Adaptive Detection and Parameter Estimation for Multidimensional Signal Models 论文

摘要

The problem of target detection and signal parameter estimation in a background of unknown interference is studied, using a multidimensional generalization of the signal models usually employed for radar, sonar, and similar applications. The required techniques of multivariate statistical analysis are developed and extensively used throughout the study, and the necessary mathematical background is provided in Appendices. Target detection performance is shown to be governed by a form of the Wilks' Lambda statistic, and a new method for its numerical evaluation is given which applies to the probability of false alarm of the detector. Signal parameter estimation is shown to be directly related to known techniques of adaptive nulling, and several new results relevant to adaptive nulling performance are obtained.