基于多星时差定位精度分析

利用矩阵理论和统计信号处理理论,推导了由于时差、卫星自定位和卫星速度等测量误差产生定位误差几何稀度(GDOP)公式。并以四星为例,在地固坐标系模型下给出了仿真结果。仿真表明:地球约束能显著提升定位精度;卫星自定位误差为10m时对卫星的定位精度影响较大。     

无线传感器网络中一种改进的分布式加权多维尺度定位算法

本文在无线传感器网络单跳定位误差分析的基础上,分析了多跳节点定位误差的特性,并据此提出针对分布式加权多维尺度定位(Distributed Weighted Multidimensional Scaling,dwMDS)的权值优化算法.在无法获知参考点确切误差的情况下,利用分析出来的克拉美劳下限代替参考点误差并与距离测量误差合并,更准确的反映了多跳定位中的点与点之间的误差,从而有助于设计更优化的权值.仿真结果表明,使用优化权值改进的算法得到的节点定位误差明显减小.     

双向DFT对称补偿测相法

为提高给定数据长度下的相位估计精度,该文提出双向DFT对称补偿测相法。该方法对样本做前向和后向两次DFT变换,再从前、后DFT谱的对称峰值谱位置做谱综合而提取出中心样点的精确相位信息。基于此,推导出了相位估计方差的闭合理论表达式,仿真实验验证了该表达式的正确性,并且证明了该文方法的相位估计方差处于全相位FFT(apFFT)估计法和两参数克拉美罗限(CRLB)之间。该文方法测相精度高,具有广泛应用前景。     

On the Cramer-Rao lower bound for RSS-based positioning in wireless cellular networks

An accurate position of a mobile user's location is substantial in wireless cellular networks with respect to location based services (LBS) implementation. Among the available parameters used to estimate a desired location, low cost measurement of received signal strength (RSS) makes it suitable for outdoor and indoor positioning. Our aim here is to look at the performance of a theoretically optimal user's position estimator. We examine the Cramer-Rao lower bound (CRLB), which sets the lowest variance of any unbiased estimator. Due to the oversimplification with respect to reliance on detailed cognizance of environment, we deploy theoretical free-space and empirical COST-231-Hata, Stanford University Interim (SUI) and ECC-33 path loss models that are dominantly used in real scenarios aiming to form the system model equations. The findings show that the CRLB on estimation precision depends on the underlying path loss exponents (PLE) and the relative positions of the mobile and base stations. The calculated bounds provide a benchmark against which it is possible to evaluate different positioning algorithms, techniques and estimators relying on the specified path loss models.     

Efficient closed-form solution for target localization using TDOA measurements in the presence of sensor position errors

An efficient solution for locating a target was proposed, which by using time difference of arrival (TDOA) measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares (TSWLS) method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares (WLS). The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound (CRLB) easily and effectively improve the localization accuracy.     

改进的基于能量的声源定位算法

为提高基于能量的两步加权最小二乘声源定位算法（two‐step WLS）的定位精度,提出一种改进算法。通过引入广义矩阵,将有噪数据中的噪声项分离出来作为约束条件,将加权最小二乘问题转化为带约束条件的最小化代价函数的求解问题,采用拉格朗日乘子法求得代数解。仿真结果表明,该算法在噪声较小时,逼近CRLB （Cramer‐Rao lower bound）下限;高噪声时,相对two‐step WLS算法,提高了定位精度,提高了突然偏离CRLB的噪声阈值,是一种高效可行的定位算法。     

中继收发器辅助的单站目标定位算法

现有无源定位闭式算法均考虑视距（Line of Sight, LOS）环境,无法直接应用于存在遮挡的城市环境低空无人机目标定位等场景,同时,非视距（Non?Line of Sight, NLOS）优化定位算法计算效率较低。针对这些问题,本文开展中继辅助下的单站目标定位研究,通过引入中继收发器对目标信号进行转发,构造两条路径从而规避遮挡问题,同时考虑中继和观测站位置存在随机误差,提出了一种闭式算法来确定未知目标位置。该算法分为3个步骤：首先利用校准目标-中继收发器-观测站这一路径的额外信息,修正中继和观测站位置;随后基于未知目标-中继收发器-观测站获取的观测信息,通过引入额外变量的方式构建伪线性方程,利用加权最小二乘技术给出目标位置粗略估计;最后进一步挖掘目标位置与额外变量的非线性关系,再次构建矩阵方程并给出目标位置最终估计解。经过理论剖析与仿真验证,所提出的算法在可接受的测量误差和观测站点位置误差范围内,能够逼近克拉美罗下界（Cramer?Rao Lower Bound, CRLB）。     

低信噪比场景下Link-16系统的联合频偏估计算法

对于Link-16数据链终端平台在低信噪比(SNR)高动态场景下的多普勒频率偏移问题,该文设计一种新的数据结构,推导了该结构下的克拉默-拉奥下界(CRLB),并在此基础上提出一种联合频域变换与时域自相关运算的分步式频偏估计算法。其基本思想是,首先对接收信号做自相关处理,然后通过频域变换进行最大值索引,结合修正因子得到多普勒频移的粗估计值,再利用时域的改进L&;R算法对接收信号进行细估计,根据两步估计算法得到最终的频偏估计值。算法应用蒙特卡罗实验仿真,仿真结果表明,与传统频偏估计算法相比,该算法的归一化均方误差更接近CRLB,在多普勒频偏为[–20 kHz, 20 kHz]时,估计精度可达10^–5。在低信噪比环境下,所提算法能达到较为理想的估计效果,适用于Link-16数据链通信。     

Improved taylor-series location algorithm for cooperation networks

This article presents an iterative algorithm for estimating the location of the destination mobile station (DS) when some extra mobile stations around the DS are involved in and assist the base stations to complete the localization process. The proposed method is based on the taylor-series (TS) method and jointly estimates both the DS and the extra mobile stations, named reference mobile station (RS) in this article, positions simultaneously. Moreover, the time-differential-of-arrival (TDOA) measurements between DS and pairs of RSs are obtained by ultra-wide-band (UWB) signal, which is adept in accurate ranging application. According to the theoretic analysis, the Cramér-Rao lower bound (CRLB) of the modified TS algorithm reduces significantly. The actual performance, under a given simulation scenario, is enhanced by 25% at best.