Quantitative Prediction of Sea Clutter Power Based on Improved Grey Markov Model
Zihao Chen; Bin Tian; Siyun Zhang; Quanjun Xu
The detection and prediction of sea clutter power is the basis of inversing atmospheric duct. At present, the technology of atmospheric duct within radar detection range is relatively perfect, but the long-distance inversion of atmospheric duct is limited by radar detection range, and the prediction of the echo power of the measured sea clutter is the basis of long-distance inversion of atmospheric duct. Based on the theory of weighted Markov model and grey Markov model, a weighted grey Markov model is constructed, and the sliding method is introduced to establish the sliding weighted grey Markov model. The relative error between the measured sea clutter power and predicted values of the above four models is calculated and analyzed using the experimental data collected. The results show that the sliding weighted grey Markov model has better accuracy not only in short-range prediction but also in long-distance prediction, which could provide data support for inversing atmospheric duct.
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