看无线电信号发射源单站定位技术的局限性

单站定位技术是指只使用一个无线电监测定向站,无需经过多站网络,即可对无线电电波发射源进行定位的技术.这一技术通常只用于短波信号.目前国际上使用的对无线电信号发射源进行单站定位的技术,还局限于以电波经过电离层的一次反射为基础的计算,目前国际上各无线电测向与定位设备和系统的厂商所能提供的产品,一般都只能对一跳路径传播的电波的发射源定位.对于多跳路径传播的无线电波,单站定位技术计算得出的发射源的距离通常比实际距离短.即使是对一跳路径传播的电波,由于电离层的高度随时间随机变化,电波可能从不同的高度反射到地面,因此单站定位系统也难以找出目标的准确距离.     

Joint signal detection and parameter estimation in multiusercommunications

The problem of simultaneously detecting the information bits and estimating signal amplitudes and phases in a K-user asynchronous direct-sequence spread-spectrum multiple-access communication system is addressed. The joint maximum-likelihood (ML) estimator has a computational complexity that is exponential in the total number of bits transmitted and thus does not represent a practical solution to the problem. An estimator that combines a suboptimum tree-search algorithm with a recursive least-squares estimator of complex signal amplitude is considered. The complexity of this estimator is O(K²) computations per decoded bit, and its performance is very close to that of the joint ML receiver. This receiver has the advantage that the transmitted signal powers and phases are extracted from the received signal in an adaptive fashion without using a test sequence     

Some lower bounds on signal parameter estimation

New bounds are presented for the maximum accuracy with which parameters of signals imbedded in white noise can be estimated. The bounds are derived by comparing the estimation problem with related optimal detection problems. They are, with few exceptions, independent of the bias and include explicitly the dependence on the a priori interval. The new results are compared with previously known results.     

Remarks, mostly historical, on signal detection and signal parameter estimation

Historical remarks outlining some of the evolution of the statistical theory of detecting signals in noise and of estimating signal parameters make up the greater part of the paper. The time period covered is roughly from the years of World War II to the middle 1960s. The remarks are rather severely limited in scope; they do not touch on nonparametric statistical methods, or filtering, or prediction theory, for example. The last part of the paper is a discussion of one aspect of a signal-processing problem area that is of current interest in optics and radar, and can be regarded as one of many descendants of the early parameter estimation theory. The area is object-field reconstruction or restoration, and the aspect of interest is the intrinsic relation between the inherent instability of solutions of many such problems and the precision or resolution of detail that can be attained in the construction.     

一种LFM信号最大似然估计模型与参数估计快速算法

从最大似然估计模型入手,提出了一种适合在一般高斯噪声环境（包括色噪声）下LFM信号目标的参数估计模型和基于此估计模型的调频斜率和初始频率估计的快速算法。此方法获得了最大似然方法估计精度高的优点,且运算量比传统的最大似然方法大大降低。另外推导出了一般高斯环境下的LFM参数估计的CRB界,为一般高斯环境下的估计的参数的方差提供实际下界。     

Fast detection and parameter estimation for polyphase-code radar signal

The detection and parameter estimation for polyphase-code radar signal are analysed in this article. In view of the fact that traditional algorithms of signal detection and parameter estimation have enormous computational complexity, a joint fast algorithm employed fractional operation is proposed to detect the polyphase-code radar signal and estimate its modulation parameter. The proposed algorithm firstly detects the signal and estimates the sweep rate with the detection statistics derived from fractional autocorrelation. Then proposed algorithm achieves the estimation of other modulation parameters by using fractional Fourier transform (FrFT). Simulation results have verified the effectiveness of the proposed algorithm. Compared with traditional algorithms, proposed algorithm has identical performance of detection and parameter estimation, but can remarkably reduce computational cost. The proposed algorithm is suitable for the application of practical equipment.     

A subspace rotation approach to signal parameter estimation

A new approach to Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) is described in the context of direction-of-arrival estimation, but is also applicable to other problems. The method relies on finding the underlying rotation between the common subspaces associated with an array of pairwise-matched and codirectional sensor doublets. ESPRIT has several remarkable advantages over earlier techniques such as MUSIC, and also provides asymptotically unbiased and efficient estimates.     

MULTIPLE FREQUENCIES ESTIMATION OF SIGNAL WITH SUB-SAMPLING

Based on time delay technology and MUSIC algorithm, a novel estimating multiple frequencies approach of signal with sampling rate which is least Nyquist sampling rate is presented in this paper. With choosing delay time properly, the estimated frequencies are unambiguous. Computer simulation confirms its availability.     

一种跳频信号实时跟踪与参数估计方法

现有的跳频信号处理方法往往需要积累足够长的样本数据,缺乏实时快速运算的能力,无法处理高速跳频信号。在小样本条件下提出一种跳频信号实时跟踪和参数估计方法。根据跳频信号的频域稀疏性建立信号模型,引入稀疏贝叶斯学习(SBL)算法解决多观测向量(MMV)信号重构问题。在构建新的判决统计量基础上,推导一种保持恒虚警概率的跳变时刻检测方法,设计滑动策略实现跳频信号的实时跟踪。分别利用几何重心法和最小二乘法估计每跳(hop)的载波频率和来波方向(DOA)。实验证明,新方法在低信噪比(SNR)下具有更低的虚警概率,参数估计精确度得到明显提升。     

Detection and parameter estimation of a transient signal usingorder statistics

Detection and parameter estimation of a transient signal in noise is a problem of many applications. It is characterized by the fact that some of the measurements consist of noise only. Modern statistical signal processing techniques are applied on a discrete version of the received data and are implemented by digital signal processing (DSP). In this correspondence, we show how order statistics (OS)-based signal processing, which is of a discrete nature, can be used for simultaneous detection and estimation of parameters (such as time of arrival and signal duration) of a sampled transient signal in white noise. We show that the resulting processors are more robust than the conventional processors, whereas their performance is about the same, at the cost of increased computational complexity     

