DOA and steering vector estimation using a partially calibratedarray

We consider the problem of estimating directions of arrival (DOAs) using an array of sensors, where some of the sensors are perfectly calibrated, while others are uncalibrated. We identify a cost function whose minimizer is a statistically consistent and efficient estimator of the unknown parameters-the DOAs and the gains and phases of the uncalibrated sensors. Next we present an iterative algorithm for finding the minimum of that cost function The proposed algorithm is guaranteed to converge. The performance of the estimation algorithm is compared with the Cramer Rao bound (CRB). The derivation of the bound is also included. It is shown that DOA accuracy can be improved by adding uncalibrated sensors to a precisely calibrated array. Moreover, the number of sources that can be resolved may be larger than the number that can be resolved by the calibrated portion of the array     

CRB: Sinusoid-Sources' Estimation using Collocated Dipoles/Loops

This work derives new asymptotic Cram?r-Rao lower bounds (CRB) for the estimation of multiple pure-tone incident signals' azimuth-elevation arrival-angles, polarization parameters, frequencies, amplitudes, and temporal phases—based on data collected by spatially collocated but orthogonally oriented dipoles and/or loops. The incident sources are pure-tones at distinct, deterministic but unknown frequencies, in contrast to the case of all incident sources at one common known frequency, as has been investigated in the existing research literature on the CRB for diversely-polarized direction-finding. The derived CRBs are closed-form expressions, explicitly in terms of the signal parameters. The new CRBs presented here reveal how a constituent dipole and/or loop's presence and orientation may affect estimation precision, thereby offering guidelines to the system engineer on what dipole(s) and/or loop(s) to include or to omit in constructing the electromagnetic vector-sensor.     

DOA estimation using one-bit quantized measurements

The effects 1-bit quantization of the input samples has on the direction-of-arrival (DOA) estimation accuracy are considered. The signal model assumes a single stochastic Gaussian point source that is embedded in white Gaussian noise (WGN). The inherent limitations governed by the extreme clipping of the input data are analyzed using the Cramer-Rao bound (CRB) that is derived for a two-sensor array. In addition, several estimators for the I-bit estimation are discussed. Numerical and analytical analyses of the estimation error reveal weak dependency on signal-to-noise ratio (SNR) with singular behavior of the estimation error in certain DOA angles.     

一种稀疏阵列下的二维DOA估计方法

研究了稀疏阵列下二维波达方向（DOA）的估计问题,提出一种基于不动点迭代的空间谱估计（FPC-MUSIC）算法。首先建立基于矩阵填充的DOA估计信号模型,并验证该信号模型满足零空间性质（NSP）,其次通过不动点迭代算法将稀疏阵列信号恢复为完整信号,最后利用恢复信号估计二维DOA。该算法可在稀疏阵列下大幅度降低谱估计平均副瓣,在大幅度降低阵元数的同时具有较高的估计精度。计算机仿真表明：FPC-MUSIC算法可在稀疏阵列下准确估计二维DOA,验证了该算法的有效性和优越性。     

A two-step weighted least-squares method for joint estimation of source and sensor locations: A general framework

It is well known that the Two-step Weighted Least-Squares(TWLS) is a widely used method for source localization and sensor position refinement. For this reason, we propose a unified framework of the TWLS method for joint estimation of multiple disjoint sources and sensor locations in this paper. Unlike some existing works, the presented method is based on more general measurement model, and therefore it can be applied to many different localization scenarios.Besides, it does not have the initialization and local convergence problem. The closed-form expression for the covariance matrix of the proposed TWLS estimator is also derived by exploiting the first-order perturbation analysis. Moreover, the estimation accuracy of the TWLS method is shown analytically to achieve the Cramér-Rao Bound(CRB) before the threshold effect takes place. The theoretical analysis is also performed in a common mathematical framework, rather than aiming at some specific signal metrics. Finally, two numerical experiments are performed to support the theoretical development in this paper.     

双偏振干涉式光纤陀螺的多相位调制技术

在双偏振干涉式光纤陀螺的发展过程中,光纤环上的应力、扭转等会造成正交偏振态之间的交叉耦合,降低陀螺系统的稳定性。提出了一种基于双偏振干涉式光纤陀螺的六态方波调制技术并进行了理论推导。该技术与传统的方波和四态方波调制相比,降低了偏振交叉耦合误差,提高了信噪比,大大增加了信号解算精度。通过实验对比测试了干涉式光纤陀螺在不同调制技术下的偏置稳定性。实验结果表明六态方波调制技术的偏置稳定性达到了9.85×10^-4(°)/h,验证了六态方波提高信号解算精度的效果。     

