移动通信中一种精确的多普勒频移估计方法

该文利用有效到达径上信道参数的估计值,统计其包络的电平通过率(Level Crossing Rate,LCR),据此估计出时变多径信道的多普勒频移。同时还在理论上分析了噪声环境下LCR方法的估计偏差,进而提出了精确的改进方法,使得通信系统在各种移动速度和信噪比下都具有较高的估计精度。     

水声多径信道多普勒因子精确估计方法

由水下平台运动导致的多普勒效应是影响高数据率水声通信性能的主要因素,现有多普勒估计方法在复杂水声多径信道条件下估计精度急剧下降。针对此问题,提出了一种可自动匹配水声多径信道的精确多普勒频移估计方法。仿真结果表明：该方法可显著提高水声多径信道的多普勒频移估计精度,信道适应性强,在信噪比大于-5 dB时,估计精度始终保持在10^-4左右,满足高数据率水声通信对多普勒因子估计精度的要求。     

NGB-W系统中最大多普勒频移估计及其改进算法

针对传统最大多普勒频移估计算法在低速移动或每帧中传输OFDM符号数较少时估计误差较大的问题,本文针对NGB-W系统提出了一种基于插值的传统多普勒频移估计算法的改进算法.本文依据传统算法,对连续导频进行插值,有效提高了多普勒频移估计算法的性能.采用CCSS平台进行仿真,仿真结果表明,改进的算法与传统算法相比,在低速移动及传输OFDM符号少时表现出更好的性能.     

OFDM水声通信中最大多普勒频偏估计算法研究

在水声通信中,发射与接收端相对运动引起的多普勒频移会严重恶化OFDM系统传输效果.因此多普勒频移估计是水声通信的关键技术之一.本文采用的最大Doppler频移估计算法,是利用信道功率谱的分布对接收的导频信号进行频域差分检测来进行估计.这种方法复杂度低,精度较高,无需获得正确的信道时域冲击响应信息,也无需再对信号进行自相关运算,而且特别适用于低信噪比的水声通信系统.     

正弦波频率估计的改进Rife算法

根据Rife算法在被估计频率接近量化频率时的估计精度较差,但接近两相邻量化频率中心区域时估计精度接近克拉美—罗限的特点,本文提出改进Rife(I-Rife)算法。I-Rife算法利用频移技术和频谱细化技术使信号频率总是位于两相邻量化频率中心区域后,然后再利用Rife算法便可以获得较高的频率估计精度。I-Rife算法改进了判据,降低了频率修正方向的误判概率,使I-Rife算法在低信噪比下仍能保持较高的频率估计精度。仿真结果表明,在信噪比达到-13dB时,I-Rife算法仍保持较高的频率估计精度,而且整个频段上性能稳定。I-Rife算法计算量小,易于硬件实现,可以实时精确的进行正弦波频率估计。      

基于线型预测频谱估计的相干激光雷达功率谱分析方法EI北大核心CSCD

基于多普勒效应的相干激光雷达广泛应用于测风等大气探测领域,实际应用于风场观测时,由于噪声杂波干扰、回波信号较弱和风场不均匀性等影响了多普勒频移估计的精度。为准确估计激光雷达弱回波信号中的多普勒频移,提升相干测风激光雷达的探测距离和探测精度,文中开展了基于激光雷达功率谱信号的多普勒频移估计算法以及探测性能提升的评估研究。在快速傅里叶变换的基础上,提出了一种结合线性预测频谱估计与导数增强方法的功率谱分析方法,通过与常用的最大似然离散谱峰值频移估计算法(ML DSP算法)进行比较,验证了文中方法在相干测风激光雷达微弱信号频移估计过程中的优势。风速数据的时间及空间相关性分析结果表明,功率谱分析方法具有更好的风速估计稳定性,有效风场探测距离相较ML DSP算法提升了73%。与超声风速计对比结果表明,文中提出的综合算法在弱信号情况下的风速测量精度高,风速结果与超声风速计的标准偏差相较ML DSP算法降低了0.23 m/s,偏离率BIAS降低了0.3 m/s,有效提高了低信噪比范围内多普勒频移估计的精度。     

OFDM移动通信系统中的最大多普勒估计

提出了一种基于信道估计自相关函数的多普勒频移估计算法.在OFDM符号数据段前插入正交可变扩频因子(OVSF)序列,求出时域的信道冲激响应,利用信道冲激响应的自相关实现多普勒频移估计.仿真结果表明,该算法可以在较大多普勒频移范围内有效地估计出多普勒频移.     

