Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matri...Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.展开更多
Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent...Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.展开更多
目前回弹法规程只适用于60 MPa以下强度等级混凝土强度的检测,针对高强混凝土的特点,采用本地区具有代表性的原材料,制作了C50、C55、C60、C65、C70、C75、C80高强混凝土试块,分为14、28、60、90、180、365 d 6个龄期进行测试,利用最小...目前回弹法规程只适用于60 MPa以下强度等级混凝土强度的检测,针对高强混凝土的特点,采用本地区具有代表性的原材料,制作了C50、C55、C60、C65、C70、C75、C80高强混凝土试块,分为14、28、60、90、180、365 d 6个龄期进行测试,利用最小二乘方法,得到了4种不同函数形式的回归方程。通过相关系数、相对标准误差和平均相对误差的比较,线性函数型的回归效果最好,精度最高,采用其作为本地区高强混凝土回弹法地方测强曲线。展开更多
基金This work is supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0467)Jiangsu Province,China.During the revision of this paper,the author is supported by China Scholarship Council(No.201906840021)China to continue some research related to data processing.
文摘Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.
基金supported by National Natural Science Foundation of China(62371225,62371227)。
文摘Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.
文摘探究广西北部湾经济区(以下简称“研究区”)2001-2020年生态系统健康时空动态变化特征,可为研究区生态系统健康和社会经济可持续发展提供数据支持与理论参考。耦合“活力组织弹性”(Vigor Organization Resilience,VOR)模型、生态系统服务和权衡的综合评估(Integrated Valuation of Ecosystem Services and Trade offs,InVEST)模型构建生态系统健康多指标评价体系,并建立最小二乘法优化赋权模型对各评价指标进行优化赋权,对研究区生态系统健康状况进行评价与分析。结果表明:①研究区近20年来生态系统健康等级为三级的区域面积占研究区总面积的85%左右,且处于相对较为稳定的变化状态,研究区生态系统健康整体处于一般健康水平以上;②研究区生态系统健康状况总体上呈现北部、西部和南部地区优于中部和东部地区的空间分布差异;③研究区生态系统健康等级转移呈现以稳定型为主、退化型面积略大于改善型面积的空间变化特征,生态系统健康状况总体呈现轻微恶化趋势;④对研究区6个城市的生态系统健康从时间尺度和空间尺度对比分析发现,崇左、防城港、钦州3市生态系统健康状况变化较为明显,而南宁、玉林、北海3市相对较为平缓,但各市健康等级空间分布变化趋势较为吻合。本研究结果对推动广西北部湾经济区生态文明建设协调发展具有实际意义。
文摘目前回弹法规程只适用于60 MPa以下强度等级混凝土强度的检测,针对高强混凝土的特点,采用本地区具有代表性的原材料,制作了C50、C55、C60、C65、C70、C75、C80高强混凝土试块,分为14、28、60、90、180、365 d 6个龄期进行测试,利用最小二乘方法,得到了4种不同函数形式的回归方程。通过相关系数、相对标准误差和平均相对误差的比较,线性函数型的回归效果最好,精度最高,采用其作为本地区高强混凝土回弹法地方测强曲线。
