基于方位时差的多站协同目标跟踪

为提高多站无源协同跟踪的精度.提出了一种基于方位时差的目标跟踪方法.从一种拟线性的方位增量卡尔曼预处理方法人手,降低方位观测的误差,利用距离和时差跟踪建立观测方程.使用扩展卡尔曼滤波的方法对目标的运动状态进行估计,并采用分布式估计集中处理的方式融合多站并行估计数据.通过计算机仿真分析了该方位时差方法的跟踪性能.仿真结果表明.该方法对于目标状态的估计与真值偏差较小,能够满足跟踪精度要求.     

基于L型阵DOA估计的研究

从阵列有效孔径的角度研究了智能天线中的阵列结构,分析了均匀线性阵列和均匀圆形阵列的有效孔径在整个空间的阵列有效孔径,采用L型阵列进行DOA估计,通过理论分析与计算机仿真试验,说明L型阵列的优良性能.     

NONINVASIVE DETECTION OF BRAIN ACTIVITY VARIATION UNDER DIFFERENT DEPTH OF ANESTHESIA BY EEG COMPLEXITY

Objective To detect the change of brain activity under different depth of anesthesia （DOA） noninvasively. A,fethods The Lempel-Ziv complexity C（n） was used to analyze EEG and its four components （delta, theta, alpha, beta）, which was recorded from SD rats under different DOA. The relationship between C（n） and DOA was studied. Results The C（n） of EEG will decrease while the depth of anesthesia increasing and vice versa. It can be used to detect the change of DOA sensitively. Compared with power spectrum, the change of C（n） is opposite to that of power spectrum. Only the C （n） of delta rhythm has obvious variations induced by the change of DOA, and the variations of delta is as similar as the EEG＇s. Conclusion The study shows that the desynchronized EEG is replaced by the synchronized EEG when rat goes into anesthesia state from awake, that is just the reason why complexity and power spectrum appear corresponding changes under different DOA. C（n） of delta rhythm dynamic change leads to the change of EEG, and the delta rhythm is the dominant rhythm during anesthesia for rats.     

阵列天线DOA估计中MUSIC算法性能综合分析

阵列信号处理是现代信号处理中的一个重要分支,而信源定位又是阵列信号处理中的重要应用.常规的子空间算法———MUSIC算法可对到达角(DOA)实现超分辨估计.然而,MUSIC算法的超分辨率是在阵列信号模型精确条件下得到的,阵元数、阵元间距、信噪比、快拍数等因素对MUSIC算法的分辨率都会产生一定的影响.本文通过仿真,综合分析了阵元数、阵元间距、信噪比、快拍数等因素对MUSIC算法的分辨率产生的影响,同时表明了,快拍数相对其它参数对MUSIC算法分辨率的影响要小.     

A new source number estimation method based on the beam eigenvalue

Most source number estimation methods based on the eigenvalues are decomposed by covariance matrix in MUSIC algorithm. To develop the source number estimation method which has lower signal to noise ratio and is suitable to both correlated and uncorrelated impinging signals, a new source number estimation method called beam eigenvalue method (BEM) is proposed in this paper. Through analyzing the space power spectrum and the correlation of the line array, the covariance matrix is constructed in a new way, which is decided by the line array shape when the signal frequency is given. Both of the theory analysis and the simulation results show that the BEM method can estimate the source number for correlated signals and can be more effective at lower signal to noise ratios than the normal source number estimation methods.     

水听器混合阵列MUSIC方位估计研究

实际应用中,矢量水听器阵列是声压水听器阵列通道数的三倍（二维矢量水听器阵列）或四倍（三维矢量水听器阵列）,其相应的数据量、信号处理复杂度及成本亦明显增加。在阵列中混合配置声压水听器与矢量水听器,是一种解决该问题的有效途径。利用多重信号分类法（MUSIC）,对五种配置的水听器混合阵列进行研究,分析在不同信噪比、目标相对运动时对方位估计的影响。仿真表明,在有相同数目矢量水听器时,水听器混合阵列间隔配置比集中配置要好;在目标方位未知的情况下,在中间配置一个矢量水听器比在一端配置要合理。     

基于四阶累积量的最小模DOA估计方法

高阶累积量由于对高斯噪声不敏感,在高分辨阵列信号处理中可用来提高参数估计的分辨性能。本文从一个统一的角度来研究基于高阶累积量的高分辨阵列信号处理方法,用四阶累积量构造了一个较通用的累积量矩阵,该矩阵符合最小模(M in-Norm)算法的结构,从而可进行DOA(D irection of Arrival)估计。由于四阶累积量对高斯噪声干扰不敏感,从而可提高估计的分辨性能。本文就这种方法在阵列信号处理中的应用,通过计算机仿真与基于二阶矩的M in-Norm算法进行了较全面的比较。仿真结果表明,该方法在高斯噪声中具有良好的统计性能,是实现高分辨方位估计的有效方法。     

基于单一线列阵的水下测速技术研究

利用水下声音可有效传播特征,提出了利用单一线列阵测试水下运动目标速度的方法．利用不同时刻运动目标和线列阵之间的几何关系,建立了速度测试的数学模型．本文介绍了最大拟然算法和信号相位匹配原理算法,用于高精度求解运动目标的方位角（DOA）．对速度测试误差影响的关键因素进行了分析,提出了测试系统组成：在运动目标相隔一定距离部位上安装两发射不同频率的换能器,在距运动目标不远处布上装有电子罗盘和深度传感器的线列阵,同时配备有信号采集记录仪．推导了系统特别是线列阵的参数要求．考虑工程上实际误差并进行仿真计算,仿真计算表明,一个孔径小于1m的16元阵均匀线列阵的速度测试误差小于4％．消声水池和水库试验进一步验证了模型和仿真计算的正确性．     

DOA方法在OFDM目标信号波束成形及抑制共道干扰中的应用

针对多目标系统中的OFDM信号波束成型问题，研究了共道干扰环境下的OFDM的频率选择性多径信号模型，根据OFDM信号的特征即基于同中心频率循环平稳信号相关函数的不同，讨论利用一种具有阵列扩展能力抑制共道干扰的DOA方法，并以估计出的干扰环境中的信号来向进行波束成型．理论分析和计算机仿真实验均表明了应用在OFDM信号波束成型中的DOA方法是可行的，并且较充分地抑制了共道干扰（CCI）．     

A Genetic Algorithm-Based Smart Antenna Technique for Anti-Collision of Multiple SAW ID-Tags

In the radio frequency identification (RFID) system based on surface acoustic wave (SAW) technique, some tags often locate in the field of a transceiver at the same time. These tags produce simultaneous echo signals which "collide" when they arrive back at the transceiver, which leads to difficult identification. In this paper, smart antenna technique is presented to implement anti-collision in SAW RFID system. The direction of arrivals (DOAs) are used to denote the locations of tags, and genetic algorithm (GA) is suggested to find the optimal estimates of the DOAs in complex multimodal search spaces. Once the DOAs are obtained, the array weights are formed and the signals of tags are recovered to implement decoding. The experimental results show that the GA-based smart antenna technique works well in some occasions.