Optimizing chaos-based signals for complex radar targets

Abstract

There has been interest in the use of chaotic signals for radar, but most researchers consider only a few chaotic systems and how these signals perform for the detection of point targets. The range of possible chaotic signals is far greater than what most of these researchers consider, so to demonstrate this, I use a chaotic map whose parameters may be adjusted by a numerical optimization routine, producing different chaotic signals that are modulated onto a carrier and optimized for different situations. It is also suggested that any advantage for these chaos-based signals may come in the detection of complex targets, not point targets, and I compare the performance of chaos-based signals to a standard radar signal, the linear frequency modulated chirp. I find that I can optimize a chaos-based signal to increase the cross-correlation with the reflection from one complex target compared to the cross-correlation with the reflection from a different target, thus allowing the identification of a complex target. I am also able to increase the cross-correlation of the reflection from a complex target compared with the cross-correlation with the reflection from spatially extended clutter. I show that a larger output signal-to-noise ratio is possible if I cross-correlate with a reference signal that is different from the transmitted signal, and I justify my results by showing how the ambiguity diagram for a chaos-based signal can be different than the ambiguity diagram for a noise signal. © 2007 U.S. Government.