宽带频率步进信号参数估计的克拉美罗界研究

随着宽带雷达技术的发展,经典窄带信号参数估计的克拉美罗(CR)界已经不能再作为参数估计算法的评估标准。该文以宽带频率步进雷达为应用背景,首先推导了宽带频率步进信号参数估计的CR界,给出了Fisher信息阵元的闭合表达式。然后深入揭示了宽带CR界的特性,证明了频率步进信号参数估计的性能不仅与信号带宽、信噪比有关,还会受到相对带宽的影响。最后验证了窄带CR界只是宽带CR界的一个特例,宽带CR界综合考虑了宽带模型下各种因素的影响,在理论分析中有更加全面的指导意义。     

LFM信号参数估计的牛顿迭代方法初始值研究

 本文研究了LFM信号参数估计的牛顿迭代方法的初始值问题,用计算量较小的DPT算法得到LFM信号中心频率和调频系数的估计值,以此作为牛顿迭代的初始值.性能分析表明,在DPT算法信噪比门限以上时,用本算法得到的中心频率和调频系数的估计值在牛顿迭代所需收敛域范围之内,保证牛顿迭代的收敛性.仿真结果表明,在信噪比门限以上时,用本文提出的方法所得参数估计的均方根误差达到克拉美-罗限.本算法计算量小,有利于LFM信号参数估计的准实时处理.     

Environmental-adaptive indoor radio path loss model for wireless sensor networks localization

In the received signal strength indicator (RSSI) based indoor wireless sensor networks localization system, RSSI measurements are very susceptible to multipath fading, anisotropy of antenna, low supply voltage of node and so on, which will cause the system failure to achieve a high location accuracy. This paper presents an environmental-adaptive path loss model. In the process of localization, the calibrated coefficient LSV of low supply voltage, which can be determined by monitoring the supply voltage of the sender, is used to calibrate ranging errors caused by its low supply voltage. The blind node utilizes the absolute value of RSSI to generate the phase of the corresponding receiver's location so as to determine the correction coefficient of indoor multipath fading R_i. Furthermore, in order to improve the accuracy of RSSI measurements, we also take full consideration of the effect of antenna to accurately determine the corresponding path loss model of the two communication nodes. The proposed path loss model is suitable for the majority of wireless location systems that are on the basis of RSSI-based ranging techniques. Experiment results show that the estimation accuracy and adaptability of the proposed path loss model are significantly higher than that of the traditional one.     

Cramer-Rao Bounds for parameter estimation of phase-coding signals

In this paper, Cramer-Rao Bound (CRB) is derived from phase-coding signal with additive white noise, where three important parameters are focused on: carrier frequency, chip width and amplitude. Simplified and close form expressions of CRB are obtained through complicated derivation, and then are applied to evaluate the performance of the cyclic estimator. The results are accurate enough and serve well as benchmark for evaluating the performance of parameter estimation method. Numerical simulations illustrate the accuracy and applicability of the derived CRB.     

A New Coherent Integration Method for Frequency Jittering Radar

For the frequency jittering radar,the problems of range migration and phase jittering among different pulses may occur during the long-time integration,which will affect the target energy integration.Therefore,a new coherent integration algorithm,namely,Frequency jittering based Radon-Fourier transform (FJ-RFT),is proposed.Based on jointly searching in the motion parameter space,the problems mentioned above can be simultaneously resolved and the coherent integration can be then realized.The Cramer-Rao lower bound (CRLB) and the Blind speed sidelobes (BSSL) of the proposed FJ-RFT are analyzed in detail.Finally,numerical experiments are provided to demonstrate the effectiveness of the proposed method.     

Cramer-Rao bounds of the frequency estimation in the time selective radio channels with Doppler spread

The mobile channel is slow fading and time selective, thus the multiplicative and additive noise of the channel will smear the spectral line, or arouse Doppler spread. This spread will make the parameters estimation accuracy degrade. The goal of this paper is to analytically assess this degradation when Carrier Frequency Offset （CFO） and Doppler shift exist jointly. Then the finite-sample Cramer-Rao Lower Bound （CRLB） is derived and close-form asymptotical expression is given for large-sample CRLB. These expressions give insights into the performance room for frequency estimation. Also the variance of Doppler shift estimator is simulated to illustrate the theoretical results.     

