基于宽带毫米波工作体制的雷达目标识别方法探讨

对基于宽带毫米波工作体制的雷达目标特征获取和识别方法进行了综合分析和探讨.表明:在毫米波照射下,雷达目标可模型化为由多个散射中心组成的扩展目标;只要发射信号有足够的带宽,就可以从回波信号中获得各散射中心的空间分布、类型等特征;仿真结果说明,这种方法对高频区复杂目标的识别是有效的.     

非平稳ARMA信号自校正滤波器及其应用

本文处理带白色观测噪声的非平稳ARMA信号估计问题.应用状态空间方法和现代时 间序列分析方法[1],基于ARMA新息模型,提出了非平稳ARMA信号自校正滤波器,推广了 Hagander和Wittenmafk的结果[2],并给出了在雷达跟踪系统和检测数据数字滤波方面的应 用.仿真结果说明了本文结果的实用性和有效性.     

UL简介与CCL认可

本文从六个方面对UL的基本知识作了一个简要的概述及CCL认可过程的介绍,希望能为业界同仁提供一个参考方向。     

基于杂波跟踪的CFAR检测研究

通过设立专门通道将图像处理技术应用于雷达检测域杂波功率数据处理,对特征杂波进行跟踪,为恒虚警处理提供背景信息.本文介绍了对抗杂波边缘的自适应CFAR检测器设计中的研究工作,设计了基于杂波跟踪的杂波属性CF(clutter feature)-CFAR检测器和结构元素SE(structuring element)-CFAR检测器,对其检测性能进行了分析.并通过蒙特卡罗(Monte Carlo)仿真方法对上述两种检测器的检测性能进行了仿真.     

基于RBF网络和IMM的机动目标跟踪方法

文中提出了一种应用RBF神经网络对标准IMM算法中的卡尔曼滤波结果进行校正的方法。网络输人为预测误差、卡尔曼增益以及测量值与估计值之差．网络输出反映了由于目标机动所带来的滤波误差．将网络输出结果和直接由卡尔曼滤波求解得到的结果相加．可以得到更为准确的滤波值。同时．在网络的学习算法中．在网络权值矩阵的修正公式中增加了反映滤波残差的调整项．若卡尔曼滤波的残差较大，网络调整权值的幅度也相应增大。仿真结果表明．在目标发生机动转弯处．校正后的IMM算法的跟踪误差要明显小于标准IMM算法的跟踪误差．跟踪精度较高。     

冀中坳陷东北部石炭—二叠系储层特征及勘探方向

渤海湾盆地冀中坳陷石炭—二叠系残留分布区即坳陷东北部的文安斜坡、杨村斜坡、大城凸起等地区,受印支—燕山和喜马拉雅期强烈的后期构造运动改造,历经差异升降和拉张断陷两大构造发育阶段,致使东、西部剥蚀带的埋藏史表现为沉降—抬升—沉降、沉降—抬升两种类型。区内沉积体系发育较为齐全,自下而上可以识别出滨海潮坪—沼泽、三角洲和河流等三大沉积体系;其中,三角洲和河流体系发育的分流河道、辫状河道砂岩分布范围广、厚度大,形成了该区最主要的砂体类型。区内砂岩储层在其间断埋藏成岩过程中,受表生淋滤作用和深部淋滤作用的影响,形成了较为发育的次生孔隙,孔隙度一般为15%～25%,大气水的深部淋滤作用又进一步改善了断层发育区的储集性能,并由此形成了该区优质的储层。综合评价认为,西部剥蚀带附近是最有利的勘探区带。     

High accuracy path tracking for vehicles in presence of sliding: Application to farm vehicle automatic guidance for agricultural tasks

When designing an accurate automated guidance system for vehicles, a major problem is sliding and pseudo-sliding effects. This is especially the case in agricultural applications, where five-centimetre accuracy with respect to the desired trajectory is required, although the vehicles are moving on slippery ground. It has been established that RTK GPS was a very suitable sensor to achieve automated guidance with such high precision: several control laws have been designed for vehicles equipped with this sensor, and provide the expected guidance accuracy as long as the vehicles do not slide. In previous work, further control developments have been proposed to take sliding into account: guidance accuracy in slippery environments has been shown to be preserved, except transiently at the beginning/end of curves. In this paper, the design of this control law is first recalled and discussed. A Model Predictive Control method is then applied in order to preserve accuracy of guidance even during these curvature transitions. Finally, the overall control scheme is implemented, and improvements with respect to previous guidance laws are demonstrated through full-scale experiments.     

Error Concealment Based on Semantic Prioritization with Hardware‐Based Face Tracking

With video compression standards such as MPEG‐4, a transmission error happens in a video‐packet basis, rather than in a macroblock basis. In this context, we propose a semantic error prioritization method that determines the size of a video packet based on the importance of its contents. A video packet length is made to be short for an important area such as a facial area in order to reduce the possibility of error accumulation. To facilitate the semantic error prioritization, an efficient hardware algorithm for face tracking is proposed. The increase of hardware complexity is minimal because a motion estimation engine is efficiently re‐used for face tracking. Experimental results demonstrate that the facial area is well protected with the proposed scheme.     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.     

A reconfigurable VLSI-based double-lens tracking camera

Watching and tracking an object while seeing a much wider view is one of advantages of the eye system. We proposed and developed a tracking camera system that mimics the eyes by using double-lens modules. In the system, a wide view is captured through the wide-lens module, while the target in it is tracked and magnified through the telescopic lens module. Electronic circuits for tracking control are implemented onto the reconfigurable VLSI or FPGA in order to embed the parallelism in the tracking algorithm into the hardware. A successfully developed FPGA-based prototype performs high-speed tracking at the video-rate. This work was present in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007