Engineering Creativity Award: Maximum Likelihood Applied to Spectrum Estimation

研究涉及平稳高斯随机过程有限样本问题的谱估计工作。重点是实现小偏差和低方差估计的一般方法。理论工作在三个方面：1)通过晶格滤波器实现，2)最大熵扩展，3)噪声中的复指数。研究还包括多信号阵列处理、波束形成和延迟多普勒雷达成像，以及将这些信号处理算法映射到并行架构。本项目为“工科本科生创意奖”资助项目。

The research deals with work in spectrum estimation for problems involving finite samples from stationary Gaussian stochastic processes. Emphasis is on the general method for achieving estimators with small bias and low variance. Theoretical work is in three areas: 1) Implementation via lattice filters, 2) Maximum-entropy extension, 3) Complex exponentials in noise. Investigations also involve multi-signal array processing, beamforming, and delay-doppler radar imaging along with mapping of these signal processing algorithms to parallel architectures. This project is one supported under the Creativity Awards for Undergraduate Engineering Students.