Estimating distances via connectivity in wireless sensor networks

Distance estimation is vital for localization and many other applications in wireless sensor networks. In this paper, we develop a method that employs a maximum‐likelihood estimator to estimate distances between a pair of neighboring nodes in a static wireless sensor network using their local connectivity information, namely the numbers of their common and non‐common one‐hop neighbors. We present the distance estimation method under a generic channel model, including the unit disk (communication) model and the more realistic log‐normal (shadowing) model as special cases. Under the log‐normal model, we investigate the impact of the log‐normal model uncertainty; we numerically evaluate the bias and standard deviation associated with our method, which show that for long distances our method outperforms the method based on received signal strength; and we provide a Cramér–Rao lower bound analysis for the problem of estimating distances via connectivity and derive helpful guidelines for implementing our method. Finally, on implementing the proposed method on the basis of measurement data from a realistic environment and applying it in connectivity‐based sensor localization, the advantages of the proposed method are confirmed. Copyright © 2012 John Wiley & Sons, Ltd.     

一种单自旋回波串信号参数估计方法

针对存在加性高斯白噪声多参数变量的单自旋回波串信号参数估计问题,提出一种参数分离化的2-D参数估计方法.利用2-D数据矩阵秩为1的特性,依照迭代加权最小二乘方法,从左、右主奇异值向量中以参数分离的方式分别估计出衰减因子和频率,基于最小二乘方法进一步获得信号幅度估计.该方法在相对高信噪比和/或大数据样本下可达到克拉美罗下界,且计算复杂度较低.仿真数据结果证明了算法的有效性.     

MIMO雷达GMTI性能及DOA估计的克拉美·罗界分析

研究了MIMO雷达GMTI 性能及其DOA估计的克拉美·罗界(CRB)。首先建立机载平台下MIMO雷达信号模型,通过对系统参数设置,可使MIMO雷达工作在3种不同模式中。接着分析了MIMO雷达GMTI性能,并推导出了在MIMO雷达空时信号模型下,利用空时联合域信息时DOA估计的CRB。仿真结果表明,无论是GMTI性能还是DOA估计性能,MIMO雷达均优于相控阵雷达,尤其是发射稀疏阵MIMO雷达性能最佳。同时,利用空时联合域信息能有效改善MIMO雷达DOA估计的CRB,在目标多普勒频率相差较大时效果更加明显。     

Fundamental limits and improved algorithms for linear least‐squares wireless position estimation

In this paper, theoretical lower bounds on performance of linear least‐squares (LLS) position estimators are obtained, and performance differences between LLS and nonlinear least‐squares (NLS) position estimators are quantified. In addition, two techniques are proposed in order to improve the performance of the LLS approach. First, a reference selection algorithm is proposed to optimally select the measurement that is used for linearizing the other measurements in an LLS estimator. Then, a maximum likelihood approach is proposed, which takes correlations between different measurements into account in order to reduce average position estimation errors. Simulations are performed to evaluate the theoretical limits and to compare performance of various LLS estimators. Copyright © 2010 John Wiley & Sons, Ltd.     

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

A novel estimation scheme that combines Bayesian and lower bound estimating radio frequency identification tag population size is proposed. The developed methodology is based on the fusion between the Bayesian and lower bound estimating techniques. It turns out that the fusion rule is built up thanks to an existing linear relationship between the cited techniques. Simulation results show that the developed technique significantly improves the accuracy of the estimating tag quantity and presents less estimation error. Also, the resulting advanced dynamic framed slotted ALOHA protocol considerably improves the performance and efficiency of the radio frequency identification anti‐collision compared with the most recent protocols using others estimating methods.     

A novel link adaptation scheme to enhance performance of IEEE 802.11g wireless LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.     

基于尺度变换的宽带线性调频信号时差/尺度差估计算法

提出了一种基于尺度变换的宽带线性调频信号时差和尺度差的快速算法.根据两路接收到的线性调频信号间调频率之比为尺度差的平方的特点,利用分数阶傅里叶变换分别估计出两路信号的调频率,即可获得尺度差的估计.将估计的尺度差对一路信号进行伸缩,并计算伸缩后信号与另一接收信号的时域相关,根据相关峰的位置估计出时差.相比于传统基于宽带互模糊函数的方法,该方法避免了二维搜索宽带互模糊函数的峰值,只需若干次快速傅里叶变换即可实现,能够显著降低运算量.仿真结果显示该方法在高信噪比下逐渐接近克拉美-罗下界.     

