Optimum Active Array Processing Structure and Space-Time Factorability

An active array processor is concerned with the problem of detecting a signal echo, reflected from a target, in the presence of reverberation (clutter). The processor can also be used to estimate target range and bearing. It is a priori not evident whether the optimum (likelihood ratio) detector can be factored into spatial and temporal operations, thus resulting in a simpler processor implementation. This paper studies this problem for a linear continuous array in a reverberation-limited environment. Conditions on signal, reverberation, and array parameters are derived under which the optimum detector is factorable. The validity of using factorability as a criterion of signal design is briefly examined. Finally, the relationship between space-time factorability and range-bearing estimates is pointed out.     

Spatial Correlation of Reverberation Noise in Active Sonar

A linear array of hydrophones is considered for detecting a signal echo from a stationary target in the presence of reverberation. The structure of the optimum (likelihood ratio) detector is compared with that of a beamformer-matched filter detector. The conditions causing an increase in the spatial noise correlation between two hydrophones are the conditions under which the optimum spatial detector performs significantly better than the beamforming detector. A study of the space-time correlation function of reverberation shows that 1) a decrease in scatterer angular spread (or a narrowing of the receiver directivity pattern) tends to increase the spatial correlation, 2) if the scatterer Doppler spread is much less than the signal carrier frequency and if the angular spread is uniform, it is still possible to get a high correlation if the intersensor distance is much smaller than the carrier wavelength. These conditions indicate situations where optimum techniques may be worthwhile.     

Array shape estimation tracking using active sonar reverberation

This paper concerns the problem of array shape estimation and tracking for towed active sonar arrays, using received reverberation returns from a single transmitted CW pulse. Uniform linear arrays (ULAs) deviate from their nominal geometry while being towed due to ship maneuvers as well as ocean currents. In such scenarios, conventional beamforming performed under the assumption of a ULA can sometimes lead to unacceptably high spatial sidelobes. The reverberation leaking through the sidelobes can potentially mask weak targets in Doppler, especially when the target Doppler is close to that of the mainlobe reverberation and the reverberation-to-target ratio (RTR) is very high. Although heading sensors located along the array can be used to provide shape estimates, they may not be sufficiently available or accurate to provide the required sidelobe levels. We propose an array shape calibration algorithm using multipath reverberation returns from each ping as a distributed source of opportunity. More specifically, a maximum likelihood (ML) array shape calibration algorithm is developed, which exploits a deterministic relationship between the reverberation spatial and Doppler frequencies causing it to be low rank in the space-time vector space formed across a single coherent processing interval (CPI). In this application, a sequence of overlapped CPI length snapshots of duration less than the CW pulse is used. The ML estimates obtained for each snapshot are tracked using a Kalman filter with a state equation corresponding to the water pulley model for array dynamics. Simulations performed using real heading sensor data in conjunction with simulated reverberation suggest that 8-10 dB improvement in sidelobe level may be possible using the proposed array shape tracking algorithm versus an algorithm that uses only the available heading information.     

LMI approach to the mixed H2/H∞filtering design for discrete-time uncertain systems

The problem of full-order robust filtering design for discrete-time uncertain linear systems is addressed. The uncertain parameters are assumed to belong to convex bounded domains (polytope type uncertainty). The main purpose is to design a stable linear filter such that the filtering error output signal remains bounded. For that, the parameterization of all linear filters assuring quadratic stability with an H_∞ attenuation constraint to the filtering error system is provided in terms of linear matrix inequalities (LMIs). Then, through the definition of an auxiliary cost, an upper bound to the filtering error variance is minimized, providing a mixed H₂/H _∞ guaranteed cost filtering design. Standard optimization procedures with global convergence assured can be used to solve the problem, as illustrated by an example     

Optimum Realizable Continuous Range Estimation

The ability to detect the presence or absence of a target is no longer the fundamental design criterion when the vehicle to be tracked is cooperative. In spacecraft tracking or navigation systems, for example, emphasis is placed on post-acquisition performance. Therefore, classical radar theory and design techniques are not specifically applicable. On the other hand, there are optimization techniques for extracting the tracking data from noise that are more to the point. In particular, optimum demodulation theory is directed specifically to the problem of continuously extracting data from a nonlinear modulation process. In this paper, the tracking properties of a multitone PM ranging signal are reviewed and are shown to be nearly optimum for cooperative vehicles. An optimum, but nonrealizable, maximum a posteriori (MAP) continuous estimator of range is derived for this signal. The linearized model of this receiver is the optimum nonrealizable Wiener filter for the data. Interpretation of this optimum nonrealizable estimator leads to a receiver design that is both practical and intuitively satisfying. With the aid of post-detection processing in the Wiener-Hopf sense, almost optimum performance is obtained from the resulting receiver, above threshold.     

