The Detection and Extraction of Features of Low Probability of Intercept Signals Using Quadrature Mirror Filter Bank Trees.
Abstract
A new type of spread spectrum intercept receiver is described which uses orthogonal 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1994
- Accession Number
- ADA315722
Entities
People
- Glenn E. Prescott
- Thomas C. Farrell
Organizations
- University of Kansas