Intersections of multiple cone classes for signal modeling and detection

The use of cone classes for signal detection and estimation is relatively new. Cone classes and the cone detector have shown potential as a viable alternative to subspace detection. The addition of new quadratic forms that model a wider range of signal characteristics, and the extension to using intersections of single cones, now makes it possible to apply cone classes to a wider range of practical problems. These extensions have resulted in a number of different types of intersection classes. Each type requires a different algorithm to implement the generalized likelihood ratio test (GLRT) used for signal detection. The authors classify these types and outline the possible solutions to implement the GLRT. New examples of signal classes modeled using cones are also given