Multicarrier signal detection and parameter estimation infrequency-selective Rayleigh fading channels

A new joint signal detection and channel parameter estimation scheme is proposed for multiple subcarrier signaling with pilot symbol-assisted modulation (PSAM) schemes. The proposed scheme estimates a pair of parameters associated with the generation process of the fading frequency selectivity, which is common to all the subcarriers. This parameter estimation can effectively extract information regarding the fading frequency selectivity through the pilot symbols received not only by the subcarrier of interest, but by other ones as well. The fading complex envelope with each subcarrier is derived from the estimates of the parameter pair. With the proposed scheme, performances are evaluated through simulations and are compared with the performance of a subcarrier-by-subcarrier detection scheme     

Some results on the stochastic signal parameter estimation problem

The problem of finding maximum-likelihood estimates of the partially or completely unknown autocorrelation function of a zero-mean Gaussian stochastic signal corrupted by additive, white Gaussian noise is analyzed. It is shown that these estimates can be found by maximizing the output of a Wiener estimator-correlator receiver biased by a smoothed version of the output noise-to-signal ratio of the Wiener estimator over the class of admissible autocorrelation functions. For the case where the autocorrelation function is known except for an amplitude scale parameter, an illuminating expression for the Cramer-Rao minimum estimation variance is derived. Detailed study of this expression yields, among other results, an interpretation of the maximum-likelihood estimator as an adaptive processor.     

基于直扩信号GPS的无源定位参数估计

在电子对抗系统中,无源定位跟踪系统由于本身不发射电磁波,具有很好的隐蔽性,而提取辐射电磁信号中携带的定位信息的参数,则是实现无源定位的前提和关键.对GPS卫星系统信号加以利用,通过计算出目标反射GPS卫星信号的回波信号相对于直达信号的时延和多普勒频移信息,仿真了一种新的估计算法,为目标的定位提供了基础.     

Robust parameter estimation of a deterministic signal in impulsivenoise

This paper presents a robust class of estimators for the parameters of a deterministic signal in impulsive noise. The proposed technique has the structure of the maximum likelihood estimator (MLE) but has an extra degree of freedom: the choice of a nonlinear function (which is different from the score function suggested by the MLE) that can be adjusted to improve robustness. The effect of this nonlinear function is studied analytically via an asymptotic performance analysis. We investigate the covariance of the estimates and the loss of efficiency induced by nonoptimal choices of the nonlinear function, giving special attention to the case of α-stable noise. Finally, we apply the theoretical results to the problem of estimating the parameters of a sinusoidal signal in impulsive noise     

线性调频步进信号雷达目标运动参数估计方法

针对目标运动对线性调频步进信号雷达成像的影响,提出一种基于时频分析的目标运动参数估计方法。对差频处理后的各簇回波信号进行快速傅里叶变换,利用变换后信号与子脉冲序列的线性调频关系,通过维格纳分布和Radon变换对目标不同时刻运动参数进行估计。结合二值数学形态学与图像边缘检测方法提高对多散射点目标运动参数估计的精度。在此基础上,针对目标可能出现的变速运动情况,利用最小二乘算法拟合整个成像时间内目标运动速度的变化,较好地实现对机动目标的运动参数估计。仿真实验验证了本文方法的有效性。     

一种扫频干扰信号参数估计方法

现代的干扰信号越来越多的采用复杂的信号波形和调制样式,为了解决对干扰信号时频分析中出现的时间分辨率和频率分辨率无法兼顾的问题,得到更加清晰明确的时频关系图,本文提出了基于平滑伪 Wigner-Ville分布（SPWVD）的时频分析方法,并通过对干扰信号的分析处理结果验证了该方法的有效性。     

基于信号子空间的多维参数联合估计

旋转不变的子空间中特征值的估计与关联是多维谱估计和阵列信号处理的重要问题.采用平行的交叉偶极子均匀线阵,利用各子阵列输出信号的相关矩阵构造多个旋转不变的子空间,并用其中一个子空间的信号子空间实现了频率、二维到达角和极化的自动配对.整个计算过程只需进行一次矩阵特征值的分解,就可完成多维参量估计与配对,且不存在参量兼并现象,理论分析与计算仿真结果证明了方法的有效性.     

On simultaneous signal estimation and parameter identificationusing a generalized likelihood approach

A common approach to blind deconvolution of Bernoulli-Gaussian processes consists of performing both signal restoration and hyperparameter identification through maximization of a single generalized likelihood criterion. It is shown on a simple example that the resulting hyperparameter estimates may not converge toward any meaningful value. Therefore, other more reliable approaches should be adopted whenever possible     

基于WiFi信号的多维参数估计与三维轨迹跟踪算法

在未来物联城市的规划和现有的发展情况下,基于位置的服务变得越来越重要。室内定位在很多场景都有着明朗的应用前景,如轨迹跟踪、老人看护、手势识别等。但是现存的室内定位通常需要在离线阶段大量实验以建立相应特征库,有些系统还对设备有特殊要求。另外,现有的定位系统多是基于对二维平面上的运动进行定位,未曾考虑对进行三维运动的人进行定位。对此我们提出了一种基于商用WiFi路由器和无线网卡下的系统,对人体反射回的无线信号做处理,从而得到多普勒频移、信号飞行时间、到达角度这些多维参数,对进行三维运动的人进行跟踪定位。我们的系统只用两个接收端,可以动态的适应环境,提取出多维用以估计位置的参数,达到0.7m精度的三维轨迹跟踪。