Maximum Likelihood DOA Estimation in Unknown Colored Noise Fields

Direction-of-arrival (DOA) estimation in unknown noise environments is an important but challenging problem. Several methods based on maximum likelihood (ML) criteria and parameterization of signals or noise covariances have been established. Generally, to obtain the exact ML (EML) solutions, the DOAs must be jointly estimated along with other noise or signal parameters by optimizing a complicated nonlinear function over a high-dimensional problem space. Although the computation complexity can be reduced via derivation of suboptimal approximate ML (AML) functions using large sample assumption or least square criteria, nevertheless the AML estimators still require multi-dimensional search and the accuracy is lost to some extent. A particle swarm optimization (PSO) based solution is proposed here to compute the EML functions and explore the potential superior performances. A key characteristic of PSO is that the algorithm itself is highly robust yet remarkably simple to implement, while processing similar capabilities as other evolutionary algorithms such as the genetic algorithm (GA). Simulation results confirm the advantage of paring PSO with EML, and the PSO-EML estimator is shown to significantly outperform AML-based techniques in various scenarios at less computational costs.     

直达与非直达环境中的多目标解耦直接定位方法

针对直达（LOS）与非直达（NLOS）环境中的定位问题,提出了一种波形已知条件下的单阵地多目标直接定位（DPD）算法。该算法针对发射时间已知和未知两种情况,利用多径信号到达角度与时延关于障碍物（或反射体）、观测站与目标位置参数的数学关系,建立了三维目标位置的最大似然（ML）函数,无需估计测量参数,避免了传统两步定位方法所需的非直达径识别与数据关联。为了克服多目标定位中的高维非线性优化问题,该算法利用独立波形信息将多目标定位解耦为对各个目标单独求解。通过对目标函数有效近似,算法在发射时间已知和未知两种情况下均仅需三维网格搜索,比相应的两步定位方法具有更低的计算量。此外,基于多径定位场景,推导了发射时间已知和未知两种情况下的位置估计克拉美罗界（CRB）。仿真结果表明：算法的定位性能能够逼近相应的克拉美罗界,比传统两步定位方法和子空间直接定位算法具有更高的定位精度。     

The Exact Cramer-Rao Bound for Gaussian Autoregressive Processes

An explicit expression is derived for the Cramer-Rao bound(CRB)on unbiased estimates of the parameters of autoregressiveprocesses, given a finite number of measurements. The expressionconverges to the well-known asymptotic form of the CRB when thenumber of measurements tends to infinity. The behavior of thebound is illustrated by some numerical examples.     

The exact Cramer-Rao bound for Gaussian autoregressive processes

An explicit expression is derived for the Cramer-Rao bound (CRB) on unbiased estimates of the parameters of autoregressive (AR) processes, given a finite number of measurements. The expression converges to the well-known asymptotic form of the CRB when the number of measurements tends to infinity. The behavior of the bound is illustrated by some numerical examples     

Null phase-shift polarization filtering for high-frequency radar

In order to effectively cancel the interference in polarization filtering, the parameters of the polarization filter should timely adapt to the variation of the polarization of the interference, which may impact the amplitude and phase of the desired signal that passes through the same polarization filter during the coherent integration time (CIT) and render the enhancement of the signal integration a failure. To avoid this, a null phase-shift polarization (NPSP) filter is proposed, which is composed of a linear polarization transformer (LPVT), a conventional single-notch polarization (SNP) filter and an amplitude/phase compensation device (A/PCD). The interference, which has polarization different from those of the desired target signal, can be suppressed completely while the target signal remains without distortion. Some applications of high-frequency (HF) radars for suppressing the radio interference are introduced. Simulation results from the experimentally derived data indicate that the improvement of the signal-to-interference ratio (SIR) can be expected to be more than 28 dB. The proposed NPSP filter is effective in HF radar or other coherent systems.     

Multipath Effects on an Azimuthal Monopulse System

The first topic considered is an analysis of the conditions under which the conventional definition of length of the glistening surface, as given by Beckmann and Spizzichino, is not valid. For some conditions, significant amounts of incoherent scattered power can be received from areas beyond the conventional length. A second topic is the investigation of the effect on azimuthal angular tracking accuracy due to such scattering factors as shadowing, surface height distribution, standard deviation in surface height ?, surface correlation length T, unevenness and inhomogeneity of the terrain, antenna heights, and signal polarization. A number of interesting results have been observed. The amount of additional incoherent power not included under the conventional definition depends on the ratio ?/T, except for the case where both transmitter and receiver are very close to the surface. The trends in the behavior of the glistening surface are similar for vertical or horizontal polarization, for Gaussian or exponential surface height distributions, and for different signal frequencies in the S-band to L-band range.     

