Detection and estimation of changes in the parameters of a chirp signal

The problem is the detection and the estimation of abrupt changes in a chirp signal. In this case, an exact generalized likelihood ratio (GLR) test cannot be achieved, the system leading to the maximum likelihood estimates (MLE) of the parameters being nonlinear. The usual solutions are to derive a GLR assuming a piecewise stationary signal or to supervise estimated parameters of the chirp. We propose two solutions taking into account both slow and fast non-stationarities of the signal. The first consists of a GLR derived from a signal phase model approximation. The second keeps the exact model and uses an approximation of the LR. The delay to the detection is studied and a discussion on estimation of the parameters after change is included.