弹道目标微动特征分析与提取方法

进动特征对导弹防御目标识别具有重要意义。建立了单频信号下雷达观测弹头的进动模型和回波模型,通过对进动弹头回波频谱与微多普勒调制特性的定量分析,提出了利用回波相关方法和频谱展宽估计进动参数的方法,并利用暗室测量数据对该方法的性能进行了实验验证。实验结果表明,该方法在目标进动角不大条件下可以有效估计目标的进动角和进动周期。     

提升类小波变换加速的模基参数估计算法

将提升类小波变换(lifting wavelet-like transform, LWLT)应用于矩量法（method of moment, MOM）快速求解电场积分方程（electric field integral equation, EFIE）,对生成的稀疏化线性系统采用模基参数估计（model based parameter estimation, MBPE）算法求解,可获得小波域的宽带解,结合小波逆变换,最终实现目标电磁散射特性的宽频分析。通过不同三维散射体的计算分析,验证了算法的正确性。与传统模基参数估计算法相比,所提算法在计算时间和内存耗费上均有很大改善。     

基于时变偏差分离估计的杂波下机动目标跟踪

在杂波环境机动目标跟踪问题中,波门位置和范围的确定是关键技术之一。在分析了时变偏差分离估计算法的有偏差的状态估计协方差基础上,提出了基于时变偏差分离估计(separate bias estimation, SBE)和概率数据关联(probabilistic data association, PDA)的新算法,利用了偏差估计和有偏差的状态估计协方差来确定波门位置和范围,并结合PDA处理多个回波的能力,实现杂波环境下机动目标的跟踪。通过仿真实验,说明了新算法的优势和有效性。     

Parameter estimation for multirate multi-input systems using auxiliary model and multi-innovation

The multirate multi-input systems have different updating periods and sampling periods such that the conventional identification algorithms cannot be used to identify such multirate systems. By using the auxiliary model identification idea, the multiinnovation stochastic gradient algorithm is developed to estimate the parameters of multirate systems. Finally, an illustrative example is given to verify the effectiveness of the proposed algorithm.     

Fast motion estimation algorithm for H.264/AVC based on centered prediction

H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality. However, this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation. The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio. Motion estimation (ME) plays an important role in motion compensated video coding. A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction, called centered prediction based fast mixed search algorithm (CPFMS). It makes use of the spatial and temporal correlation in motion vector (MV) fields and feature of all-zero blocks to accelerate the searching process. With the initialized searching point prediction, adaptive search window changing and searching direction decision, CPFMS is provided to reduce computation in block-matching process. The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio (PSNR) loss. Also, the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.     

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window.since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).     

应用矩阵分解的阵列信号参数辨识

从矩阵分解的角度研究了均匀线阵信号参数的可辨识性问题. 在范得蒙结构约束条件下实现接收信号矩阵的唯一分解. 运用交换引理和范德蒙矩阵的结构性质,给出了均匀线阵信号参数的可辨识条件,并将参数的可辨识条件扩展到相关信源情况和多径传输情况. 从矩阵分解的角度得到的阵列信号参数的辨识条件给出了阵列信号参数估计算法有效的必要条件,阵列信号参数仅与接收天线的阵列流形和信号的结构有关,与具体的参数估计算法无关.     

具有部分缺失数据时两个Weibull总体的估计和检验

本文讨论了具有部分缺失数据时两个Weibull总体的参数估计和关于总体相同的似然比检验．证明估计的强相合性和渐近正态性,给出似然比检验统计量的极限分布,并讨论基于精确分布的检验问题．     

基于曲线拟合的卫星通信信号参数盲估计

针对非协作卫星通信环境,提出了一种卫星通信信号参数盲估计方法。它利用线性调制信号功率谱形状的对称性及其与成型滤波器的关系,基于曲线拟合的思想进行功率谱包络的提取,进而实现载波频率、带宽等参数的盲估计。仿真结果验证了该方法对MPSK、MQAM等常用卫星通信信号的有效性,且能适应较低的信噪比,具有计算量小、易于实现等优点。     

基于前后向协方差矩阵投影的信源数估计算法

针对均匀线阵的信源数估计问题,提出了一种基于前向-后向采样协方差矩阵正交投影的多目标信源数快速估计算法。该算法将经过酉变换后的前向-后向采样协方差矩阵的列矢量做Gram-Schmidt (GS)正交化,并将正交化后矢量的模值与一个自适应判决门限做比较来估计信源个数。该判决门限根据阵列采样协方差矩阵估计误差的渐近分布特性推导得到。计算机仿真证明了该算法的正确性和有效性。