An Analysis and Comparison of Energy Direction Finding Systems

Direction finding systems that use knowledge of only the aporoximate center frequency and bandwidth of the arriving signal and perform the azimuth estimate using the signal energy azimuthal distribution are of widespread interest. In this paper, a variety of such systems are considered. Their performances are analyzed and compared to each other and to a baseline optimal system. Particular attention is given to systems that will perform well against wideband signals in a low signal-to-noise environment.     

A Parametric Technique for Time Delay Estimation

The problem of estimating the time difference of arrival of a signal with unknown spectrum to two receivers is treated. A signal model containing both spectral and delay parameters is derived. The model parameters are computed by a two-step procedure: (1) the modified Yule-Walker equations are used to estimate the autoregressive spectrum of the source signal, and (2) a frequency domain squared error criterion is minimized to provide the delay estimate. The performance of the proposed technique is illustrated by simulation results.     

Experiments in Adaptive Estimation of Unknown Binary Waveforms

A special-purpose adaptive machine is described which carries out estimation in real time of an unknown binary waveform which is perturbed with additive Gaussian noise. Unknown waveforms of over 103 samples in duration can be recovered. The unknown waveforms are of unknown epoch and can reappear at either random or periodic time intervals. The observed signal is received at moderate or low signal-to-noise ratios so that a single observation of the received data (even if one knew the precise signal arrival time) is not sufficient to provide a good estimate of the signal waveshape. Experimental results are described which show transient behavior waveform estimate. The transient behavior is expressed as the number of errors in the current estimate of the signal plotted vs. time. In a noisy environment, each ``learning' transient is a random time function. These learning transients are shown for several different signal-to-noise ratios and indicate the threshold noise levels for various types of initial states of the machine memory.     

基于Doppler估计的弹载接收机抗欺骗干扰研究

GNSS接收机在军用方面尤其是高精度制导武器中的应用日益增强.针对卫星信号易受敌方欺骗信号干扰的问题,设计一种基于Doppler频率估计的弹载接收机抗欺骗干扰的方法.首先分析了欺骗干扰和真实信号的Doppler变化特点;然后在捕获阶段利用残留信号检测存在欺骗干扰的卫星编号;最后根据弹载的高动态特性,在跟踪阶段采取扩展 Kalman 滤波器(EKF)进行载波Doppler频率估计,并根据Doppler变化的相似性提取出欺骗信号.通过仿真实验验证,该方法可以有效排除欺骗信号的干扰.     

双重未知干扰解耦的多传感器系统偏差校正与状态估计

具有未知干扰输入的随机系统状态估计问题广泛存在于控制、通信、信号处理和故障诊断等领域,但目前的研究成果大多局限于单传感器动态离散系统。针对状态方程含有未知干扰、量测方程含有未知偏差的多传感器系统状态估计问题开展了研究,提出了一种双重未知干扰解耦下的最小方差无偏估计滤波器。首先,建立量测偏差通用演化模型;然后,解耦偏差演化模型中的未知输入,设计最小方差无偏估计器对量测干扰偏差进行估计;之后,利用估计出的量测偏差来校正动态系统测量值;最后,根据量测偏差校正后的系统模型设计最优状态观测器,获得具有最小方差无偏的状态估计。径向飞行控制系统的例子验证了所提方法的有效性,与相关方法的仿真对比反应了所提方法的优越性。     

Implementation and performance analysis of accurate localization of short-range targets based on multisensor systems

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Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

基于自适应修正曼哈顿距离的室内定位方法

在室内WiFi环境下,针对常见指纹匹配算法所忽略的信号波动问题,提出了一种基于自适应修正曼哈顿距离和AP选择的指纹匹配算法,并结合加权K近邻方法实现定位。首先采用AP选择算法获取部分受干扰程度小和出现频率高的AP,在指纹匹配时仅使用该部分AP的接收信号强度进行计算;在分析WiFi信号传播衰减公式和信号波动的基础上,提出了将自适应修正曼哈顿距离作为指纹匹配的度量距离,使用该距离旨在平滑信号波动对指纹相似度计算的影响;最后采用加权K近邻方法估计测试点的坐标。实验结果表明,在加权K近邻方法的框架下,基于自适应修正曼哈顿距离的定位算法在定位精度上优于基于欧氏距离、曼哈顿距离、余弦距离和Sorensen距离的定位算法。     

