线性相位有限冲激响应滤波器的实现

介绍线性相位滤波器的一种实现方法,即采用有限冲激响应（FIR）滤波器的窗函数法设计线性相位的数字滤波器。     

图像序列直线提取和匹配时Hough变换的应用研究

本文利用Hough变换的点线对偶性,将对图像序列中的特征直线的匹配转化为在参数空间中对特征点运动轨迹的参数估计,设计采用卡尔曼滤波器对运动目标进行初步跟踪,通过建立模板与图像的匹配相关系数判定搜索到的特征点的精确坐标。实验结果表明,该方法具有较好的跟踪结果。     

一种基于数字信号处理的阻抗参数测量新方法

利用数字信号处理理论与技术提出了一种阻抗参数测量新方法,即采用任意的周期信号作为测量的激励信号,激励信号的信噪比可以很低;采用高镜频抑制比的数字正交采样滤波器得到被测阻抗和标准阻抗上的电压采样序列的同相分量与正交分量,并据此确定被测阻抗参数,该方法能得到较高的阻抗参数测量精度和较宽的测量范围,并且硬件电路实现比较容易.文中给出了计算机仿真分析和硬件实现系统的实验结果,证明了新方法的有效性和正确性.     

组合式三相双Buck宽变频逆变器

介绍了两态滞环电流控制型双Buck逆变器的电路结构和工作原理,对系统内环进行建模和分析。从理论上分析得到电流内环可以把LC二阶系统降阶为一阶系统,并将电流内环近似等效为一阶惯性环节,其时间常数主要取决于系统滤波电感的大小,并提出了一种滞环电流控制型逆变器输出滤波器的解耦设计方法,对宽变频输出时的输出滤波器进行优化设计。在此基础上进行三相组合式实验研究,通过数字控制技术实现逆变器系统具有360~800 H z宽变频输出。最后通过三相6 kVA原理样机,验证了本逆变器系统在全频率范围得到良好的输出电压波形和较高的效率,具有更广的应用前景。     

多传感器组合导航系统的改进多尺度滤波算法

多尺度滤波算法在多传感器组合导航系统中已得到成功应用，然而该算法用到多个时刻的量测向量，导致算法计算量过大，并影响系统的实时性。针对上述问题，首先利用分块技术与小波变换将时域内描述的系统原始状态方程转换为块状态方程，然后将实时得到的当前时刻的量测向量表达为块状态向量的形式，最后结合常规卡尔曼滤波技术与序贯滤波的思想，提出了一种改进的多传感器组合导航系统多尺度滤波方法。将该算法应用于GPS/SST/SINS多传感器组合导航系统，仿真结果验证了该算法不仅具有较好的实时性，而且相对于传统算法,系统的定位精度提高1倍以上。     

State estimate for stochastic systems with dual unknown interference inputs

Stochastic system state estimation subject to the unknown interference input widely exists in many fields, such as the control, communication, signal processing, and fault diagnosis. However, the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input, and the state model and the measurement model are both with the same unknown interference input. State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs (dual-UI) with different physical meanings and mathematical definitions is concerned here. Firstly, the decoupling condition with the Unknown Interference input in the State model (S-UI) is shown, which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs (M-UI) appearing in the state model and the measurement model. Then, through defining the Differential term of the adjacent M-UI (M-UID), the equivalent system with only M-UID in the state model is obtained. Finally, considering the design freedom of the equivalent system, the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate, respectively. Two simulation cases verify the effectiveness and superiority compared with the traditional methods.     

Guidepost-based autonomous orbit determination method for GEO satellite

Guidepost-based navigation system is a novel autonomous orbit determination method for the GEO satellite. The system is achieved by using the camera imaging function to obtain the guidepost images and the GNSS signal receiver to obtain the pseudoranges between the GEO and the navigation satellites. Due to the high altitude of GEO satellite and the time-varying sunlight condition in the space environment, it may be difficult to obtain object image points and the distance measurements of GNSS because of the weak visibility of the guideposts. To deal with the problem, a novel integrated orbit determination system is presented. The Earth landmarks, the in-orbit spacecraft and GNSS navigation satellites whose line-of-sights and the distance can be easily obtained are used at the same time as information for the GEO satellite navigation based on the observability conditions analysis. The observability of the GEO satellite navigation system is analyzed through the physical observability, the mathematical observability and the engineering observability through the observing geometry, the rank of observability matrix and the Cramer-Rao lower bound (CRLB) respectively. Besides, the maximum correntropy unscented Kalman filter (MCUKF) algorithm is applied to improve the estimation stability of the system in the presence of non-Gaussian noises. The simulation indicates the feasibility of the proposed scheme.     

采用单目视觉的非合作目标星状态估计

针对微小卫星逼近观测未知的空间翻滚非合作目标星任务，提出一种基于单目视觉的目标星相对状态估计方法。在建立追踪星/目标星相对运动模型的基础上，以单目相机识别并测量获得的目标星固有特征的像素位置为观测输入，通过扩展卡尔曼滤波算法实现对目标星相对位置、相对速度、相对姿态、角速度、惯量比和特征位置等状态的估计。仿真结果表明,该方法能够很好地实现对未知非合作目标星的相对状态估计，姿态估计误差小于2°，位置估计误差小于0.1 m，特征点位置平均估计误差小于0.04 m。     

用于平台连续瞄准和校准的卡尔曼滤波器

本文为提高制导精度,讨论了用于惯性平台的连续瞄准、校准的卡尔曼滤波器,介绍平台系统和加速度表的误差模型、参数辨识的卡尔曼滤波方法及重力残数加速度表校准原理。     

带限信号采样和数字相参处理

传统的相参处理器包括Ｉ，Ｑ二个通道，存在不避免的幅相不平衡，本文研究中频带限信号采样经数字处理获得零中频正交数字信号的方法，该方法只用一路Ａ／Ｄ转换器直接对中频带限信号进行采样和数字变换，用镜频抑制滤波器，二次重采样移频电路分离零中频信号的同相分量Ｉ。和正交分量Ｑ，因而，该方法能够克服Ｉ，Ｑ通道不平衡，文中对中频频率，采样时钟周期的选择，镜频抑制滤波器的设计进行了详细讨论，选用具有线性相位特性的Ｆ