Mismatched Filtering of Sonar Signals

A replica correlator (matched filter) is an optimum processor for a receiver employing a pulse of continuous wave (CW) signal in a white Gaussian noise background. In an active sonar, however, when the target of interest has low Doppler shift and is embedded in a high reverberation background, this is not so. High sidelobes of the correlator frequency response pass a significant portion of the signal contained in the mainlobe of the reverberation spectrum. In order to reduce the sidelobes of the correlator output spectrum and at the same time keep the increase in its 3 dB bandwidth to a small amount, we propose lengthening of the replica of the transmitted signal and weighting it by a Kaiser window. It is demonstrated that by extending the weighted replica by 50 percent compared with the transmitted signal, it is possible to reduce the sidelobe levels to at least 40 dB below the mainlobe peak, with the concomitant increase of the 3 dB band-width by less than 5 percent. The degradation in signal-to-noise ratio (SNR) performance for such a ?mismatched? filter receiver with respect to the matched filter is less than 1.5 dB.     

宽带认知雷达低峰均比波形快速设计算法

发射波形设计是宽带认知雷达系统的关键技术。为了提高宽带认知雷达系统对距离扩展目标的检测性能,建立了目标检测模型,分析了系统的检测性能,在此基础之上研究了基于最大输出信干噪比(SINR)的低峰均比(PAR)波形设计算法。通过将原波形优化问题等效为接收权值与低峰均比波形的联合优化问题,同时利用循环优化的思想,提出了一种低峰均比波形快速设计算法。相比于现有的梯度法以及凸优化算法,该算法所设计的恒模波形信干噪比与二者相当,但算法实现难度明显变小,计算复杂度明显降低。仿真结果证实了算法的有效性。     

柔性转子的优化平衡

本文提出一种柔性转子优化平衡准则—有约束的最小应变能准则,它能满足航空燃气涡轮发动机结构强度和性能一体化设计的要求。应用该准则时,平衡校正量(大小和方位)是优化参数,转子—支承系统的总应变能为目标函数;转子若干截面的振动幅值作为约束条件。选用了鲍威尔法和网格随机射线法,进行优化计算。编制了优化全过程的FORTRAN程序,并经算例和实验考核、验证。      

涡扇发动机早期退化性能的线性变参数估计

针对涡扇发动机线性变参数(Linear parameter varying,LPV)模型,给出了一种新的早期退化航空发动机部件性能LPV滤波器设计方法.该方法采用仿射依赖于参数的二次Lyapunov函数,在仿射二次稳定性的基础上,引入多凸性引理将滤波器求解问题转化为线性矩阵不等式(Linear matrix inequalities,LMI)约束下的凸优化问题,避免了求解参数化线性矩阵不等式(Parameterized linear matrix inequalities,PLMI)约束下的优化问题.针对某型早期退化涡扇发动机的仿真表明,该方法能以较高精度估计性能退化参数,且鲁棒性强,增益调度简单,具有一定的工程意义.      

双调和方程在航空离心泵叶型优化设计的应用

为了减少构建代理模型的计算量,提高优化效率,基于双调和方程模型和混合人工鱼群算法对航空离心泵叶型进行优化改型设计。在Matlab平台下分别采用5点4次Bezier曲线和线性函数控制叶型圆周角分布和积叠变化规律,通过软件UG和Fluent的联合批处理方法对15组设计结果进行内流场数值仿真。在曲面插值获得计算空间边界条件的基础上,采用中心差分格式对双调和偏微分方程进行数值求解,建立超曲面性能代理模型。以效率最高为目标函数基于人工鱼群算法对设计变量进行全局寻优。结果表明:基于双调和方程的超曲面代理模型能够保证试验值与预测值完全一致,而优化后的离心叶轮流动中的尾迹效应被明显减弱,水力效率比原型泵提高5.4%。      

存在外部干扰的网络控制系统故障检测和优化

针对存在时延和丢包的网络控制系统,研究了系统的故障检测滤波器设计和优化设计问题.通过泰勒展开将未知时延处理成外界干扰,采用伯努利随机过程来描述丢包现象.设计观测器产生残差信号,将故障检测问题转化为H∞滤波问题.通过Lyapunov函数方法分析了系统的稳定性.以线性矩阵不等式的形式给出了滤波器存在的充分条件和求解方法.为进一步提高系统对故障信号的灵敏度,采用了一种优化设计方法对故障检测系统进行了优化.最后通过仿真验证了算法的有效性.     

