基于角度约束采样的单站无源定位混合粒子滤波算法

为实现固定单站对运动辐射源的快速定位,该文给出了一种基于角度约束采样的混合粒子滤波算法。该算法从EKF(Extended Kalman Filter)滤波得到建议分布,利用角度测量对状态变量的约束关系从建议分布产生所需粒子,可以减少粒子滤波用于高维情况时所需的粒子数目,改善滤波性能,降低运算成本。结合利用多普勒变化率和角度测量的单站定位方法,与EKF,UKF(Unscented Kalman Filter)以及一般混合粒子滤波算法的仿真比较表明,该算法在滤波收敛速度、跟踪精度以及稳定性方面优于其它算法,估计误差更接近Cramer-Rao下界。     

基于角度约束采样的单站无源定位混合粒子滤波算法

为实现固定单站对运动辐射源的快速定位,该文给出了一种基于角度约束采样的混合粒子滤波算法。该算法从EKF（Extended Kalman Filter）滤波得到建议分布,利用角度测量对状态变量的约束关系从建议分布产生所需粒子,可以减少粒子滤波用于高维情况时所需的粒子数目,改善滤波性能,降低运算成本。结合利用多普勒变化率和角度测量的单站定位方法,与EKF,UKF（Unscented Kalman Filter）以及一般混合粒子滤波算法的仿真比较表明,该算法在滤波收敛速度、跟踪精度以及稳定性方面优于其它算法,估计误差更接近Cramer—Rao下界。     

基于粒子滤波的机载单站无源跟踪算法

针对空中观测平台对远距离海面慢速运动目标定位跟踪这一非线性估计问题,介绍了专门处理非线性估计问题的粒子滤波算法,将粒子滤波算法(Particle Filter,PF)应用于机载单站无源定位跟踪问题,有效提高了对慢速运动目标的单站无源定位跟踪性能,解决了传统的扩展卡尔曼滤波算法在非线性估计时存在收敛速度慢的问题。通过与扩展卡尔曼滤波算法的仿真比较表明,粒子滤波算法可实现对慢速运动目标的高精度定位跟踪,且性能优于扩展卡尔曼滤波算法。     

基于UT的混合粒子滤波单站无源定位算法

为利用无源固定单站对运动辐射源快速定位,将粒子滤波和UT(unscented transformation)应用于单站无源定位,给出了一种基于UT的角度约束采样混合粒子滤波无源定位算法,该算法从UKF滤波得到建议分布,从该建议分布采样时引入角度测量对状态变量的约束,可以减少粒子滤波用于高维情况时所需的粒子数目,改善滤波性能.与EKF、UKF(unscented kalman filter)以及基于EKF的混合粒子滤波算法的仿真比较表明,本文算法在滤波收敛速度、跟踪精度以及稳定性方面优于其它算法,估计误差可以接近Cramer-Rao下界.     

一种改进的EKPF算法在固定单站无源定位中的应用

本文针对EKPF算法在固定单站无源定位目标跟踪的应用中运算量大、实时性差的问题,通过对部分粒子进行EKF采样,将EKPF算法进行改进,改进的EKPF算法不仅有效降低了运算量,同时增加了粒子的多样性,使粒子集更能体现概率密度函数的真实分布。Matlab仿真表明,与传统的EKPF算法相比,改进算法在保证滤波性能基本不变的前提下,算法运算量大幅下降。     

一种基于EPF滤波的三维单站无源定位算法研究

利用频率变化率、方位角及俯仰角信息,提出一种对固定辐射源的三维单站无源定位算法。该方法通过质点运动学原理,得出目标辐射源的位置,之后采用EPF滤波算法进行处理,对粗略定位结果进行修正和平滑,逐步估计出目标的位置。EPF（ExtendedParticleFilter）滤波是将EKF（ExtendedKalmanFilter）算法作为重要性函数的一种粒子滤波方法。仿真结果表明,基于EPF滤波的单站无源定位算法比传统的EKF滤波算法收敛更快、更稳定,滤波效果更好,定位精度更高,这对无源定位跟踪算法精度的提高和实际应用有很大的意义。     