A Recursive Method for Signal Resolution

A recursive method is given for resolving signals overlapping in time. Assume that the signal waveform is known and several signals are received. The signals (of unknown number) may overlap with one another and the amount of time delay of each individual signal is unknown. The signals are corrupted with additive white Gaussian noise. The problem is to estimate the number, the amplitudes, and the time delays of the overlapping signals. Assume that at a certain instant tk-1 estimates have been made on the number of signals arriving in the time interval (O, tk-1) and the amplitudes and time delays of these signals. Using these estimates, we test at tk the hypothesis H1 that a new signal arrives at tk against the null hypothesis Ho that no new signal arrives. The decision gives the number of signals arriving in the time interval (0, tk); the parameters are then re-estimated. The overlapping signals are detected and resolved, and the estimates are improved at each stage. The system is analyzed in detail, and computer-simulated results are presented.     

常用脉冲重复间隔估计算法

雷达信号分选是电子战系统(EW)与反辐射导弹(ARM)的关键技术,脉冲重复间隔(PRI)是信号分选与识别的一个重要参数,它决定了雷达的最大无模糊距离和最大无模糊径向速度。目前以脉冲序列的自相关函数为基础,利用脉冲到达时间(TOA)提出了多种脉冲重复间隔估计算法。本文介绍了几种常用算法的原理,讨论了各算法的缺陷,并给出了PRI变换应用于抖动PRI序列时的计算机仿真结果。最后分析了各种算法的性能与适用范围。     

Resolution of signal sources via spectral moment estimation

In different practical situations it is desired to estimate the number of signal sources and their positions in space or in frequency domain. The first problem is known as the detection or the order estimation and the second one as the resolution. For the resolution problem techniques such as nonlinear least squares (NLSM), high-order Yule-Walker method (HOYW), multiple signal classification (MUSIC), Pisarenko harmonic retrieval method, min-norm method, estimation of signal parameters by rotational invariance technique (ESPRIT), were proposed (Marple, 1987 and Stoica and Moses, 1997). All these high-resolution methods are based on the analysis of the signal covariance matrix. But the covariance matrix is not the only choice to represent the signal spectrum. In different applications (weather radars, synthetic aperture radar (SAR) signal processing, ultrasound imaging in medicine, atmospheric turbulence measurements) the signal spectrum can be modeled through its algebraic moments. Recently a number of efficient nonparametric methods have been proposed to estimate the algebraic spectral moments (Monakov, 1999). The presented paper is an attempt to solve the direction of arrival (DOA) problem via estimation of the algebraic spectral moments. A method proposed in the article is comparable in its accuracy with the MUSIC method. At the same time its computational burden is much lower. The method permits to estimate the signal power of sources easily to complete the full spectral line analysis. Additionally the method shows good robustness in situations when signal sources have noticeable spatial extend     

An operational system implementation of the ESPIRIT DF algorithm

The practical implementation of the ESPRIT algorithm into direction-finding system architecture is considered. In particular, the problems of phase ambiguity resolution for extended array separations and multidimensional azimuth/elevation estimation are addressed. Generalized solutions for these problems are proposed, and a bearing quality indicator that provides a measure of credibility associated with each angle-of-arrival estimate is developed. Plots of computer simulated performance are presented in order to assess the probability of detection, of failure to alarm, and of false alarm as a function of azimuthal separation and period of signal observation     

Array Processor Performance Under Directional Uncertainty

Detection performance of four candidate receiver structures for the signal known except for direction (SKED) array problem is investigated. Included are the Bayes optimal detector, two estimate and plug structures, and a fixed estimate structure. Estimators considered are the maximum likelihood (ML) and maximum a posteriori (MAP). Performance degradation from optimal for the estimate and plug structures considered is shown to be significantly more severe the larger the array size.     

