A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative ...A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative position,velocity and attitude of two unmanned aerial vehicles (UAVs).The second-order divided difference filter which makes use of multidimensional interpolation formulations to approximate the nonlinear transformations could achieve more accurate estimation and faster convergence from inaccurate initial conditions than standard extended Kalman filter.The filter formulation is based on relative motion equations.The global attitude parameterization is given by quarternion,while a generalized three-dimensional attitude representation is used to define the local attitude error.Simulation results are shown to compare the performance of the second-order divided difference filter with a standard extended Kalman filter approach.展开更多
A current-mode low input and high output impedances first-order allpass filter using two multiple output second-generation current conveyors (MOCCIIs), one grounded capacitor and one grounded resistor is presented. Th...A current-mode low input and high output impedances first-order allpass filter using two multiple output second-generation current conveyors (MOCCIIs), one grounded capacitor and one grounded resistor is presented. The suggested filter uses a canonical number of passive components without requiring any component matching condition. The frequency responses simulation results of the proposed filter confirm the theoretical analysis.展开更多
Current methods of order tracking, such as synchronous resampling, Gabor filtering, and Vold-Kalman filtering have undesirable traits. Each method has two or more of the following deficiencies: requires measurement or...Current methods of order tracking, such as synchronous resampling, Gabor filtering, and Vold-Kalman filtering have undesirable traits. Each method has two or more of the following deficiencies: requires measurement or estimate of rotational speed over time, failure to isolate the contribution of crossing orders in the vicinity of the crossing time, large computational expense, end effects. In this work a new approach to the order tracking problem is taken. The Second Order Blind Identification (SOBI) algorithm is applied to synthesized data. The technique is shown to be very successful at isolating crossing orders and circumvents all of the above deficiencies. The method has its own restric-tions: multiple sensors are required and sensors must be mounted on a structure that responds quasi-statically to exci-tation of the rotational system.展开更多
为提高永磁直线同步电机速度控制的稳定性,尤其是在高速运动时的速度波动抑制能力,提出了一种基于FSMO-SOGI的永磁直线同步电机自适应反步速度控制策略。首先,根据Lyapunov稳定性定理设计了自适应反步速度控制器,该控制器可以对动子质...为提高永磁直线同步电机速度控制的稳定性,尤其是在高速运动时的速度波动抑制能力,提出了一种基于FSMO-SOGI的永磁直线同步电机自适应反步速度控制策略。首先,根据Lyapunov稳定性定理设计了自适应反步速度控制器,该控制器可以对动子质量、摩擦因数和负载扰动等不确定性参数进行估计,从而实现控制系统全局渐近稳定的速度跟踪控制。其次,为了实现速度闭环控制,提出了一种将全阶滑模观测器(Full-order sliding mode observer,FSMO)与二阶广义积分滤波器(Second order generalized integral filter,SOGI)相结合的无传感器控制方法。FSMO基于电流和反电动势模型,可以提高反电动势的观测精度,而SOGI则有效滤除反电动势中的谐波分量。最后,通过试验证明了本文方法能够实现电机动子速度的准确辨识,提升了永磁直线同步电机速度控制的品质。展开更多
为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以...为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。展开更多
为解决软件无线电(Software Defined Radio,SDR)中采样后信号混叠问题,提出了一种改进的相位调整滤波算法。依托具备可调时间延迟的二阶射频带通采样前端,设计了一种支持多分点分段滤波的抗混叠滤波器,可以根据实际需求灵活设置多个频...为解决软件无线电(Software Defined Radio,SDR)中采样后信号混叠问题,提出了一种改进的相位调整滤波算法。依托具备可调时间延迟的二阶射频带通采样前端,设计了一种支持多分点分段滤波的抗混叠滤波器,可以根据实际需求灵活设置多个频率分点,从而实现针对不同频段的精确滤波。通过在MATLAB SIMULINK中进行仿真验证,该方法相比同类方法的滤波器抑制效果更佳,达到38 dB以上,并能有效滤除所需信号而不影响其他信号的完整性,简化了接收前端,具备较强的灵活性和适应性,能够更好地支持未来的通信技术和高密度通信连接。展开更多
Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also...Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming （SOCP） and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.展开更多
基金Sponsored by the Aerospace Technology Innovation Funding(Grant No. CASC0209)
文摘A second-order divided difference filter (SDDF) is derived for integrating line of sight measurement from vision sensor with acceleration and angular rate measurements of the follower to estimate the precise relative position,velocity and attitude of two unmanned aerial vehicles (UAVs).The second-order divided difference filter which makes use of multidimensional interpolation formulations to approximate the nonlinear transformations could achieve more accurate estimation and faster convergence from inaccurate initial conditions than standard extended Kalman filter.The filter formulation is based on relative motion equations.The global attitude parameterization is given by quarternion,while a generalized three-dimensional attitude representation is used to define the local attitude error.Simulation results are shown to compare the performance of the second-order divided difference filter with a standard extended Kalman filter approach.