伽利略搜救信号FOA和TOA估计的克拉美-罗界

该文考虑信息位宽的不确定性,研究了单个伽利略搜救信号FOA(Frequency Of Arrival)和TOA(Time Of Arrival)估计的克拉美-罗界(CRB)。推导了伽利略搜救信号Fisher信息矩阵元素的计算表达式,利用单位冲激函数的性质和Parseval定理,将单位冲激函数的平方和转换到频域进行计算,得到了FOA和TOA估计的CRB的解析结果。数值分析,Monte Carlo仿真及实测结果表明,上述CRB具有有效性,可以用于评估上述参数估计算法的性能。     

运动双基地MIMO雷达参数估计的克拉美罗界

在杂波环境下,该文研究了目标、发射站及接收站均运动时双基地多输入多输出(MIMO)雷达参数估计的克拉美罗界(CRB)。首先建立了运动双基地MIMO雷达的数学模型,推导了杂波背景下多目标参数估计CRB的一般表示式,然后给出了无杂波时单目标波离方向(DOD)、波达方向(DOA)以及速度CRB的闭式解,并分析了各参数对CRB性能的影响。理论与仿真实验表明：无杂波时的参数估计性能优于杂波背景下的参数估计性能;目标DOD(DOA)的估计性能与收发站速度、目标速度无关,而目标速度的估计性能将随着收、发站和目标速度的增大而下降。     

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。     

Systematic Tracking of the Random Movement of a Mobile in Cellular Mobile Network

In wireless networks we evaluate the distance of a mobile from its base station and from other base stations in some neighboring cells to estimate a channel and also to measure interference caused by a co-channel. In this paper a systematic tracking of the random movement of a mobile is presented. In this work we find the position of any mobile at any point of time within its complete call duration. Using this model not only we can locate the mobile but also can find the distance of any mobile from the base station of the same cell and also when they belong to different cells. Such a model seems to be very promising in giving a platform to study the performance of HCA/FLCA and DCA like advanced channel allocation techniques. H. K. Pati received his MCA degree from UCE. Burla, under Sambalpur University, India, in 1998. Then he received his ME degree in computer science and engineering from REC Rourkela, India (now named as NIT Rourkela, India) in 2000. Since 2000 he has been working as a PhD student in the CSE Department IIT Kharagpur, India. Since September 2005 he is also associated with the Department of Computer Science, Trinity College, University of Dublin, Dublin 2, Ireland as a research staff (Postdoctoral research fellow). His current research focus is on quality of service provisioning in personal wireless communications.     

Joint Carrier-Frequency Offset and Channel Estimation for MIMO-OFDM Transmission

In this paper, we consider a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system operating over frequency-selective fading channels. We propose a novel scheme for joint carrier-frequency offset (CFO) and channel estimation based on the expectation–maximization (EM) algorithm. Furthermore, the Cramer-Rao bounds (CRBs) for both CFO and channel estimators are exploited to evaluate the performance of the proposed scheme. Computer simulations show that the proposed algorithm achieves almost ideal performance compared with the CRBs for both channel and frequency offset estimations.

基于STFAP的MIMO雷达运动目标参数估计的CRB研究

多发多收(Multiple-Input Multiple-Output, MIMO)雷达在目标检测、参数估计等方面具有显著优势。目标参数估值的CRB被证明是系统设计和空时自适应处理(STAP)性能分析中的有力工具。该文针对采用频分正交信号的共置天线MIMO雷达,首先建立基于MIMO雷达的目标和杂波空-时-频信号模型;在此基础上,研究基于空-时-频自适应处理(STFAP)的MIMO雷达地面运动目标角度和多普勒参数最大似然估值的克拉美-罗界(CRB);最后通过CRB性能仿真分析验证了MIMO雷达STFAP有效消除动目标检测盲速,提高目标参数估计精度的优势。