DNA computing from a signal processing viewpoint

In this article, an analysis of Adleman's experiment and a review of DNA computing applications from a signal-processing point of view are provided. In addition, certain key parts of DNA computing are emphasized, such as the code word design, to which the application of signal processing theory and techniques can offer significant advantages. The goal of this article is to introduce to the signal processing community a new unexplored area of research.     

Knowledge-based radar signal and data processing: a tutorial review

Radar systems are an important component in military operations. In response to increasingly severe threats from military targets with reduced radar cross sections (RCSs), slow-moving and low-flying aircraft hidden in foliage, and in environments with large numbers of targets, knowledge-based (KB) signal and data processing techniques offer the promise of significantly improved performance of all radar systems. Radars under KB control can be deployed to utilize valuable resources such as airspace or runways more effectively and to aid human operators in carrying out their missions. As battlefield scenarios become more complex with increasing numbers of sensors and weapon systems, the challenge will be to use already available information effectively to enhance radar performance, including positioning, waveform selection, and modes of operation. KB processing fills this need and helps meet the challenge.     

Wave-oriented processing of scattered field data from aplane-wave-excited finite array of filaments on an infinite dielectricslab

In a companion paper, we presented the formulation and solution for time-harmonic plane wave fields scattered by truncated periodic and aperiodic arrays of infinitely long filaments on an infinite dielectric slab. The solution was constructed so as to highlight the coupled phenomenologies associated with slab loading of the Floquet mode beams characteristic of the truncated arrays and with the slab-guided leaky modes excited by these arrays. Asymptotic reduction of the solution yielded a parameterization of the scattered fields and a numerically accurate algorithm, based on physically observable ray- and mode-field constituents. This study is concerned with the inverse procedure of extracting from the scattered field data the phenomenological footprints of the scattering mechanisms found by forward problem asymptotics; this information is relevant to target classification and identification. The data processing tools involve Gaussian windowed transforms and superresolution algorithms that yield projections onto appropriate subdomains of the (space)-(spectral wave number) phase space. A variety of examples demonstrate physically and quantitatively the interplay of Floquet-mode and leaky-mode phenomena, and how these are affected by changes in the problem parameters. Of special interest is the performance of superresolution algorithms for “cleaning up” the diffuse Gaussian windowed phase space distributions, in the absence and presence of system noise     

基于多激光光束后向散射的大气风场检测和时域信号分析

系统地研究了一种基于后向散射信号的光学闪烁机理的多激光光束风场测量（MLBM）系统及其性质。在实时检测过程中,使用光学互相关方法对信号进行分析得出了固定距离200m处的近场风速及风向信息;同时,测量并计算了在不同时刻和不同系统摆放情况时的风速。实验结果表明,测量得到的风速与参照风速之间的相对误差小于5％。     

基于降维算法从少量测量数据中重构温度场

由于测量环境及测量技术的制约,工业中温度信息的获取主要依据少量测点数据,难以得到被测对象完整温度信息。计算方法可以获得被测对象完整温度信息,但计算量大,信息再现实时性差。为了解决这个问题,实现快速、有效、准确的实时温度分布测量,提出一种基于Gappy POD低维表示的温度分布降维重建算法,从少量局部温度测量数据准确中重建温度场,并分析采用上述算法进行温度场重构时POD基个数、测点数量和测点位置对其的影响。通过双峰温度场模型重建结果和误差分析表明,重建误差在1×10^-10以下,且该算法显著地减少了测量传感器的数量,降低了温度分布测量的复杂性与测量成本,为工业测量中数据缺失提供新的解决思路。