Some Matched Filter Configurations for Infrared Systems

An analysis of the output of three alternative matched filter configurations in an infrared scanning system model is presented. The sensor is corrupted by thermal noise, generation-recombination noise, photon noise, and modulation noise, the latter providing an extreme discoloration in the signal passband. Expressions for the signal voltage density spectrum, signal pulse shape, noise power spectrum, and average noise power at the matched filter output are derived where the integral evaluations attendant to these derivations do not appear elsewhere in the literature. The paper also provides graphical displays of the signal-to-noise power ratio at the filter output versus various system parameters, noise power spectrum out of the matched filter versus ?, and the signal pulse shape out of the filter versus time. Also included are discussions of practically realizable approximations to the matched filters and curve fitting techniques for the signal pulse shape function.     

Detection of Known Signals in Nonstationary Noise

The basic design of a nonlinear, time-invariant filter is postulated for detecting signal pulses of known shape imbedded in nonstationary noise. The noise is a sample function of a Gaussian random process whose statistics are approximately constant during the length of a signal pulse. The parameters of the filter are optimized to maximize the output signal-to-noise ratio (SNR). The resulting nonlinear filter has the interesting property of approximating the performance of an adaptive filter in that it weights each frequency band of each input pulse by a factor that depends on the instantaneous noise power spectrum present at that time. The SNR at the output of the nonlinear filter is compared to that at the output of a matched filter. The relative performance of the nonlinear system is good when the signal pulses have large time-bandwidth products and the instantaneous noise power spectrum is colored in the signal pass band.     

一种基于盲同态解卷积的SAR成像自聚焦算法

针对大气扰动及飞行平台不稳引起机载合成孔径雷达(SAR)图像散焦的问题,提出了一种新的自聚焦算法来估算运动误差。该算法是基于运动误差函数及场景散射函数平滑特性的差异来进行估计的,利用复对数变换将图像的幅度与相位信息分离,进而分别对相位及幅度信息进行处理。运动误差通常为慢变函数,而场景的散射信息具有某种随机特性。因此,经过复对数变换后,运动误差及散射信息可以通过滤波器进行分离,将相位中的随机噪声去除,从而保留了慢变的运动误差函数。为了去除噪声信息,需要建立一个平滑滤波器,利用Daubechies小波的尺度函数构造Riesz基向量,从而建立了正交子空间,通过所建立信号子空间及噪声子空间组建平滑滤波器,最终可以获得准确的运动误差。在实验部分,分别利用仿真数据及实测数据对本文方法进行验证,最终结果分析表明该方法具有很高的估计精度及执行效率。     

Radar Target Pointing Error Reduction Using Extended Kalman Filtering

A new method of reducing target glint errors in radar systems is presented. The target is modeled as n reflectors whose magnitudes and phases are known. The reflector positions are described by a dynamical model driven by white Gaussian noise. The resulting vibrations of the target reflectors produce glintlike pointing errors in the radar system. An extended Kalman filter is developed to estimate the positions of the target reflectors; this information is used to substantially reduce the pointing error due to glint. Data illustrating this glint reduction is given. The model is extended by the inclusion of clutter effects modeled in the same fashion as the glint phenomenon. The results presented indicate the limits of usefulness of this technique as a function of both receiver noise and relative clutter amplitude.     

Matched Filter Criteria and Range Weighting for Weather Radar

The effective weighting function for weather radar is defined. This weighting function considers the effects of both the transmitted signal and the receiver filter. It is used to assign effective ranges to samples taken at prescribed times. For uniformly distributed targets it is shown that "signal"-to-noise ratio depends on the receiver filter, transmitted signal envelope, and receiver noise spectral density. Maximization of this signal-to-noise ratio when range resolution constraints are imposed is discussed, and a receiver design approach specifically adapted for Doppler weather radars is developed.     

Theory of Adaptive Radar

This paper reviews the principles of adaptive radar in which both the spatial (antenna pattern) and temporal (Doppler filter) responses of the system are controlled adaptively. An adaptive system senses the angular-Doppler distribution of the external noise field and adjusts a set of radar parameters for maximum signal-to-interference ratio and optimum detection performance. A gradient technique for control of the radar array/filter weights is described and shown to generate weights which asymptotically approach optimum values. Simulation results illustrate the convergence rate of adaptive systems and the performance improvement which can be achieved.     

