Algebraic spectral moments based moving clutter parameter estimation and clutter suppression

Oktar, Onur
In many modern radar systems, it is desired to detect the presence of targets in the interference which includes clutter and noise. Various signal processing techniques are proposed to effectively suppress the clutter and increase the signal to interference ratio. To achieve optimum suppression, radar system must know clutter characteristics and process the radar echoes based on these characteristics. For ground radars, the clutter environment characteristics are relatively stable and predictable. These characteristics can be stored in radars memory and optimum clutter suppression can be achieved. However, for maritime radars, dealing with sea clutter is a rather big problem since its characteristics changes over time according to change in velocity vector of wind, grazing angle etc. In such a case, a radar needs to adapt itself to changing clutter environment to achieve good clutter suppression. The bigger problem arises when both the rain clutter and the sea clutter coexists since they are differently affected by environmental conditions and radar parameters. In these environments, adaptive estimation of both clutter characteristics to suppress the interference becomes obligatory if high-performance target detection is needed. In this study, parametric clutter parameter estimation techniques are considered and the performance of algebraic spectral moments based moving clutter parameter estimation technique is investigated for different conditions. To compare the clutter suppression of the algebraic spectral moments based moving clutter parameter estimation technique with that of more conventional methods, improvement factor (IF) is used as the figure of merit.


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Citation Formats
O. Oktar, “Algebraic spectral moments based moving clutter parameter estimation and clutter suppression,” M.S. - Master of Science, Middle East Technical University, 2014.