Detection and Extraction of Features of Low Probability of Intercept SignalsUsing Quadrature Mirror Filter Bank Trees

摘要

A new type of spread spectrum intercept receiver is described which usesorthogonal Wavelet techniques and a Quadrature Mirror Filter (QMF) bank tree to decompose a waveform into components representing the energy in rectangular tiles in the time frequency plane. By simultaneously examining multiple layers of the tree, the dimensions of concentrations of energy can be estimated with a higher resolution than is normally associated with linear transform techniques. This allows detection and feature extraction even when the interceptor has little knowledge of specific parameters of the signal being detected. In addition, the receiver can intercept and distinguish between multiple signals. For each category of spread spectrum, the receiver estimates the energy cells' positions in the time frequency plane, the cells' bandwidths, time widths and signal to noise ratios, and the energy distribution within each cell. With this information, a classifier can then determine how many transmitters there are, and which cells belong to each. In this report, algorithms are described for detecting and extracting features for each of the spread spectrum signal formats. These algorithms are analyzed mathematically and the results are verified with simulation. The detection abilities of these algorithms are compared with other spread spectrum detectors hat have been described in the literature.