基于FCD的旅行时间估计算法研究

根据FCD(Floating Car Data浮动车数据)的特点建立基于FCD旅行时间估计的Kalman滤波模型以及BP神经网络模型,运用上述两种模型进行路段旅行时间短时预测,路段平均旅行时间为输入变量,输出预测路段的旅行时间,并用实测数据进行分析验证.结果表明,针对路段短时旅行时间估计,Kalman滤波模型方法的预测精度要优于BP神经网络方法.     

An innovative method for the analysis of vehicle movements in roundabouts based on image processing

The objective of this paper is to propose a method, based on the image processing of field survey data, to analyze vehicles movements into roundabouts. This research study consisted of three stages: a field survey to collect vehicular flow images captured by video cameras, the processing of these images using a proprietary software (VeTRA—Vehicle Tracking for Roundabout Analysis), and finally, the analysis of the collected data. The main feature of the software is that it allows the automatic computation of the main variables necessary to rank and evaluate a generic roundabout: the entry/exit (E/E) matrix with classification of vehicles (e.g., heavy, light, and motorbikes), vehicle trajectories, and vehicular speed diagrams along the paths inside the roundabout. The processing system is robust enough to withstand classic problems affecting image processing such as variable wind conditions, cloud cover, shadows, and obstructions. Calibration and error evaluation have been deduced from data collected by a high precision Real Time Kinematic GPS video recording system mounted on a probe vehicle. Data of E/E matrices generated by VeTRA are compared with those manually counted on the corresponding video images. A case study of an existing roundabout is featured in the paper. The results indicate that the software has a high capability of generating the E/E matrix. The analysis of vehicular trajectories with both the plot of curvature diagrams and the corresponding speed diagrams enable the evaluation of driver behavior relative to the geometric shape of the roundabout. Copyright © 2011 John Wiley & Sons, Ltd.     

测量平差模型误差的验后检验

提出了一种将间接平差模型转换为条件平差模型的参数消去方法．该方法通过消去间接平差模型中的所有参数，将其转换为条件平差模型，解决了条件方程式的计算机自动建立问题．在此基础上，给出了基于条件方程闭合差的粗差检测和定位方法，并用实例验证了它的可行性．该方法可检验控制网极条件和坐标条件在内的所有检核条件，增强平差系统检验粗差和定位粗差的能力，较好地解决测量控制网闭合环自动搜索一类基本问题．     

火控系统相关噪声滤波器稳态增益的研究

针对现代战争中火控系统传感器的量测噪声的实际情况,经理论分析与推导,得到了具有相关量测噪声的Kalman滤波稳态增益的关系式,试图对火控系统滤波效能的提高进行实质性探索。     

旁瓣消隐技术在雷达中的应用

旁瓣消隐技术（SLB）是雷达抗有源干扰的有效方法。它采用空间滤波技术，通过比较主、辅天线接收机的输出信号幅度，实现对干扰信号的抑制。介绍了旁瓣消隐的原理，建立雷达旁瓣消隐技术的数学模型。并给出基于DSP的SLB工程实施方案。与传统的对消系统相比，该旁瓣消隐系统具有更好的抗干扰性能。     

应用于列车完整性检测系统的改进型滤波器

列车完整性检测系统是新型车载设备,对防止列车抛车有重要意义。其硬件构架上以MSP430微处理器为主控制器,由ADXL202传感器实现加速度信息采集。作为判据的加速度信息在复杂的行车条件下被干扰。本文以加速度信息为研究对象,进行理论分析、数学建模和结果仿真。文中设计了一个二维的改进型滤波器。主要采用最小二乘滤波思想,选取适当的加权矩阵和遗忘因子,它不需要被估计量和观测量的统计规律,不易发散,完全符合观测数据被随机干扰,难以建立精确模型的特点。为了进一步提高滤波精度在滤波器中设计了一个野值剔除环节,在前期去掉粗大误差。对系统采集的数据进行上述的滤波,显著提高了数据的可靠性。     

合成孔径雷达图像船舶自动检测新方法

针对传统SAR图像船舶自动检测方法在检测近岸目标时存在的普适性不强、计算量大、自动识别差的缺陷,提出了一种新的迭代阈值分割算法,通过消除噪声、分离目标检测出船舶目标,对比验证该方法能自动、快速、准确地检测近岸船舶目标。     

Application of H∞ filtering in the initial alignment of strapdown inertial navigation system

In this paper , the principle of H∞ filtering is discussed and H∞ filter is constructed, which is used in the initial alignment of the strapdown inertial navigation systems(SINS). The error model of SINS is derived. By utilizing constructed H∞ filter, the filtering calculation to that system has been conducted. The simulation results of the misalignment angle are given under the condition of unknown noises. The results show that the process of alignment with H∞ filter is much faster and with excellent robustness.     

基于扩展卡尔曼滤波的船舶纵向运动受扰力与力矩的估计

基于递推最小二乘法设计并实现海浪干扰力和干扰力矩的成型波滤器,对有色的次优卡尔曼滤波和扩展卡尔曼滤波(EKF)的效果进行对比.通过引入成型滤波器,采用EKF,提高了状态估计的精度,实现对随机海浪扰动力和力矩的估计.仿真结果表明,通过扩展卡尔曼滤波对海浪扰动力和力矩进行估计是可行的.     

机动目标滤波的最小二乘方法

基于最小二乘滤波精度分析的解析表达式，得出了最小二乘滤波器记忆长度的优化方法，提出一种目标运动加速度的在线实时估计方法，据此可实现最小二乘滤波器记忆长度的实时优化，形成一种适用于机动目标的基于最小二乘的自适应滤波方法。最后进行数值仿真，验证理论分析与算法的正确性。