单站被动目标的多假设距离粒子滤波跟踪

针对单站被动目标跟踪的无距离信息,多假设距离粒子滤波方法利用多个粒子滤波的并行运算,对不同初始距离的粒子滤波器进行计算,利用各子滤波的残差概率对并行处理的粒子滤波运算进行自适应采样实现单站纯方位目标跟踪,并与粒子滤波、多假设距离滤波方法进行比较,仿真结果表明该算法收敛速度快,跟踪精度高。     

基于粒子滤波的单站无源定位跟踪新算法研究

针对单站无源定位跟踪系统非线性较强、传统跟踪滤波方法收敛速度、慢容易发散的问题,提出了一种新的跟踪滤波算法P-EKF。该方法采用粒子滤波的思想对目标实现初始的捕捉,然后通过扩展卡尔曼滤波方法对目标进行跟踪保持,提高了目标跟踪收敛速度和跟踪精度,而对计算资源的消耗有限。缩比仿真实验证明了该方法的可行性和有效性,具有较高的应用价值。     

一种导向粒子滤波跟踪算法

粒子滤波算法在运动目标跟踪方面有着广泛的使用,粒子滤波中的重采样是解决粒子退化的一种重要方法,但是重采样会导致粒子的多样性的丧失。针对这个问题,改进粒子滤波算法,改进过程中结合了导向滤波的基本思想,因此将这种方法称为导向粒子滤波跟踪算法。导向滤波是近几年提出的一种新的滤波方式,与传统滤波相比,它在滤波的时候会引入一幅指导图像,鉴于这个思想,我们在进行粒子滤波的时候,引入一种导向粒子作为一个指导量,来保留一些目标图像上的信息。实验证明了这种算法可以更好地对目标进行定位跟踪。     

UPF改进算法在单站无源定位中的应用

针对UPF算法在固定单站无源定位目标跟踪应用中存在运算量大、实时性差的问题,通过借鉴简化UKF的思想采用超球面单形采样策略、针对应用背景下状态模型的线性特性采用KF代替状态模型的Sigma点采样、在粒子滤波中对部分粒子间隔进行UKF采样三个方面的改进,提出一种改进的UPF算法。改进的UPF算法既有效降低了运算量,又增加了粒子的多样性,使粒子集更加逼近真实的后验概率密度函数。计算机仿真表明,改进的UPF算法在保持原有滤波精度的同时,有效减少了运算时间,可用相当于EKPF的运算效率得到UPF的滤波精度,适用于固定单站无源定位跟踪系统。     

Software‐only TDOA/RTT positioning for 3G WCDMA wireless network

A hybrid location finding technique based on time difference of arrival (TDOA) with round‐trip time (RTT) measurements is proposed for a wideband code division multiple access (WCDMA) network. In this technique, a mobile station measures timing from at least three base stations using user equipment receive—transmit (UE Rx—Tx) time difference and at least three base stations measure timing from the mobile station using RTT. The timing measurements of mobile and base stations are then combined to solve for both the location of the mobile and the synchronization offset between base stations. A software‐only geolocation system based on the above mobile/base stations timing measurements is implemented in Matlab platform and the performance of the system is investigated using large‐scale propagation models. Copyright © 2007 John Wiley & Sons, Ltd.     

小信息量下蜂窝网定位算法研究

为了实现蜂窝网中小信息量情况下对移动用户的定位,文中在只有一个基站和一台定位设备可用的条件下建立了TOA／TOA定位模型,并在该模型下提出了基于UKF算法的位置估计方法。并重点讨论了该定位模型下固有的模糊点问题的解决策略,最后给出了UKF算法在该方案下的进行定位的仿真结果并进行了讨论总结。通过仿真结果可以看出,给出的基于跟踪的UKF算法在定位精度和实时性上表现出了很好的性能。同时,该方案较传统定位对参数的要求更少,具有更广泛的应用空间。     

GSM Mobile Station Location Using Reference Stations and Artificial Neural Networks

In this paper we present a novel approach to the automatic GSM mobile station location. The approach is based on measurement of radio signal strengths from a number of the neighboring base stations (antennas) and estimation of the mobile station position using trained artificial neural network (ANN) models. First, we present an improved version of our previous positioning back propagation (BP) ANN multi-level perceptron (MLP) model that further improves positioning accuracy. Then, we extend the MLP primary ANN model by introducing correctional factors obtained from a number of reference stations with known positions. Two new models with the improved location accuracy, both aimed at real-time application, are presented. The first model is using differential range to improve the estimated location of the mobile station. The second is using small-scale secondary neural networks trained with data obtained from reference stations, in addition to the primary ANN, to correct location accuracy.     