OFDM系统中多普勒频偏估计技术仿真研究

研究了移动信道中的最大多普勒频移估计技术。分析了一种基于循环前缀的多普勒频移估计算法,该算法通过计算正交频分复用（OFDM）符号已有的循环前缀的相关函数来获得最大多普勒频移。采用广义平稳非相关散射下的多径时变瑞利信道模型,对各个算法进行了仿真试验,比较了各个算法的性能。仿真结果表明,利用多普勒分集技术,可以显著降低误码率,提高系统在移动环境下的性能。     

LEO卫星信道多普勒频移估计与补偿

为削弱LEO卫星信道的时间选择性衰落,提出了一种多普勒频移估计与补偿方法。基于差分相关检测器,从中频信号提取下行信号中的多普勒频移信息,然后利用A/D和DSP进行相应地采集与处理。用得到的多普勒频移估计实时调节接收机本振频率,实现对下行信号的多普勒频移补偿,同时计算出上行多普勒频移并进行补偿。该方法无需符号同步,特别适合于超过符号速率的多普勒频移估计。     

基于分段模型的OFDM时变信道估计

文章提出了一种二次多项式模型对信道的时变特征进行逼近，并与现有的两种分段线性模型的抗ICI性能做了比较分析。然后利用导频序列在不同的模型下做信道的时域估计，对其在双选择信道下的误码性能做了仿真比较。分析表明，二次多项式模型较一斜率模型的抗干扰和噪声性能有所改善，在较高信噪比环境中能够大大减弱多普勒频移带来的ICI影响。最后，比较了基于分段模型的时域估计和基于DFT的频域估计。     

Accurate estimation of Doppler shift in mobile communications with high vehicle speed

Representing the channel varying rate and the mobile speed of a mobile terminal directly, Doppler shift is an important parameter in vehicular mobile communications and therefore is widely used in mobile target detection and adaptive applications. Hence, this paper puts forward an accurate Doppler shift estimator in mobile communications with high vehicle speeds, which can also be treated as a vehicular speed estimator due to the well‐known relation between the Doppler shift and the mobile speed. Specifically, the proposed estimator is based on the channel level crossing rate, and an iterative process is presented to achieve signal‐to‐noise ratio (SNR) insensitive estimates in accordance with the level crossing rate estimation error analysis. Moreover, we prove the convergency of the iterative Doppler shift estimator in theory. Computer simulations conducted under a wide range of noise corruption clearly show that the proposed estimator substantially outperforms several existing estimators in terms of accuracy and achieves a good SNR‐insensitive performance in a wide range of velocities and SNRs. Copyright © 2013 John Wiley & Sons, Ltd.     

无源雷达目标信号时延与多普勒频率联合估计

提出一种基于STFRFT的无源雷达目标时延与多普勒联合估计新方法。首先,给出了一种STFRFT时频分辨率量化方法及其数学表达式;其次,利用STFRFT的投影包络对回波信号时延与Doppler频移进行了联合估计;最后,讨论分析了脉内信噪比、高斯窗参数等对所提方法估计性能的影响。仿真结果表明,与CAF方法相比,所提方法更容易获得高精度的时延与Doppler频移的联合估计,具有更高的可靠性。     

Optimal mean velocity estimation for Doppler weather radars

Optimal Doppler velocity estimation is explored for a standard Gaussian signal measurement model and thematic maximum-likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter [velocity, spectrum width (SW), and signal-to-noise ratio (SNR)], the exact formulation of an ML or Bayes solution involves a system of coupled equations that cannot be made explicit for any of the parameters. Simple computational forms are shown to exist when SW and SNR are assumed known. An information-theoretic concept is used to extend these equations to the general case of SW and SNR unknown. A Monte Carlo simulation experiment is used to verify that the method can work, with no a priori information for either SW or SNR and a very small (20 pulse) sample size. The improved performance of this new Doppler velocity estimator is documented by comparison with derived optimal bounds and with the performance of the pulse pair (PP) method. Bayes estimator results are used to provide true performance bounds for comparison. Cramer-Rao bounds are also derived and shown to be inferior to the Bayes bounds in the small sample case considered     

Pilot-based estimation of time-varying multipath channels forcoherent CDMA receivers

Reliable coherent wireless communication requires accurate estimation of the time-varying multipath channel. This paper addresses two issues in the context of direct-sequence code-division multiple access (CDMA) systems: (i) linear minimum-mean-squared-error (MMSE) channel estimation based on a pilot transmission and (ii) impact of channel estimation errors on coherent receiver performance. A simple characterization of the MMSE estimator in terms of a bank of filters is derived. A key channel characteristic controlling system performance is the normalized coherence time, which is approximately the number of symbols over which the channel remains strongly correlated. It is shown that the estimator performance is characterized by an effective signal-to-noise ratio (SNR)-the product of the pilot SNR and the normalized coherence time. A simple uniform averaging estimator is also proposed that is easy to implement and delivers near-optimal performance if properly designed. The receivers analyzed in this paper are based on a time-frequency RAKE structure that exploits joint multipath-Doppler diversity. It is shown that the overall receiver performance is controlled by two competing effects: shorter coherence times lead to degraded channel estimation but improved inherent receiver performance due to Doppler diversity, with opposite effects for longer coherence times. Our results demonstrate that exploiting Doppler diversity can significantly mitigate the error probability floors that plague conventional CDMA receivers under fast fading due to errors in channel estimation     

