Influence of high-resolution processing on background noise distribution in ship-borne radar

When a high-resolution algorithm is applied in a ship-borne radar, its non-linearity and distributional characteristics before high-resolution processing determine the distributional characteristics of background clutter after high resolution and detector design afterwards. Because background noise before high-resolution has physical significance, the statistical model of first-order Bragg lines and second-order components of sea clutter is put forward. Then, by using higher order cumulative quantity's statistical verification of actual measured data, it is concluded that the background noise before high resolution conforms to normal distribution in a ship-borne radar. The non-linearity of the high-resolution algorithm means that the background noise after high-resolution processing conforms to non-normal distribution. Non-normal-distributed clutter mainly includes Weibull, lognormal, and K-clutter. Rayleigh clutter can be seen as a special case of Weibull clutter. These clutter types have different statistical characteristics and can be discriminated by recognition of clutter characteristics. The numerical domain's distribution after high-resolution processing is determined by an improved, minimum entropy, clutter characteristics recognition method based on the AIC rule, namely, a two-parameter domain-scanning method. This identification method has a higher recognition rate. It is verified that the background noise after high-resolution by pre-whitened-constrained-MUSIC conforms to lognormal distribution.