使用正交频分复用(OFDM)信号,其用于测距时的抗多径能力却没有得到系统研究。所以,文章首先分析研究了基于相邻子载波相位差的到达时间(TOA)测距方法,然后采用室内环境的IEEE 802.11信道模型,对基于Zadoff-Chu导频序列的相位差方法的性能进行了计算机仿真,验证了该方法具有线性拟合方法所不具有的抗多径能力。然后,我们使用WARP软件无线电平台在两种实际室内环境中进行相邻子载波相位差方法的测距实验。结果表明在带宽为20 MHz及测量范围为2-7米的情况下,该方法的平均TOA估计精度分别达到0.4米和0.49米,显示了较强的抗多径能力,表明该方法在室内定位中具有较大的应用潜力。

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.

基于免疫选择和自适应权重的鲸鱼优化定位算法

针对鲸鱼优化算法(WOA)在到达时间差和到达角度混合定位中存在后期迭代种群多样性减小,容易导致局部最优、定位精确度降低的问题,提出一种基于免疫选择和自适应权重的鲸鱼优化算法(IM-WOA).由最大似然估计法得到目标定位函数,为丰富种群多样性引入免疫机制,能够有效产生新的个体,从而避免种群陷入局部最优.通过将自适应惯性权重应用于个体位置的更新公式,实现算法全局探索能力和局部开发能力的平衡和协调,对经典基准函数和目标定位函数进行求解.结果表明,与WOA、AWOA、CSSOA、PIO、CASSA算法相比,IM-WOA算法对绝大多数基准函数的求解具有更高的精度、稳定性和定位精度.