SEA clutter & CHAOS: Improved surrogate-data tests

Currently there is contention as to the nature of sea clutter for high resolution radar. Conventionally, sea clutter has been modelled as a compound stochastic k-distribution, originally suggested by Ward et al. However, recent work by Haykin et al. has suggested that the clutter can be modelled as a nonlinear deterministic process, otherwise referred to as a chaotic process. The paper presented here uses a new surrogate test which is designed specifically for this problem. The test is designed with a null hypothesis (H
0
= The data can be approximated to by a compound stochastic k-distribution). Therefore, acceptance of such a test will accept the conventional k-distribution as a viable model sea clutter. In addition, a new surrogate statistic is introduced which is used to reject/accept the null hypothesis. This statistic is the normalised mean square error(NMSE) from a predictor and is a statistic which can be applied to any type of time-series. An overview of the method is presented together with results for a number a sea clutter data sets.