桥联重积分方程一种新的数值方法

纤维增强复合材料断裂力学中的桥联问题常常可归结为一个二重积分方程。常见的求解方法有矩阵迭代法和积分迭代法，但这两种方法都产复杂。本文给出一种新的分段插值方法，对此积分方程进行求解。数值计算结果表明，该方法效果令人满意。     

功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势,可以更加充分地利用频谱资源。设计了一种新的一体化波形,在实现通信符号传递的同时,利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出,其中以星座图上的范数误差衡量通信性能,以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际,在问题求解时同时考虑了波形总功率约束和波形恒模约束,并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。     

功率约束下低相关旁瓣的通导一体化波形研究

通信导航一体化是未来无线系统的发展趋势，可以更加充分地利用频谱资源。设计了一种新的一体化波形，在实现通信符号传递的同时，利用其进行时延测距进而实现相应的定位导航功能。一种联合的优化目标函数被提出，其中以星座图上的范数误差衡量通信性能，以自相关函数的加权积分旁瓣电平衡量波形的定时性能。结合一体化系统的实际，在问题求解时同时考虑了波形总功率约束和波形恒模约束，并采用变量交替迭代优化的算法进行迭代求解。最后利用数值仿真验证了算法的有效性。     

边界元法分析回转体的自由扭振问题

 边界元法用于分析非线性问题和动力问题时,在最终得到的积分方程中同时包含边界积分和区域积分。通常的做法是对区域积分项采用常值有限元离散,这需要用很密的网格才能达到较高的精度。     

基于近似技术的高亚声速运输机机翼气动/结构优化设计

探索基于近似技术的高亚声速运输机机翼气动/结构多学科设计优化方法,建立了基于近似技术的多学科设计优化框架。气动学科采用全速势方程加黏性修正进行翼身组合体跨声速流动的气动计算,结构学科采用有限元分析方法进行应力与变形计算。采用均匀设计法给出若干样本点,分别采用二次响应面、Kriging模型和径向基神经网络等多种近似技术,构造气动学科和结构学科的近似分析模型,并对几种近似模型精度进行了分析和比较。研究发现,Kriging模型和二次响应面具有几乎等同的较高的近似精度,神经网络的近似精度则较差,由于二次响应面计算量更小,故最终选定为机翼设计优化的近似方法。以升阻比和结构重量为目标,考虑升力、机翼面积以及应力和应变约束条件,对运输机机翼4个外形参数和4个结构参数进行多目标、多约束优化设计。优化后的机翼具有较好的气动/结构综合性能,表明本文方法是可行的。     

An Adaptive Threshold System for Nonstationary Noise Backgrounds

The problem of detecting target signals in an ocean environment using active sonar is complicated by the nonstationary background which usually consists of both ambient ocean noise and reverberation. on. In this paper a signal processing system capable of detecting a signal in nonstationary noise is introduced. This system makes use of the mean and variance time functions of the nonstationary noise background in order to design estimation filters which will cope with the nonstationarity. Appropriate statistics of the noise and signal (tone burst) plus noise have been obtained and are used to determine the probabilities of false alarm and detection and the receiver operating characteristics.     

多指灵巧手考虑渐近稳定性的最优抓持规划

基于抓持刚度和关节刚度、抓持阻尼和关节阻尼的概念,采用拉格朗日方程推导了多指抓持系统的小位移干扰方程并对其进行了模态分析,按照最佳稳定性为目标对多指灵巧手抓持进行了最优化设计以得到最佳的抓持姿态。以 BH-2类人手抓持一圆柱体作为算例显示方法的实用性和有效性     

Navigation system design using time-varying complementary filters

A new methodology for the design of navigation systems for autonomous vehicles is introduced. Using simple kinematic relationships, the problem of estimating the velocity and position of an autonomous vehicle is solved by resorting to special bilinear time-varying filters. These are the natural generalization of linear time-invariant complementary filters that are commonly used to properly merge sensor information available at low frequency with that available in the complementary region. Complementary filters lend themselves to frequency domain interpretations that provide valuable insight into the filtering design process. This work extends these properties to the time-varying setting by resorting to the theory of linear differential inclusions and by converting the problem of weighted filter performance analysis into that of determining the feasibility of a related set of linear matrix inequalities (LMIs). Using this set-up, the stability of the resulting filters as well as their "frequency-like" performance can be assessed using efficient numerical analysis tools that borrow from convex optimization techniques. The mathematical background that is required for complementary time-varying filter analysis and design is introduced. Its application to the design of a navigation system that estimates position and velocity of an autonomous vehicle by complementing position information available from GPS with the velocity information provided by a Doppler sonar system is described.     

Optimization of point target tracking filters

We review a powerful temporal-based algorithm, a triple temporal filter (TTF) with six input parameters, for detecting and tracking point targets in consecutive frame data acquired with staring infrared (IR) cameras. Using an extensive data set of locally acquired real-world data, we used an iterative optimization technique, the Simplex algorithm, to find an optimum set of input parameters for a given data set. Analysis of correlations among the optimum filter parameters based on a representative subset of our database led to two improved versions of the filter: one dedicated to noise-dominated scenes, the other to cloud clutter-dominated scenes. Additional correlations of filter parameters with measures of clutter severity and target velocity as well as simulations of filter responses to idealized targets reveal which features of the data determine the best choice of filter parameters. The performance characteristics of the filter is detailed by a few example scenes and metric plots of signal to clutter gains and signal to noise gains over the total database