A Stochastic Model for the Generation of Correlated Sea Clutter

Abstract

Maritime Conditions represent a challenging environment for radar detection due to the so-called sea clutter. It may lead to a lower probability of a correct target detection. Thus, a detailed modelling of sea clutter with its time-dependent correlations is crucial for evaluating the robustness of modern radar systems and their signal processing. This paper utilizes a stochastic approach to generate time-correlated sea clutter, dependent of the used radar system, the environment and the measuring geometry. Therefore, different models are used to determine the RCS of the illuminated sea surface, the time-dependent correlations and finally the statistical distribution of the received signal-amplitudes. Furthermore, bistatic radar geometries should be at the scope of this paper. Afterwards the simulated signal data is compared and validated with free accessible, recorded radar data from different locations and environmental conditions. The comparison with the correlation properties and probability density functions of the radar data shows good accordance with the data generated by the model. Furthermore the results show that generating sea clutter with the developed stochastic model and a minimum of basic observeable and available quantities (sea state, wind direction) is sufficient accurate and possible. By utilizing the presented method, time-correlated radar data, which imitates the different properties of real-world sea clutter, is generated in an efficient, less time consuming and reliable laboratory environment with a minimum of known environmental parameters.