Conventional PI control encounters some problems when dealing with large lag process in the presence of parameter uncertainties.For the typical first-order process,an observerbased linear active disturbance rejection ...Conventional PI control encounters some problems when dealing with large lag process in the presence of parameter uncertainties.For the typical first-order process,an observerbased linear active disturbance rejection control（LADRC） scheme is presented to cope with the difficulties,and a reduced-order observer scheme is proposed further.Some quantitative dynamic results with regard to non-overshoot characteristics are obtained.Finally,the performance boundaries of LADRC and PI control are explicitly compared with each other,which shows that the former is more superior in most cases.展开更多
To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in r...To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.展开更多
最小二乘逆时偏移(least-squares reverse time migration,LSRTM)具有更高的成像分辨率、振幅保真性及均衡性等优势。然而,目前的LSRTM算法大多基于水平地表假设,在面对复杂地形时无法很好地适应剧烈的起伏地表。基于二阶常密度声波方程...最小二乘逆时偏移(least-squares reverse time migration,LSRTM)具有更高的成像分辨率、振幅保真性及均衡性等优势。然而,目前的LSRTM算法大多基于水平地表假设,在面对复杂地形时无法很好地适应剧烈的起伏地表。基于二阶常密度声波方程的LSRTM算法忽略了密度变化对振幅的影响,很难在变密度介质中取得保真的成像结果。为此,从一阶速度-应力方程出发,在曲线坐标系下推导相应的扰动方程和伴随方程,并通过伴随状态法给出梯度更新公式,最终实现基于贴体网格的起伏地表LSRTM算法。模型试算验证了算法的有效性和对复杂地表的适应性。结果表明,提出的算法能够消除起伏地表的影响、压制低频噪声、恢复高频成分、均衡成像振幅,实现地下变密度介质的高分辨率和高保真度成像。展开更多
基金supported by the National Natural Science Foundation of China(60774088)the National High Technology Research and Development Program of China(863 Program)(2009AA04Z132)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20090031110029)
文摘Conventional PI control encounters some problems when dealing with large lag process in the presence of parameter uncertainties.For the typical first-order process,an observerbased linear active disturbance rejection control（LADRC） scheme is presented to cope with the difficulties,and a reduced-order observer scheme is proposed further.Some quantitative dynamic results with regard to non-overshoot characteristics are obtained.Finally,the performance boundaries of LADRC and PI control are explicitly compared with each other,which shows that the former is more superior in most cases.
文摘To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.
文摘最小二乘逆时偏移(least-squares reverse time migration,LSRTM)具有更高的成像分辨率、振幅保真性及均衡性等优势。然而,目前的LSRTM算法大多基于水平地表假设,在面对复杂地形时无法很好地适应剧烈的起伏地表。基于二阶常密度声波方程的LSRTM算法忽略了密度变化对振幅的影响,很难在变密度介质中取得保真的成像结果。为此,从一阶速度-应力方程出发,在曲线坐标系下推导相应的扰动方程和伴随方程,并通过伴随状态法给出梯度更新公式,最终实现基于贴体网格的起伏地表LSRTM算法。模型试算验证了算法的有效性和对复杂地表的适应性。结果表明,提出的算法能够消除起伏地表的影响、压制低频噪声、恢复高频成分、均衡成像振幅,实现地下变密度介质的高分辨率和高保真度成像。
