Array Signal Processing: Estimator Design and Experiments

Kaveh这项研究建立在实验室空中超声阵列的建造和校准过程中获得的经验的基础上，以便建立一种系统的方法进行实验和理论分析。优化泛函正在为一类具有与著名的MUSIC方法相似的计算负担的估计器而开发。与MUSIC等方法相比，这些估计器有望显著降低一般校准阵列的门限信噪比。正在建立一个概率框架内的分析技术，用于比较这类估计者的分辨率阈值。检测方法也正在与实验测量相结合，以最大限度地利用阵列校准数据。新算法正在推广到涉及宽带信号和具有循环平稳性等特殊特性的信号的情况。正在进行的实验工作，包括在DSP处理器上实现子空间估计算法，旨在建立许多所提出的方法的实用水平。

Kaveh This research builds on experience that has been gained during the construction and calibration of a laboratory ultrasound-in-air array, in order to establish a systematic approach for experimentation and theoretical analysis. Optimizing functionals are being developed for a general class of estimators with similar computational burden as the well-known method of MUSIC. These estimators are expected to significantly reduce the threshold signal to noise ratio, for a general calibrated array, over a method such as MUSIC. Analysis techniques are being established within a probabilistic framework for comparing the resolution thresholds of estimators in this class. Detection methods are also being developed in conjunction with experimental measurements that make optimum use of the array calibration data. The new algorithms are being generalized to cases involving wideband signals and signals possessing special characteristics such as cyclostationarity. The ongoing experimental work, which includes the implementation of subspace estimation algorithms on DSP processors, is intended to establish the level of practicality of many proposed methods.