CIF: Small: Collaborative Research: Signal Design for Low-Complexity Active Sensing

摘要：“本奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。”这项研究计划的动机是认识到传感器数据的量有望压倒摩尔定律所表达的硅技术的巨大性能改进。重点是通过信号设计的创新，开发一种低复杂性的非自适应图像形成替代方案。这些目标支持对天气模式进行更密切的监测，并可能导致对气候变化更详细的了解。它们还影响了从微波着陆系统到穿墙成像的更广泛的监视应用。该研究项目是高度跨学科的，信号处理是应用领域和序列设计数学之间的桥梁。当前的硬件允许传输跨空间、极化、时间和频率变化的波场，并且可以快速连续地改变。然而，遥感分辨率受到限制，不是硬件，而是远程图像形成的复杂性。该研究项目开发了新的信号设计原则，以最小的接收信号处理复杂性实现快速可靠的主动传感。传输的基本单位是由阵列元件和脉冲重复间隔索引的相位编码波形的统一矩阵，其中组成波形的极化可能会变化。互补波形作为这些矩阵的项出现。适当排序的统一波形矩阵在时间上消除了多普勒诱导范围副瓣，并提供弹性多径而不影响信号处理的简单性。互补波形的OFDM信号通过引入非线性信号处理，将静态副瓣交换为更动态的交叉项，从而提高了传统匹配滤波的性能。基于群论的数学框架的发展使新的互补序列的系统构造成为可能。

Abstract"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."This research program is motivated by the recognition that the volume of sensor data is expected to overwhelm even the enormous performance improvements in silicon technology expressed by Moore's Law. The focus is the development of a low-complexity alternative to non-adaptive image formation through innovations in signal design. The objectives support closer monitoring of weather patterns and may lead to a more detailed understanding of climate change. They also impact a wider range of surveillance applications from microwave landing systems to through-wall imaging. The research program is highly interdisciplinary with signal processing as the bridge between application domains and the mathematics of sequence design.Current hardware allows transmission of wavefields that vary across space, polarization, time and frequency and which can be changed in rapid succession. However, sensing resolution is limited, not by hardware, but by the complexity of remote image formation. This research program develops new signal design principles that enable fast and reliable active sensing with minimal receiver signal processing complexity. The basic unit of transmission is a unitary matrix of phase coded waveforms indexed by array element and by pulse repetition interval, where the polarization of constituent waveforms may vary. Golay Complementary waveforms appear as entries of these matrices. Appropriate sequencing of unitary waveform matrices in time eliminates Doppler induced range sidelobes and provides resilience to multipath without compromising the simplicity of signal processing. OFDM signaling of complementary waveforms improves performance beyond conventional matched filtering by introducing nonlinear signal processing that exchanges static sidelobes for more dynamic cross-terms. The development of a new mathematical framework based on group theory enables the systematic construction of new complementary sequences.