结合模糊分割和遗传算法的航空影像车辆提取方法

利用高分辨率遥感影像实现道路车辆监测在交通管理系统中占有重要地位,然而受成像条件及车辆本身颜色多样性的影响,很难从遥感影像中直接提取道路车辆。为此,本文提出了一种结合遗传算法和数学形态学的遥感影像道路车辆提取方法。首先利用模糊聚类方法建立影像分割模型,并利用遗传算法对其进行求解,从而实现影像中道路、车辆及环境的精确分割;然后对分割结果中不同层进行赋值,实现分割结果的二值化;最后利用数学形态学操作从分割的道路-车辆的二值结果中剔除道路,从而实现道路车辆的提取。利用本文方法对航空影像进行了道路车辆提取试验。试验结果表明,本文方法不仅能够准确识别地面车辆位置,还能精确提取其轮廓线。     

基于交互多模型的水下目标跟踪方法

According to the requirements of real-time performance and reliability in underwater maneuvering target tracking as well as clarifying motion features of the underwater target, an interacting multiple model algorithm based on fuzzy logic inference （FIMM） is proposed. Maneuvering patterns of the target are represented by model sets, including the constant velocity model （CA）, the Singer mode~, and the nearly constant speed horizontal-turn model （HT） in FIMM technology. The simulation results show that compared to conventional IMM, the reliability and real-time performance of underwater target tracking can be improved by FIMM algorithm.     

地图模型的研究

讨论了地图模型的实质,对地图模型的直观性、一览性、抽象性、概括性、可量测性、几何精确性、合成性、几何相似性、地理一致性、单义性、连续性、艺术性等认识论特性和表现形式的多样性、存储量的巨大性、信息传输性、信息多维动态性等信息论特性进行了重点分析了,并阐述了地图模型对计算机制图和地图分析应用的研究意义。     

Population growth and the development of a central place system

This paper describes the spatial and functional evolution of a central place system as market conditions change with population growth. Utilizing a partial equilibrium optimization model, we examine the spatial response of two economic sectors to increases in market populations resulting from natural increase and migration. Response in both sectors is conditioned by threshold demand, with factor prices also affecting one of the sectors. As the central place system evolves it exhibits spatial and functional characteristics that are initially consistent with a Löschian landscape, then a Christallerian landscape at higher populations, while at even larger populations Krugman’s landscape emerges.     

Modeling long-period noise in kinematic GPS applications

We develop and test an algorithm for modeling and removing elevation error in kinematic GPS trajectories in the context of a kinematic GPS survey of the salar de Uyuni, Bolivia. Noise in the kinematic trajectory ranges over 15 cm and is highly autocorrelated, resulting in significant contamination of the topographic signal. We solve for a noise model using crossover differences at trajectory intersections as constraints in a least-squares inversion. Validation of the model using multiple realizations of synthetic/simulated noise shows an average decrease in root-mean-square-error (RMSE) by a factor of four. Applying the model to data from the salar de Uyuni survey, we find that crossover differences drop by a factor of eight (from an RMSE of 5.6 to 0.7 cm), and previously obscured topographic features are revealed in a plan view of the corrected trajectory. We believe that this algorithm can be successfully adapted to other survey methods that employ kinematic GPS for positioning.     

道路工程平面坐标系的统一性理论研究

传统上道路工程勘测、设计、施工各单位统一采用以初测导线点处垂线为基准线、水准面为基准面的,把各相邻测站处局部水准面相连拼接成一个统一带状的平面坐标系统（定义为道路工程渐变平面坐标系）。本文提出顾及地球重力场模型,用GPS直接建立垂线和水准面系统的道路工程渐变平面坐标系的解决方案,从理论上统一了勘测坐标系（GPS平面坐标系）和设计、施工坐标系（道路工程渐变平面坐标系）,消除了其间存在的系统误差。     

基于模糊理论和典型线路的地质灾害评价的GIS方法研究

根据影响区域地质灾害发生的地质因素、地形因素、诱发因素和人为因素,建立区域地质灾害评价指标体系,对典型线路穿越的评价试验区进行地质灾害区域评价.由于地质灾害数据不仅含有不确定性而且还有复杂的模糊性,因而选用模糊评价方法.本文主要通过选取典型线路,采用模糊综合评判,利用GIS来进行,该研究结果表明是科学的、合理的和客观的...     

用模糊ARTMAP算法对CBERS-2数据进行分类

用模糊ARTMAP（fuzzy adaptive resonance theorymap）神经网络算法对CBERS-2数据进行了分类实践。首先介绍了模糊ARTMAP神经网络的算法原理和具体训练分类过程；然后用2004年9月新疆石河子地区的影像数据进行土地利用分类试验，并将分类结果与基于统计的最大似然法（MLC）、反向传播神经网络（BP）的分类结果作比较，总分类精度比MLC和BP算法分别提高9．9％和4．6％。结果表明，模糊ARTMAP对试验区CBERS-2影像上的裸地识别能力很强，对高分辨率的CBERS-2影像可获得很好的分类结果。     

植被的微波散射与吸收特征

被动微波遥感中大尺度像元内植被种类多种多样并且分布不均匀，较低频率下像元尺度内的植被影响可以根据单个散射体的散射与衰减特性获得。本文讨论了任意朝向的各类植被散射体的计算问题。其中叶片和针叶的散射采用了一般化Rayleigh-Gans计算；杆的散射采用了无限长近似理论。关于各类散射体的衰减，本文比较了散射系数和吸收系数之和，与前向散射定理的结果，并对前向定理的适用性进行了讨论。