Interference control in sliding window detection processes using a Bayesian approach

Abstract

Recently a Bayesian approach has been introduced, for the design of non-coherent sliding window detection processes, to operate in X-band high resolution maritime surveillance radar scenarios. The classical problem of comparing a cell under test with a normalised measurement of the clutter level is re-interpreted in terms of a Bayesian predictive inference approach. Viewing unknown clutter parameters as statistical variables, it is possible to construct a Bayesian posterior distribution, using Jeffreys priors. This approach has permitted the construction of detection processes, with the constant false alarm rate property, in situations where this was previously difficult to achieve. However, in the presence of interference in the clutter cells, the detector degrades in performance, as do others constructed in more traditional ways. Here it will be shown how the Bayesian approach can be extended to produce sliding window detectors which are immune to the presence of interference.