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

在过去的几十年中，阵列处理技术已被证明是最活跃的研究课题之一，其本身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的电话（最近的美国FCC E911紧急要求）;以及用于改善通信系统性能的智能天线。本研究的重点是提高目前的最先进的阵列处理，特别是在检测和精确估计的位置嵌入在高度复杂的环境中的无源目标与强干扰和噪声。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，少量的天线元件（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在接收阵列处被记录，并且针对与探测环境相关的期望物理参数被处理。在传统的阵列处理中，多个目标通过不同的路径到达接收阵列是一个普遍现象，它严重降低了系统的性能。因此，大多数传统技术试图补偿多重散射（多径）的影响。在这项研究中，我采取了一种不同的方法，并解决了这样一个问题：如果一个数组处理算法探索了存在于观测场的时间结构中的附加信息（即，在多径延迟的集合中）。我的方法是基于时间反转（TR）用于开发新的TR为基础的阵列处理算法，在雷达和声纳系统，生物医学和无线通信的实际源定位应用。我的TR算法积极利用多径，以实现高分辨率和上级性能高达5dB的增益超过现有的国家的最先进的阵列处理。

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.