Multi-input multi-output random vibration control using Tikhonov filter

Noises always disturb the control effect of an environment test especially in multi-input multi-output (MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces will be amplified and the response spectral lines may awfully exceed their tolerances. Most of the major biases between the response spectra and the reference spectra are pro-duced by the amplified noises. However, ordinary control algorithms can hardly reduce the level of noises. The influences of the noises on both the auto-and cross-power spectra are analyzed in this paper. As a conventional frequency domain method on the inverse problem, the Tikhonov filter is adopted in the environment test to suppress the exceeding spectral lines. By altering regularization parameters gradually, the auto-power spectra can be improved in a closed control loop. Instead of using the traditional way of selecting regularization parameters, we observe the coherence change to estimate noise eliminations. Incidentally, the requirement of coherence control can be realized. The errors of the phase are then studied and a phase control algorithm is introduced at the end as a sup-plement of cross-power spectra control. The Tikhonov filter and the proposed phase control algo-rithm are tested numerically and experimentally. The results show that the noises in the vicinity of lightly damped resonant peaks are more stubborn. The response spectra are able to be greatly improved by the combination of these two methods.     

相关信道下一种新的发射天线选择算法

现有的天线选择算法大多都是假设信道是独立同分布的,而实际的信道是相关的。针对这一问题,本文在研究盖尔圆算法的基础上,提出了一种新的用于相关信道的低复杂度天线选择算法。算法利用奇异值估计方法给出最小奇异值的下界,通过递增的方法,选择使信道矩阵最小奇异值的下界最大的列从而提高最小奇异值,使得容量最大化并得到较好的误码性能。理论分析与仿真结果表明,该算法在射频链路较少时具有很低的复杂度,同时容量和误码性能优于随机选择算法,接近最优选择算法。     

Joint Iterative Decoding for Network-Coding-Based Multisource LDPC-Coded Cooperative MIMO

A network-coding-based multisource LDPC-coded cooperative MIMO scheme is proposed,where multiple sources transmit their messages to the destination with the assistance from a single relay.The relay cooperates with multiple sources simultaneously via network-coding.It avoids the issues of imperfect frequency/timing synchronization and large transmission delay which may be introduced by frequency-division multiple access(FDMA)/code-division multiple access(CDMA)and time-division multiple access(TDMA)manners.The proposed joint″Min-Sum″iterative decoding is effectively carried out in the destination.Such a decoding algorithm agrees with the introduced equivalent joint Tanner graph which can be used to fully characterize LDPC codes employed by the sources and relay.Theoretical analysis and numerical simulation show that the proposed scheme with joint iterative decoding can achieve significant cooperation diversity gain.Furthermore,for the relay,compared with the cascade scheme,the proposed scheme has much lower complexity of LDPC-encoding and is easier to be implemented in the hardware with similar bit error rate(BER)performance.     

多输入多输出雷达的非均匀线性阵列配置(英文)

提出了利用非均匀线性阵列(Non-uniform linear array,NLA)对多输入多输出(Multiple-input multipleoutput,MIMO)雷达系统进行阵列配置优化的方法。在传统的相控阵雷达中,非均匀线性阵列配置被用来形成较窄的波束方向图,而在MIMO雷达中,利用非均匀线性阵列来获得更多的互不相同的虚拟阵元,以此来提高雷达的参数可辨识性能。文中所采用的一种非均匀线性阵列是最小冗余线性阵列,并给出了一种在物理阵元数量较大时最小冗余线性阵列的生成方法。实验结果表明:与均匀线性阵列(Uniform linear array,ULA)配置的MIMO雷达相比,非均匀线性阵列MIMO雷达能够利用较少的物理天线阵元获得相同的参数可辨识性能;而在两种配置的雷达系统的物理阵元个数相同的情况下,非均匀线性阵列MIMO雷达可以获得更大的阵列孔径长度和更低的克拉美.罗界。     

机载MIMO雷达空时自适应杂波对消器

针对机载多输入多输出(MIMO)雷达杂波分布呈现空时耦合特性,提出一种空时自适应杂波对消器.利用机载MIMO雷达的脉冲回波数据,构造杂波对消器的系数矩阵.通过空时自适应杂波对消器的预处理,可以有效地抑制杂波,并通过与常规空时处理算法的级联,最终可以有效提高动目标的检测性能.实现了由传统地基雷达杂波对消器向机载运动平台的推广.仿真结果表明,这种自适应杂波对消器不仅适用于正侧视雷达,对于非正侧视雷达也同样适用.     