Further study of the Pencil-MUSIC algorithm

For finding 2-D angles and polarizations of waves arriving at a rectangular array of crossed dipoles, the Pencil-MUSIC method can achieve the near optimum performance with much less computational burden than the MUSIC (multiple signal classification). Following an angle-only ESPRIT (estimation of signal parameters via rotational invariance techniques) method, an angle-only Pencil-MUSIC can be easily formulated which is far more accurate than the former especially in the coherent case. The angle-only Pencil-MUSIC is analyzed and compared with the original Pencil-MUSIC. The new version sacrifices the polarization estimation to achieve about 8 times more efficient computation The accuracy of the new version seems no more than 4 times worse in terms of estimation deviation     

Posterior Cramer-Rao bounds for multi-target tracking

This study is concerned with multi-target tracking (MTT). The Cramer-Rao lower bound (CRB) is the basic tool for investigating estimation performance. Though basically defined for estimation of deterministic parameters, it has been extended to stochastic ones in a Bayesian setting. In the target tracking area, we have thus to deal with the estimation of the whole trajectory, itself described by a Markovian model. This leads up to the recursive formulation of the posterior CRB (PCRB). The aim of the work presented here is to extend this calculation of the PCRB to MTT under various assumptions.     

鲁棒成形极化敏感阵列波束的方法及极化估计

基于极化敏感阵列,提出了一种鲁棒成形阵列波束的方法。该方法首先将阵列的数据模型进行了重新描述,从而获得了信号波达角(DOA)和极化解耦的模型。借助于该模型并对信号的两个极化方向分别进行鲁棒约束,设计出了一个新的鲁棒空域波束空间成形矩阵,利用该矩阵可以获得信号两个极化分量的鲁棒估计。基于特征值分解的方法,最后给出了估计信号极化参数的方法。分析和数值仿真实验均表明:提出的方法,在对DOA估计误差以及阵列位置误差等造成的阵列失配具有较强鲁棒性的同时,也能有效抑制干扰和噪声,进而提升了极化参数估计的性能。     

Solar-tracking methodology based on refraction-polarization in Snell's window for underwater navigation

Underwater navigation system is an indispensable part for autonomous underwater vehicles. Due to the indiscernibility of satellite signal, however, the underwater navigation problem is quite challenging, and a satellite-free navigation scheme should be looked for. Polarization navigation, inspired by insects’ capability of autonomous homing and foraging, is an alternative solution to satellite navigation with great application potential. Underwater polarization provides an indirect sun compass t...     

Estimation of the covariance matrix for dependent signal samples:polarization diversity systems

The problem of the estimation of covariance matrices in multichannel radar system when signal samples are statistically dependent is addressed. An optimal maximum likelihood (ML) estimate is derived. Probability characteristics and sensitivity to signal models of the estimate are evaluated for a polarization diversity system     

恶劣天气下的仿生偏振定向方法

针对偏振光导航在恶劣天气下精度显著下降的问题,提出了一种可以在恶劣天气下基于大气偏振模式的定向算法。与现有方法相比,首次将三维块匹配与canny边缘检测结合的思想应用于修复被不同天气破坏的偏振角度图像中。具体而言,将偏振角度图像的修复分为噪声粗处理和边缘提取处理去噪两部分。在噪声粗处理阶段采用三维块匹配算法,在边缘提取处理去噪部分,利用canny边缘检测算法对偏振角度图像进行二次去噪。实验结果表明,该方法不仅能够提高晴朗天空下的定向精度,而且能够显著提升在阴天、沙尘、雾霾等恶劣天气条件下的导航定向精度,即使在偏振角图像对称∞模式被破坏的情况下,航向角精度仍可由9.4470°提高到1.6859°。     

基于局部大气偏振特性的仿生导航方法

目前主流的偏振导航算法中，思路通常为通过对全天域偏振图像的获取拟合出太阳子午线或中性点的位置，进而判断导航方向。现提出一种新的导航方向获取算法，可在小视场条件下，通过对太阳方向矢量的拟合判断导航方向。在此基础上进行了计算机仿真和室外实验，利用偏振相机获取了天顶区域大气偏振分布模式；利用斯托克斯矢量分析法解算出了大气偏振模式的分布情况，包括其中偏振度和偏振角的信息，初步证实了解算算法在实际情况下的可行性和精度，导航精度可达到0.2°左右。     

基于声波传播时间估计的气流速度测量方法

 为实现对亚声速和超声速气流速度的统一测量,提出了一种基于声传感器的新型测量方法。首先,根据声波在亚声速和超声速气流中的传播特性,利用特定的测量装置建立了声波传播时间与气流速度之间的数学模型,从而将气流速度的测量问题转化为声波传播时间的测量问题。然后,在此基础上,利用计时法和最大似然估计(MLE)方法来估计声波传播时间;其中,计时法在实时性上优势明显,而MLE方法则在可靠性上优于前者。最后,分别从阵元位置扰动性、计时误差和克拉美-罗界(CRB)3个方面对所提算法的性能进行了分析与仿真验证。结果表明,该算法能够实现对亚声速和超声速气流速度的精确测量。