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基于频率选择表面的毫米波压缩感知成像技术研究

发布时间:2018-10-05 20:18
【摘要】:压缩感知理论是一个介于数学与信息处理领域间的热门研究前沿,它能够在远小于奈奎斯特采样率的情况下实现信号采集,并能从少量的非相关测量值中高效率重构出原始信号,使其在无线传感器网络、数据重构、图像处理、雷达成像等方面的应用越来越广泛。测量矩阵是压缩感知理论步入实践的关键,它对少量测量值的获取和原始信号的准确重构起着举足轻重的作用,但因其硬件实现的高成本和复杂度,严重制约了压缩感知的推广应用。毫米波具有良好的穿透性能和较强的抗干扰能力,使得毫米波成像技术在安检、探测、反恐等领域拥有无可比拟的优势。因此,利用压缩感知理论的采样特点,研究出一种易于硬件实现、复杂度和成本较低、重构效率较高的毫米波成像体制具有及其重要的现实意义。本文在充分研究压缩感知理论和毫米波成像技术的基础上,围绕构建毫米波压缩感知成像体制,在以下几个方面进行了深入探讨:1、研究了具有带通/带阻特性的频率选择表面理论,并基于PIN二极管开关,设计出可调环路型FSS结构单元,研究了偏置电路对FSS结构的影响。仿真结果表明,在频率为37.5GHz的毫米波辐射下,利用PIN二极管控制这种FSS结构单元的开/关状态,其对应呈现出带通/带阻特性,实现单元处毫米波传输特性的控制。2、针对测量矩阵在毫米波压缩感知成像体制中的关键作用,仿真设计出可随机控制的10×10 FSS掩膜板结构,并将这种随机掩膜板放置于毫米波天线上,则可通过这种口径的掩模板获取多次不相关测量,构造出有效测量矩阵。本文通过软件仿真对不同结构的口径进行了200次有效测量,构造了一个200×256测量矩阵,分析了测量矩阵的性能。3、在研究毫米波压缩感知成像原理的基础上,利用重构算法对大小为16×16的原始图像进行恢复重构,验证了本文所提成像体制的可行性。仿真结果表明,这种成像方法易于从硬件上实现,复杂度和成本较低,能以较低测量次数实现较好的图像重构效果。
[Abstract]:The theory of compressed sensing is a hot research frontier between mathematics and information processing. It can realize signal acquisition when the sampling rate is far less than Nyquist sampling rate. And it can efficiently reconstruct the original signal from a small number of non-correlated measurements, making it more and more widely used in wireless sensor networks, data reconstruction, image processing, radar imaging and so on. Measurement matrix is the key of compression sensing theory in practice. It plays an important role in obtaining a small number of measurement values and accurately reconstructing the original signal. However, because of the high cost and complexity of its hardware implementation, the measurement matrix plays an important role in the acquisition of a small amount of measurement value and the accurate reconstruction of the original signal. It seriously restricts the application of compression perception. Millimeter wave has good penetration performance and strong anti-jamming ability, which makes millimeter wave imaging technology have unparalleled advantages in security inspection, detection, anti-terrorism and other fields. Therefore, it is of great practical significance to develop a millimeter wave imaging system, which is easy to implement in hardware, low complexity and cost, and high reconstruction efficiency, based on the sampling characteristics of compression sensing theory. Based on the research of compression sensing theory and millimeter wave imaging technology, this paper constructs a millimeter wave compression sensing imaging system. The following aspects are discussed in detail: 1. The frequency selective surface theory with band-pass / band-stop characteristics is studied. Based on the PIN diode switch, a tunable loop type FSS structure unit is designed, and the influence of bias circuit on the FSS structure is studied. The simulation results show that the PIN diode is used to control the on-off state of the FSS structure unit under millimeter wave radiation with frequency 37.5GHz, and the corresponding band-pass / band-stop characteristic is presented. To realize the control of millimeter wave transmission characteristics at the unit. Aiming at the key role of measurement matrix in millimeter wave compression sensing imaging system, a random control 10 脳 10 FSS mask structure is designed by simulation. When the random mask is placed on the millimeter-wave antenna, the effective measurement matrix can be constructed by using this aperture mask template to obtain several independent measurements. In this paper, 200 effective measurements of the aperture of different structures are carried out by software simulation, and a 200 脳 256 measurement matrix is constructed. The performance of the measurement matrix is analyzed. On the basis of studying the principle of millimeter-wave compression sensing imaging, The reconstruction algorithm is used to reconstruct the original image with the size of 16 脳 16, which verifies the feasibility of the proposed imaging scheme. The simulation results show that this imaging method is easy to be implemented in hardware, with low complexity and cost, and can achieve better image reconstruction effect with lower measurement times.
【学位授予单位】:国防科学技术大学
【学位级别】:硕士
【学位授予年份】:2016
【分类号】:TP391.41

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