"Time Reversal Signal Processing: Applications in Radar, Biomedicine, and Wireless Communications"

在过去的几十年里，阵列处理技术已被证明是最活跃的研究课题之一，从航空航天应用发展到许多其他方面，包括：用于监视的传感器网络；用于定位感兴趣对象的麦克风和地震阵列；用于定位电话用户的移动电话(美国联邦通信委员会最近的E911紧急要求)；以及用于提高通信系统性能的智能天线。本研究致力于改善阵列处理的最新技术，特别是在强干扰和强噪声的高度复杂环境中检测和准确估计无源目标的位置。感兴趣的应用包括生物医学(乳腺癌检测)、雷达/声纳系统(目标定位和跟踪)和无线通信(改进的发射器/接收器设计，以增强系统性能)。 在传统的阵列处理中，少数天线单元，统称为发射阵列，探测环境。由环境的不同部分散射或反射的波被记录在接收阵列上，并被处理以获得与被探测环境有关的所需物理参数(S)。在传统的阵列处理中，一个显著降低系统性能的常见现象是多个目标反射通过不同的路径到达接收阵列。因此，大多数传统技术试图补偿多个散射(多路径)的影响。在这项研究中，我采取了一种不同的方法，并解决了如果阵列处理算法探索存在于观察场的时间结构中的附加信息(即，在多径延迟集合中)以利于其获得的问题。我的方法基于时间反转，用于开发新的基于时间反转的阵列处理算法，用于雷达和声纳系统、生物医学和无线通信中的实际信号源定位应用。我的TR算法充分利用了多路径的优势，获得了比现有最先进的阵列处理技术高达5db的高分辨率和更高的性能。

In the past few decades, array processing technology has proven to be one of the most active research subjects evolving itself from aerospace applications to many other dimensions including: sensor networks for surveillance; microphone and seismic arrays to localize objects of interest; mobile phones to locate phone users (a recent US FCC E911 emergency requirement), and; smart antennas to improve communication systems' performance. This research focuses on improving the current state-of-the-art in array processing in particular in the detection and accurate estimation of the locations of passive targets embedded in highly complex environments with strong interference and noise. Applications of interest include biomedicine (breast cancer detection), radar/sonar systems (target localization and tracking), and wireless communications (improved transmitter/ receiver design for enhanced system performance). In traditional array processing, a small number of antenna elements, collectively referred to as the transmit array, probe the environment. The waves scattered or reflected by different sections of the environment are recorded at the receive array and are processed for the desired physical parameter(s) related to the probed environment. A common phenomena in traditional array processing that significantly degrades the system's performance is multiple target reflections reaching the receive array through differnt paths. Consequently, most traditional techniques attempt to compensate for the effect of multiple scattering (multipath). In this research, I take a different approach and address the question of what can be gained if an array processing algorithm explores the additional information existing in the temporal structure of the observed fields (i.e., in the set of multipath delays) to its advantage. My approach is based on time reversal (TR) used to develop new TR based array processing algorithms for practical source localization applications in radar and sonar systems, biomedicine, and wireless communications. My TR algorithms makes positive use of multipath to achieve high resolution and superior performance up to a gain of 5dB over the existing state-of-the-art in array processing.