In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes fu...In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes full advantage of the original electromagnetic scattering data and its conjugated form by combining them with the novel covariance matrices.To analyse the superiority of the modified algorithm,the mathematical expression of equivalent signal to noise ratio(SNR)is derived,which can validate our proposed algorithm theoretically.In addition,compared with the conventional matrix pencil(MP)algorithm and the conventional root-multiple signal classification(Root-MUSIC)algorithm,the proposed algorithm has better parameter estimation performance and more accurate multiband fusion results at the same SNR situations.Validity and effectiveness of the proposed algorithm is demonstrated by simulation data and real radar data.展开更多
Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows t...Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows that when the correlated matrix, the mean of noise, the control input, and the measurement error are all zero, the result in this paper turns out to be the standard algorithm discussed. Simulation shows that the mean of noise, the control input, and the measurement error will not change the estimation covariance and the estimation covariance fluctuates greatly when the cross-correlated matrix is similar to the covariance of process noise.展开更多
The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acqu...The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.展开更多
锂离子电池健康状态(state of health,SOH)估计对确保能量存储系统的可靠性和安全性至关重要。然而,现有SOH估计方法在单一特征提取和固定充放电条件依赖方面存在局限性,难以适应多变的实际工作环境。为解决这一问题,本工作提出了一种...锂离子电池健康状态(state of health,SOH)估计对确保能量存储系统的可靠性和安全性至关重要。然而,现有SOH估计方法在单一特征提取和固定充放电条件依赖方面存在局限性,难以适应多变的实际工作环境。为解决这一问题,本工作提出了一种基于弛豫电压的并行多尺度特征融合卷积模型(multi-scale feature fusion convolution model,MSFFCM)结合极端梯度提升树(XGBoost)的SOH估计方法。MSFFCM通过多层堆叠卷积模块提取弛豫电压数据的深层特征,同时利用并行多尺度注意力机制增强了多尺度特征的捕捉能力,并将这些特征与统计特征进行融合,以提升模型的特征提取和融合能力。针对XGBoost模型,本工作应用贝叶斯优化算法进行参数调优,从而在多源融合特征基础上实现高精度SOH估计。实验验证基于两种商用18650型号电池的多温度和多充放电策略数据集,结果表明该方法的均方根误差(RMSE)和平均绝对误差(MAE)均小于0.5%,明显优于传统方法。本工作为锂电池健康管理提供了一种不依赖特定充放电条件的有效估计工具,有望在复杂的实际应用中发挥重要作用。展开更多
针对虚假数据注入攻击(false data injection attack,FDIA)下的分布式安全状态估计问题,提出了一种基于攻击削减的分布式安全状态估计算法。首先,在无攻击的假设下对局部滤波器中预测值与估计值间的差值进行统计分析;然后,将FDIA建模为...针对虚假数据注入攻击(false data injection attack,FDIA)下的分布式安全状态估计问题,提出了一种基于攻击削减的分布式安全状态估计算法。首先,在无攻击的假设下对局部滤波器中预测值与估计值间的差值进行统计分析;然后,将FDIA建模为导致有效预测值与受损估计值间的差值产生变化的未知输入,并设计带有遗忘因子的递归最小二乘(recursive least squares,RLS)对其进行估计;最后,设计攻击削减机制对因攻击而受损的数据进行恢复,并对处理后的局部估计值进行融合。仿真结果表明,所提方法能够有效实现攻击估计,降低攻击的影响,提高了鲁棒性和估计精度。展开更多
文摘In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes full advantage of the original electromagnetic scattering data and its conjugated form by combining them with the novel covariance matrices.To analyse the superiority of the modified algorithm,the mathematical expression of equivalent signal to noise ratio(SNR)is derived,which can validate our proposed algorithm theoretically.In addition,compared with the conventional matrix pencil(MP)algorithm and the conventional root-multiple signal classification(Root-MUSIC)algorithm,the proposed algorithm has better parameter estimation performance and more accurate multiband fusion results at the same SNR situations.Validity and effectiveness of the proposed algorithm is demonstrated by simulation data and real radar data.
文摘Based on the single sensor Kalman filtering equations, this paper presents two-level and three-level optimal centralized and distributed estimation algorithms for hierarchical multisensor systems. The solution shows that when the correlated matrix, the mean of noise, the control input, and the measurement error are all zero, the result in this paper turns out to be the standard algorithm discussed. Simulation shows that the mean of noise, the control input, and the measurement error will not change the estimation covariance and the estimation covariance fluctuates greatly when the cross-correlated matrix is similar to the covariance of process noise.
基金supported by a grant from the Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology (Grant No. GZZKFJJ2020004)the National Natural Science Foundation of China (Grant Nos. 61875013 and 61827814)the Natural Science Foundation of Beijing Municipality (Grant No. Z190018)。
文摘The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.
文摘针对虚假数据注入攻击(false data injection attack,FDIA)下的分布式安全状态估计问题,提出了一种基于攻击削减的分布式安全状态估计算法。首先,在无攻击的假设下对局部滤波器中预测值与估计值间的差值进行统计分析;然后,将FDIA建模为导致有效预测值与受损估计值间的差值产生变化的未知输入,并设计带有遗忘因子的递归最小二乘(recursive least squares,RLS)对其进行估计;最后,设计攻击削减机制对因攻击而受损的数据进行恢复,并对处理后的局部估计值进行融合。仿真结果表明,所提方法能够有效实现攻击估计,降低攻击的影响,提高了鲁棒性和估计精度。
