Programmable Blind Adaptive Multivariate Filtering

在无线通信中，包括蜂窝通信系统、扩频覆盖系统和信号智能应用，由快速时变的多径和未知的同信道干扰引起的降级可以通过使用天线阵列的自适应空间滤波来减小。 这项研究正在寻求一个灵活的框架，用于适应空间滤波器，而不使用训练信号，阵列校准数据，或所需的或干扰信号的空间特性的知识。 它来自两个概念上不同的观点：从多元统计的典型相关分析，和条件最大似然问题的数据导出的训练信号从用户可编程的转换接收到的数据。 该变换可以由用户编程，以基于所接收的信号表现出一个或多个用户选择的统计特性的不同程度来对所接收的信号进行分类和分离。 许多这样有用的转变正在研究之中。 新方法的性能正在研究分析和计算机模拟，以量化其信号分离，多径缓解和干扰抑制的能力。 初步结果表明，新的方法可以收敛得非常快，产生的信号估计是可比的MSE方法，使用完全已知的训练信号。 更一般地说，本研究的目的是开发和评估一种新的和非常普遍的方法，可编程盲自适应多元滤波，具有广泛的应用，传感器阵列处理，除了无线通信。

In wireless communications, including cellular communication systems, spread spectrum overlay systems, and signals intelligence applications, the degradation caused by rapidly time-varying multipath and unknown cochannel interference can be reduced by adaptive spatial filtering using antenna arrays. This research is pursuing a flexible framework for adapting a spatial filter without using a training signal, array calibration data, or knowledge of spatial characteristics of the desired or interfering signals. It is derived from two conceptually different perspectives: canonical correlation analysis from multivariate statistics, and the conditional maximum likelihood problem for a data-derived training signal obtained from a user-programmable transformation of the received data. The transformation can be programmed by the user to sort and separate the received signals on the basis of the differing degrees to which they exhibit one or more user-selected statistical properties. Many such useful transformations are being examined. The performance of the new method is being investigated analytically and by computer simulations to quantify its capabilities of signal separation, multipath mitigation, and interference rejection. Preliminary results suggest that the new method can converge very quickly to yield signal estimates that are comparable to those obtained by the MSE method that uses perfectly known training signals. More generally, the objective of this research is to develop and evaluate a new and very general approach to programmable blind adaptive multivariate filtering that has broad application to sensor array processing in addition to wireless communications.