文摘A current-mode low input and high output impedances first-order allpass filter using two multiple output second-generation current conveyors (MOCCIIs), one grounded capacitor and one grounded resistor is presented. The suggested filter uses a canonical number of passive components without requiring any component matching condition. The frequency responses simulation results of the proposed filter confirm the theoretical analysis.
文摘Current methods of order tracking, such as synchronous resampling, Gabor filtering, and Vold-Kalman filtering have undesirable traits. Each method has two or more of the following deficiencies: requires measurement or estimate of rotational speed over time, failure to isolate the contribution of crossing orders in the vicinity of the crossing time, large computational expense, end effects. In this work a new approach to the order tracking problem is taken. The Second Order Blind Identification (SOBI) algorithm is applied to synthesized data. The technique is shown to be very successful at isolating crossing orders and circumvents all of the above deficiencies. The method has its own restric-tions: multiple sensors are required and sensors must be mounted on a structure that responds quasi-statically to exci-tation of the rotational system.
文摘为提高永磁直线同步电机速度控制的稳定性,尤其是在高速运动时的速度波动抑制能力,提出了一种基于FSMO-SOGI的永磁直线同步电机自适应反步速度控制策略。首先,根据Lyapunov稳定性定理设计了自适应反步速度控制器,该控制器可以对动子质量、摩擦因数和负载扰动等不确定性参数进行估计,从而实现控制系统全局渐近稳定的速度跟踪控制。其次,为了实现速度闭环控制,提出了一种将全阶滑模观测器(Full-order sliding mode observer,FSMO)与二阶广义积分滤波器(Second order generalized integral filter,SOGI)相结合的无传感器控制方法。FSMO基于电流和反电动势模型,可以提高反电动势的观测精度,而SOGI则有效滤除反电动势中的谐波分量。最后,通过试验证明了本文方法能够实现电机动子速度的准确辨识,提升了永磁直线同步电机速度控制的品质。
文摘为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。
文摘为解决软件无线电(Software Defined Radio,SDR)中采样后信号混叠问题,提出了一种改进的相位调整滤波算法。依托具备可调时间延迟的二阶射频带通采样前端,设计了一种支持多分点分段滤波的抗混叠滤波器,可以根据实际需求灵活设置多个频率分点,从而实现针对不同频段的精确滤波。通过在MATLAB SIMULINK中进行仿真验证,该方法相比同类方法的滤波器抑制效果更佳,达到38 dB以上,并能有效滤除所需信号而不影响其他信号的完整性,简化了接收前端,具备较强的灵活性和适应性,能够更好地支持未来的通信技术和高密度通信连接。
基金This work was supported by the National Natural Science Foundation of China （Grant No. 60472073） the Doctorate Foundation of Northwestern Polytechnical University.
文摘Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming （SOCP） and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.