一种应用于无线传感网的频偏估计改进方法

为解决频偏估计中经典的M&M算法在频偏增大时信噪比门限变差的问题,提出一种改进的频偏估计算法。首先对自相关函数做预平均处理来降低噪声,然后利用预平均值做频偏粗估计,并利用粗估计值纠正相位来减轻相位模糊的问题,最后推导更加合理的窗函数并给出最终频偏估计表达式。仿真表明该算法的信噪比门限比M&M算法至少低-1 dB,且在频偏加大时仍然能保持较低的信噪比门限。在保证-3.5 dB的信噪比门限的前提下该算法的估计范围达到了理论值的90%,另外在最大自相关阶数较小时,估计精度门限优于M&M算法。该算法在M&M算法基础上的改进达到了预期效果,能同时满足无线传感网频偏估计中对低信噪比门限和大估计范围的要求。     

A fast parameter estimation algorithm for polyphase coded CW signals

A fast parameter estimation algorithm is discussed for a polyphase coded Continuous Waveform (CW) signal in Additive White Gaussian Noise (AWGN). The proposed estimator is based on the sum of the modulus square of the ambiguity function at the different Doppler shifts. An iterative refinement stage is proposed to avoid the effect of the spurious peaks that arise when the summation length of the estimator exceeds the subcode duration. The theoretical variance of the subcode rate estimate is derived. The Monte-Carlo simulation results show that the proposed estimator is highly accurate and effective at moderate Signal-to-Noise Ratio (SNR).     

基于插值的多普勒频偏和频率斜升联合估计算法

为解决卫星移动通信系统中突发传输在低信噪比条件下的载波快速同步问题,该文提出一种基于插值的频偏和频率斜升联合估计算法。先通过对多普勒斜升搜索结合低复杂度频偏估计获得频偏和频率斜升的粗估计结果,再以频率斜升粗估计结果为中心、计算3个频率斜升值所对应的对数似然函数并据此对频率斜升进行二次插值以获得频率斜升估计值,最后在该估计值下计算出对应的频偏估计值,完成频偏和频率斜升的联合估计。仿真结果表明,该文算法的信噪比门限较低,估计性能接近克拉美罗下界(CRLB),而且计算复杂度远低于最大似然估计算法,非常适于实际应用。     

一种改进的CPFSK信号频率估计方法

针对突发信号解调中多普勒频偏大的问题,提出了一种改进的连续相位移频键控信号(CPFSK)频率估计方法.首先接收信号平方运算使信号的调制指数加倍,再通过一次离散傅里叶变换(DFT),用搜索信号平方谱谱峰的方法实现突发信号频率估计.仿真实验表明,在低信噪比条件下,该算法的频率估计精度比经典的相位差频率估计算法提高了20%;该算法与广泛用于高动态突发信号的频率插值估计算法相比,同道干扰信道下信干比改善可达4 dB,DFT长度缩短约1/3.     

Improved estimation of low velocities in color Doppler imaging byadapting the mean frequency estimator to the clutter rejection filter

An adaptive mean frequency estimator is proposed for color flow imaging. It is based on a series expansion of the first derivative of the autocorrelation function of the Doppler signal at origin. Its bias can be reduced by shifting the integration bounds in the series expansion and its variance adjusted by adapting the coefficients of the serial-development. This estimator can be fitted to the specific characteristics of the clutter rejection filter using the signal-to-noise ratio (SNR) of the Doppler signal as an adaptive parameter. Its performance is compared to that of the usual correlation angle estimator, and its thresholded version, as well as that of the general mean frequency estimator, using a model of Doppler signal. The detection of low frequencies was significantly improved. The mean square error (MSE) was reduced an average 15 fold over a 25-dB range on the SNR, compared to the correlation angle estimator (CAE) or the general mean frequency estimator. A two-fold reduction in the MSE was obtained compared to the thresholded correlation angle estimator     

SNR estimation in time-varying fading channels

Signal-to-noise ratio (SNR) estimation is considered for phase-shift keying communication systems in time-varying fading channels. Both data-aided (DA) estimation and nondata-aided (NDA) estimation are addressed. The time-varying fading channel is modeled as a polynomial-in-time. Inherent estimation accuracy limitations are examined via the Cramer-Rao lower bound, where it is shown that the effect of the channel's time variation on SNR estimation is negligible. A novel maximum-likelihood (ML) SNR estimator is derived for the time-varying channel model. In DA scenarios, where the estimator has a simple closed-form solution, the exact performance is evaluated both with correct and incorrect (i.e., mismatched) polynomial order. In NDA estimation, the unknown data symbols are modeled as random, and the marginal likelihood is used. The expectation-maximization algorithm is proposed to iteratively maximize this likelihood function. Simulation results show that the resulting estimator offers statistical efficiency over a wider range of scenarios than previously published methods.