MIMO系统中迭代捕获算法的性能分析

基于迭代消息传递的伪码捕获方法能够在复杂度较低的情况下,极大的提高捕获速度,但在低信噪比下捕获性能下降很快。多输入多输出 (MIMO) 系统可以在不增加频谱资源和发射功率的条件下,削弱多径衰落,改善通信系统的性能。本文提出将迭代捕获算法应用于MIMO系统中,在接收端采用分集技术,运用最大比合并方法进行信号合并,然后用迭代算法进行捕获。仿真结果表明：将迭代捕获算法与MIMO系统结合,在不影响捕获速度的前提下能够有效提高信号的捕获概率,信噪比在-22dB条件下捕获概率达到90%以上,性能优于现有的迭代捕获算法。     

集中式多输入多输出雷达信号盲分离算法研究

在电子对抗领域,对集中式多输入多输出（Multiple Input Multiple Output, MIMO）雷达的信号侦察和分选是一个难点。提出采用盲分离（Blind Source Separation, BSS）算法中的非圆复信号快速独立分量分析（Noncircular Complex Fast ICA, NC FastICA）对MIMO雷达进行信号分选。为了满足盲分离算法的应用条件,提出一种在多视角观测位置采集雷达信号的侦察方法来构建可分离的满秩混合矩阵。仿真结果表明,对相位编码、离散频率编码等典型正交波形进行等角度间隔采样和盲分离时,无论是否存在幅度起伏,在信噪比为10dB时均可以达到低于-14dB的正交波形分离度,对分离后的波形进行相关性对比和时频分析的结果也验证了本文方法的有效性。     

采用ISAR技术的MIMO雷达极坐标格式成像算法研究

对MIMO雷达的系统结构和它采用ISAR技术时的信号模型进行分析,以二次降维方式详细讨论了回波信号在波数域的分布特点,得出两条针对成像应用的MIMO雷达阵列设计准则。在此基础上,提出一种可有效聚焦的极坐标格式算法,经过对MIMO雷达回波数据逐次渐进降维重排,将其从四维转换到二维,然后通过距离向和方位向两次一维插值,把以极坐标格式记录的回波数据变换为直角坐标下均匀分布的数据。针对推导过程中因平面波假设引入的误差进行了分析,得到算法的适用条件。最后仿真验证了本文算法的有效性。     

冲击杂波下的MIMO雷达DOA估计方法

研究了对称α稳定分布(SαS)冲击杂波下的多输入多输出（MIMO）雷达目标波达方向（DOA）估计问题,分别提出基于分数低阶最小方差无畸变响应(FrMVDR)的MIMO雷达DOA估计算法和无穷范数归一化最小方差无畸变响应（Inf-MVDR)算法。FrMVDR算法,首先进行冲击杂波特征指数的估计,然后使MIMO雷达接收阵列的分数低阶输出功率最小,实现MIMO雷达的DOA估计。为了避免FrMVDR算法对杂波特征指数估计,提出Inf-MVDR算法,首先用无穷范数对接收信号进行归一化处理,使归一化后的阵列输出功率有界,继而采用传统MVDR算法进行DOA估计。计算机仿真验证了上述两种算法的有效性;同时仿真结果还表明在冲击杂波下,MIMO雷达的空间分集特性可显著提高DOA估计的精度。     

基于MIMO技术的卫星高速数据传输系统研究

多输入多输出（MIMO）系统作为提高频谱效率的一种有效方式,已经成为未来无线通信系统实现高速可靠数据传输的突破性技术之一,受到国际众多研究机构的普遍关注。文章通过研究MIMO信道模型、信道容量、卫星信道特征,构建了全新高速数传系统模型,解决了卫星大容量数据实时传输和频带限制之间的矛盾。