Chaotic signals for wideband radar imaging

We explore the characteristics of chaos for wideband radar imaging. Chaos can be generated via nonlinear functions that produce statistically independent samples with invariant probability density functions. By feeding this type of chaos to the input of a voltage-controlled oscillator, a stochastic frequency modulated signal with fractal features is generated. The FM signal is an ergodic and stationary process with initial random phase. The power spectral density of such signal is typically broadband. We show that the time autocorrelation associated with the FM signal provides high range resolution for zero Doppler and dies out rapidly for increasing Doppler shifts. Furthermore, we show that a set of realizations of the signal can be processed into a set of ambiguity surfaces that when averaged yield a low self-noise pedestal.