Adaptive chaotic maps for identification of complex targets

Identification of complex targets in radar or sonar is a difficult problem. The author shows how the parameters of a simple chaotic map may be optimised to increase the cross correlation of a transmitted signal with the reflection from one target while decreasing the cross correlation with another target. The targets consist of simple arrays of point scatterers. The author shows that the optimisation process produces a chaotic signal with a power spectrum that maximises the ratio of the cross correlation with one target to the cross correlation with a different target, however the author also shows that the specific time ordering of the chaotic signal is also important in determining the cross correlation. The performance of the chaotic signal is better than a random signal with the same power spectrum. The author also shows an example of applying these methods to targets that are more complex.