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，使用天线阵列的自适应空间滤波可以减少由快速时变的多径和未知同频干扰引起的衰落。这项研究正在追求一种灵活的框架，用于在不使用训练信号、阵列校准数据或所需或干扰信号的空间特征的知识的情况下自适应空间滤波器。它是从两个概念上不同的角度导出的：来自多元统计的典型相关分析，以及从接收数据的用户可编程变换获得的数据导出的训练信号的条件最大似然问题。该变换可以由用户编程，以基于接收到的信号展现一个或多个用户选择的统计特性的不同程度来分类和分离接收到的信号。许多这样有用的转变正在被研究中。新方法的性能正在通过分析和计算机模拟进行研究，以量化其信号分离、多径抑制和干扰抑制的能力。初步结果表明，新方法可以非常快地收敛到与使用完全已知的训练信号的MSE方法所获得的信号估计相当的信号估计。更广泛地说，这项研究的目的是开发和评估一种新的和非常通用的可编程盲自适应多元滤波方法，该方法除了在无线通信之外，还可以广泛应用于传感器阵列处理。

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.