一种快速航空图像去雾算法

 基于暗元先验规律的图像去雾算法去雾效果较好,但在进行介质透射率估计时会造成图像中出现方块效应,所以需要进行图像抠图处理。而图像抠图计算复杂度非常高,使得图像去雾时间消耗很大。本文提出一种快速图像去雾算法,使用Kuwahara边缘-角点保持滤波器对大气散射光进行估计,并对所采用的Kuwahara滤波器进行改进。通过增加子块的数目以及进行局部加权等,提高边缘保留效果,抑制方块效应,从而获得较为准确的介质透射率。实验结果表明本文算法时间复杂度低,图像去雾效果好。     

The Estimation of the "Center of Gravity" of a Photon Density Profile in Noise

A model for an optical position estimation system is developed employing the photon Poisson process theory. The position estimate is based upon the definition of a center of gravity (CG) of the power density profile of the optical source on the focal plane. An estimator structure is derived using maximum likelihood estimates of the image profile. The resulting estimate of the CG is shown to be unbiased and its variance is obtained. The variance is shown to depend upon the signal energy and noise level as well as upon the distance of the center from the initial counting point. Thus, a composite estimation system is presented which reduces the variance and yet yields a simple structure. Studies on star estimation have yielded position accuracies better than 0.1 seconds of arc for a 2.5 visual magnitude star in a background of equivalent intensity.     

基于机器视觉与UMAC的自动铺丝成型构件缺陷检测闭环控制系统

为保证自动铺丝成型构件的性能,实现对成型构件表面质量的高效检测,本文基于机器视觉检测技术,自行研发自动铺丝成型构件表面缺陷检测闭环控制系统,使自动铺丝过程中预浸纱之间的间隙或重叠在允许范围内,从而保证铺丝精度。研究主要分为三个部分:铺丝成型构件表面图像提取与缺陷检测,检测数据传输,运动轴反馈控制,实现在自动铺丝过程中对成型构件表面缺陷检测实时闭环控制。针对电荷耦合相机采集到的预浸纱图像存在运动模糊和信噪比低等问题,将图像预处理划分为图像复原和降噪两大功能,根据不同类型的噪声采用对应滤波法进行降噪处理,提高了图像的信噪比,为后续检测提供高质量图像;预浸纱缺陷主要由其边缘直线这一几何特征进行表征,因此通过对预浸纱边缘检测实现缺陷识别;利用工控机向图像采集控制器发送命令实现图像采集,同时通过工控机与运动控制器之间信息流和数据流的交换实现检测数据的传输。探讨模糊控制理论用于闭环控制的研究,在反模糊化环节后面,加入自适应参数调节,以适应加工过程的突变,并成功地应用到自动铺丝缺陷检测闭环控制系统中,提高了伺服跟踪精度和跟踪实时性,从而提高铺丝精度。     

Calculation of Output Noise Variances for Discrete Time-Invariant Filters

Certain calculations to minimize output noise variance are introduced. Many applied problems in sampled data systems require that data be smoothed in the presence of noise for the prediction of future positions, velocities, or accelerations. Smoothing coefficients in discrete time-invariant filters are computed to minimize the output noise variance, but under the constraints that the function and derivatives be predicted ahead. The output noise variance is seen to be a function of the input noise, the number of input signals (N+1) that the filter has to smooth, and the prediction time ?T. Four examples are given in the derivation of smoothing coefficients for step and ramp inputs subjected to either almost white noise or Gaussian-Markoff noise. The examples illustrate the number of constraint relations that the filter smoothing coefficients must satisfy for function and/or derivative convergence under noise-free conditions. The smoothing coefficients are also a function of the type of noise input into the system or the discrete filter. From the examples, it can be observed that as N becomes larger, the output noise variance becomes smaller, but the computation time is increased.     

Kalman Filtering with Nonlinear State Constraints

An analytic method was developed by D. Simon and T. L. Chia to incorporate linear state equality constraints into the Kalman filter. When the state constraint was nonlinear, linearization was employed to obtain an approximately linear constraint around the current state estimate. This linearized constrained Kalman filter is subject to approximation errors and may suffer from a lack of convergence. We present a method that allows exact use of second-order nonlinear state constraints. It is based on a computational algorithm that iteratively finds the Lagrangian multiplier for the nonlinear constraints. Computer simulation results are presented to illustrate the algorithm.     

Observer-type Kalman innovation filter for uncertain linear systems

An observer-type of Kalman innovation filtering algorithm to find a practically implementable "best" Kalman filter, and such an algorithm based on the evolutionary programming (EP) optima-search technique, are proposed, for linear discrete-time systems with time-invariant unknown-but-hounded plant and noise uncertainties. The worst-case parameter set from the stochastic uncertain system represented by the interval form with respect to the implemented "best" filter is also found in this work for demonstrating the effectiveness of the proposed filtering scheme. The new EP-based algorithm utilizes the global optima-searching capability of EP to find the optimal Kalman filter and state estimates at every iteration, which include both the best possible worst case Interval and the optimal nominal trajectory of the Kalman filtering estimates of the system state vectors. Simulation results are included to show that the new algorithm yields more accurate estimates and is less conservative as compared with other related robust filtering schemes     