测量转子叶片振动的脉冲处理技术

一、引言 为解决转子运行状态下叶片振动的测量问题,本文发展了多个探头组合的光电脉冲处理技术,并进行了误差估计。对于呈钟形分布而非尖型的单个脉冲,提出了新的信号计时基准,同时作了理论考证和实验分析。     

Remaining useful life prediction for engineering systems under dynamic operational conditions: A semi-Markov decision process-based approach

For critical engineering systems such as aircraft and aerospace vehicles, accurate Remaining Useful Life(RUL) prediction not only means cost saving, but more importantly, is of great significance in ensuring system reliability and preventing disaster. RUL is affected not only by a system's intrinsic deterioration, but also by the operational conditions under which the system is operating. This paper proposes an RUL prediction approach to estimate the mean RUL of a continuously degrading system under dynamic operational conditions and subjected to condition monitoring at short equi-distant intervals. The dynamic nature of the operational conditions is described by a discrete-time Markov chain, and their influences on the degradation signal are quantified by degradation rates and signal jumps in the degradation model. The uniqueness of our proposed approach is formulating the RUL prediction problem in a semi-Markov decision process framework, by which the system mean RUL can be obtained through the solution to a limited number of equations. To extend the use of our proposed approach in real applications, different failure standards according to different operational conditions are also considered. The application and effectiveness of this approach are illustrated by a turbofan engine dataset and a comparison with existing results for the same dataset.     

Performance of pulse-pair method of Doppler estimation

Because of its simplicity, the pulse-pair method is usually used in the estimation of Doppler from backscattered acoustic signals. In the literature, various improvements to the basic pulse-pair estimate have been proposed. The statistics of these improved methods have also been derived using simplified assumptions for the signal and noise. By developing a multiplicative noise model for the backscatter signal, in this work, the variance of the Doppler estimate is derived under all signal scenarios. The dependency of the variance on the amplitude correlation length of the data is also discussed. It is demonstrated that the use of parabolic window in the estimate is the proper method of Doppler evaluation under all conditions     

State estimate for stochastic systems with dual unknown interference inputs

Stochastic system state estimation subject to the unknown interference input widely exists in many fields, such as the control, communication, signal processing, and fault diagnosis. However, the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input, and the state model and the measurement model are both with the same unknown interference input. State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs (dual-UI) with different physical meanings and mathematical definitions is concerned here. Firstly, the decoupling condition with the Unknown Interference input in the State model (S-UI) is shown, which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs (M-UI) appearing in the state model and the measurement model. Then, through defining the Differential term of the adjacent M-UI (M-UID), the equivalent system with only M-UID in the state model is obtained. Finally, considering the design freedom of the equivalent system, the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate, respectively. Two simulation cases verify the effectiveness and superiority compared with the traditional methods.     

基于广义Kalman估计的机载雷达高精度控制系统

 研究了在某型现役机载雷达系统中, 采用广义Kalman 滤波器方法来预估目标机的俯仰角和方位角,产生跟踪目标用的雷达天线驱动信号, 替代传统的速率陀螺测量元件来补偿本机机动所造成的扰动的方法,同时对探测信号本身所具有的延迟起到了补偿作用。对目标的运动采用直角坐标系中的Singer 模型描述, 而对测量信号则是应用极坐标系中的描述, 采用广义Kalman 滤波器来完成估计, 即在每一步的估计和控制中对计算测量方程进行线性化结果, 实现两种坐标系的转换。通过应用Matlab/ Simulink 软件对整个系统的建模、设计及仿真研究, 得到了满意的结果。     

Optimal Digital Beam Splitting for Radar Beacon Systems

Beam splitting for a radar beacon system that scans in azimuth is investigated from a theoretical viewpoint. The video output is quantized into two levels corresponding to a detection and no detection. Further, the antenna sensitivity profile is described by sin ?/?. For this system, a digital method of beam splitting that minimizes angular error is developed. Prior information about the probable location of targets can be included. Both Bayesian and minimax approaches are developed. The minimax estimate of the target azimuth is the average of the angles at which beacon signals are detected. The antenna beam can be interpolated by a factor of 10 when the signal power is 3 dB above the noise and without prior azimuth information The interaction of beam splitting and detection is discussed.     

Robust speed sensorless induction motor drive

A speed sensorless induction motor (IM) drive with robust control characteristics is introduced. First, a speed observation system, which is insensitive to the variations of motor parameters, is derived based on the concept of sliding mode. Next, an integral-proportional (IP) speed controller using the estimated speed signal is designed to stabilize the speed loop. Then, to preserve the robust control performance under parameter variations and external load disturbance, an adaptive uncertainty observer with feedforward control is proposed. The adaptive uncertainty observer is implemented to estimate the lump of uncertainty of the controlled plant. To increase the accuracy of the estimated values, the speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate