This paper dwells upon optimizing the azimuth samp-ling interval of digital surface maps used to model radar ground clutter.The resulting equations can be used to find the digital map sampling interval for the require...This paper dwells upon optimizing the azimuth samp-ling interval of digital surface maps used to model radar ground clutter.The resulting equations can be used to find the digital map sampling interval for the required calculation error and modeled power of the simulated signal,which determines the resulting distribution of backscatter intensity.The paper further showcases how the sampling interval could be increased by pre-processing the map.展开更多
Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
基金supported by the Russian Foundation for Basic Research(19-37-90103).
文摘This paper dwells upon optimizing the azimuth samp-ling interval of digital surface maps used to model radar ground clutter.The resulting equations can be used to find the digital map sampling interval for the required calculation error and modeled power of the simulated signal,which determines the resulting distribution of backscatter intensity.The paper further showcases how the sampling interval could be increased by pre-processing the map.
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