TOA数据处理对NLOS环境下定位精度的改善

基于移动通信环境中非视距(NLOS)传播时延服从指数分布的特性,提出了一种改善移动台定位精度的波达时间(TOA)数据处理方法.NLOS传播时延是TOA测量误差的一部分,是基站与移动台距离的指数函数,具有正偏置的特性,因此TOA测量值越大其误差越大.对所有的TOA测量数据进行分析,仅保留误差最小的3个,然后再采用最小二乘(LS)法估计移动台的坐标.仿真结果表明,该TOA数据处理方法能够明显改善NLOS传播环境下的定位精度,在系统测量误差较小时对LOS传播条件下的定位精度几乎没有影响.     

一种实用无线定位算法

在移动通信系统中,利用CELLID定位的方法是最简单最快速的,但是该方法只能利用手机接收到的基站信息来确定基站位置,从而推测移动台的位置,因此误差较大,与实际路径不符。本文提供一种利用本地均值来改进该定位精确性的方法,消除毛刺。仿真结果表明,该方法显著改善了CELLID方法的误差,消除了不规则跳跃的点,使路径与真实路径更吻合。     

Hybrid TDOA/AOA mobile user location for wideband CDMA cellularsystems

This paper proposes a mobile user location scheme for wideband code-division multiple-access (CDMA) wireless communication systems. To achieve high location accuracy and low cost of the mobile receiver, the location scheme combines the time difference of arrival (TDOA) measurements from the forward link pilot signals with the angle of arrival (AOA) measurement from the reverse link pilot signal. High chip rates in wideband CDMA systems facilitate accurate TDOA measurements, and a smart antenna used at the home base station (BS) can provide accurate AOA measurement in a macrocell environment. A two-step least square location estimator is developed based on a linear form of the AOA equation in the small error region. Numerical results demonstrate that the proposed hybrid TDOA/AOA location scheme gives a much higher location accuracy than TDOA only location, when the number of base stations is small and/or when the TDOA measurements have a relatively poor accuracy     

Ranking of TOA Measurements Based on the Estimate of the NLOS Propagation Contribution in a Wireless Location System

The presence of non-line-of-sight (NLOS) propagation is a key issue that limits the accuracy of wireless location systems. The lack of direct sight causes the measurements obtained by location systems to be so unpredictable that they can produce high inaccuracies in the estimation of the mobile station location. In this paper we propose a novel technique to improve location reliability and accuracy in cases where NLOS propagation is present. For that, in registers of time of arrival (TOA) measurements taken from each base station (BS) in view, we detect the presence of NLOS propagation and estimate the ratio of the measurements coming from NLOS propagation. With this estimate we can assess how much is NLOS propagation affecting the measurements taken from each BS and then we can identify the best measurements and BSs to achieve the highest accuracies in location.     

Location estimation and trajectory prediction for cellular networks with mobile base stations

This paper provides mobility estimation and prediction for a variant of the GSM network that resembles an ad hoc wireless mobile network in which base stations and users are both mobile. We propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user's next mobile base station from the user's location, heading, and altitude, to improve connection reliability and bandwidth efficiency of the underlying system. Our analysis demonstrates that our algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.     

CDMA无线定位系统的基站选择算法

在基于CDMA网络的无线定位系统中,当移动终端处于多个基站的侦收范围时会面临定位基站的选择问题,基站选择的优化可以减少系统资源的占用,并且直接影响系统定位性能。文中提出采用精度因子的基站选择算法,通过实测验证具有较高的稳定性,并可提高系统的定位精度和实时性,对定位系统的基站架设和系统设计有实际的指导意义。     

基于移动信令数据分析的位置服务与基站定位技术的混合应用

基于移动信令数据分析的位置服务与基站定位是两种不同类型的用户位置服务.一种是即时定位业务,另一种是基于历史信令数据分析的位置业务,二者各有优劣性.提出一些将基站即时定位与基于历史轨迹、区域人群统计的移动信令数据分析位置开放能力相结合的技术方案,并详细描述了这些方案的实现方法.所述内容为电信运营商基于网络信令的位置能力与优化提供了新思路.