一种提高测量CCD成像系统MTF精度的数据处理方法

根据刃边图像的特点,采用中值滤波法、多剖线平均法以及局部滤波法对图像中的噪声进行前期处理,去噪效果好,使图像的有用信息损失小,提高了测量CCD成像系统调制传递函数的精度。实验表明,本文的数据处理方法能有效的提高测量CCD成像系统的传递函数的精度。     

自适应增量 Kalman 滤波方法

提出自适应增量Kalman滤波(AIKF)的概念和定义,建立自适应增量Kalman滤波模型及其分析方法,给出主要的计算步骤.传统自适应Kalman滤波(AKF)方法能够对事先未知的系统噪声和量测噪声的统计量进行有效的估计.但是,传统自适应Kalman滤波方法也无法对由于环境因素(如深空探测)的影响、测量设备的不稳定性等原因产生的未知时变测量系统误差进行补偿和校正,从而产生较大的滤波误差,甚至导致发散.提出的自适应增量Kalman滤波方法不但能够对系统噪声和量测噪声的统计量进行估计,而且还能成功消除这种测量系统误差,有效地提高滤波精度.该方法计算简单,便于工程应用.      

固体火箭发动机无损检测图像质量研究

详细介绍了利用工业CT进行固体火箭发动机无损检测中，提高图像质量方面的几点尝试－光轴对准、提高系统的信噪比、提高探测器效率、采用合适的硬滤手段和选用适当的图像滤波函数。给出了测试数据和处理前后的图像比较。上述几点尝度收到了较好的处理效果。     

含圆形分层损伤复合材料层合板在弯曲载荷作用下的屈曲行为研究

分层损伤是复合材料层合板结构最主要的损伤形式,其主要由于制造缺陷以及受到外力冲击而产生。本文对含圆形分层损伤复合材料层合板在弯曲载荷作用下的屈曲行为进行研究,首先利用RayleighRitz法对含圆形分层复合材料层合板进行二维模型建立,通过此理论模型可以计算出材料屈曲临界弯矩值以及在特定弯曲载荷下中心点的离面位移值。随后,采用三维数字图像相关方法对分层材料进行实验研究,得到了分层材料在弯曲载荷作用下的屈曲形貌以及其中心点的载荷—位移曲线。通过实验验证了理论的可行性与准确性,可用于对含圆形分层材料在弯曲载荷作用下屈曲临界弯矩以及中心点离面位移大小的初步估算。     

Steady state analysis for discrete tracking filters

An analysis of a discrete constant-gain α-β-γ tracking filter is presented. Steady-state tracking filter gains are determined without solving a discrete matrix Ricatti equation. Explicit closed-form gain solutions are found as a function of the roots to a cubic equation. Gain variations as a function of process noise, measurement noise, and sampling time are investigated     

考虑驾驶仪动态性能的指令滤波反演制导律

针对攻击机动目标的制导问题,设计了一种考虑自动驾驶仪性能、输入项约束的指令滤波反演制导律。首先,基于三维空间内弹目相对运动模型,采用反演递推方式设计制导律。针对传统反演控制存在的"微分膨胀"问题,引入指令滤波器对虚拟量进行过滤计算。考虑硬件计算能力的约束,引入自动驾驶仪二阶动力学模型减少控制过程延迟,并利用饱和函数和低通滤波器对输入项进行约束。此外,针对机动目标设计了一种扩张状态观测器来获取其加速度。通过Lyapunov理论证明了所设计闭环制导系统的稳定性。通过仿真实验验证了该制导律相有效性及优越性。     

Group-Complementary Array Coding for Radar Clutter Rejection

A radar waveform design technique which utilizes Lagrange's method of multipliers to control temporal sidelobes and to reduce Doppler sidelobes is described. This classical method of constrained optimization is applied to the problem of synthesizing a radar wave-form where mismatch loss is the objective function to be minimized. The associated constraints are taken from expressions for the composite temporal sidelobes of the cross-correlation response and the peak correlation response where sets of code words are used to modulate a series of radar pulses. The resulting code sets and receiver reference sets are called group-complementary and produce a trench parallel to or on the range axis of the cross-ambiguity surface.     

Error Probability for NCFSK with Linear FM Jamming

An expression is derived for the probability of error for a conventional binary, noncoherent, frequency-shift-key (NCFSK) communications system under the influence of bandpass Gaussian noise and a linear frequency-modulation jamming waveform. The resulting integral is expressed in terms of the well-known Q function, which depends upon average signal, noise, and jamming powers. The analytical procedures used can be applied to the analysis of the effects of other types of jamming.