Environmental reference systems for large-scale spaces

Human navigation in well-known environments is guided by stored memory representations of spatial information. In three experiments (N = 43) we investigated the role of different spatial reference systems when accessing information about familiar objects at different locations in the city in which the participants lived. Our results indicate that two independent reference systems underly the retrieval of spatial knowledge. Environmental characteristics, e.g., the streets at an intersection, determine which headings are easier to imagine at a given location and lead to differences in accessibility of spatial information (orientation-specific behavior). In addition, access to spatial information depends on the relative direction of a location with respect to the imagined heading, such that information about locations imagined in front of oneself is easier to access than about locations towards the back. This influence of an egocentric reference system was found for environmental knowledge as well as map-based knowledge. In light of these reference system effects, position-dependent models of spatial memory for large-scale environments are discussed. To account for the simultaneous effect of an environmental and an egocentric reference system, we present a 2-level model of spatial memory access.     

Human Four-Dimensional Spatial Judgments of Hyper-Volume

The dimensionality limitation of human spatial representations has been a long-lasting, unsolved issue in psychology, mathematics, and philosophy. The present study examined the possibility of human four-dimensional spatial representations using a spatial judgment task on hyper-volume, a novel property unique to higher dimensional space. Observers studied visual simulations of random wireframe hyper-tetrahedrons (4-simplexes) rotating around the y-z plane and judged their hyper-volume by adjusting the size of a 4-D block. Multiple regression analyses showed a significant correlation between the responses and the actual hyper-volume but not the definition-based, lower-dimensional cues such as the mean 3-D volume, providing empirical evidence of human 4-D spatial representations that can support judgments of certain novel, high-dimensional properties.     

A systematic spatial bias in remembering eye positions

Categorical bias in location memory in geometric spaces is well established. The present study assessed the presence of the bias in locating eyes in images of human faces. Participants were presented with digital faces and indicated the position of one of the eyes in both upright and inverted orientations. Biases resulted from participants using multiple sources of accessible information. No differences were found for upright vs. inverted face images. Overall, the data were consistent with the retrieval category adjustment model. These distortions may be considered within the forensic context, when eyewitnesses work with a sketch artist or use a computer program to generate an image of the culprit.     

Assessment of between-floor structural and topological properties on cognitive map development in multilevel built environments

The present study investigated cognitive map development in multilevel built environments. Three experiments were conducted in complex virtual buildings to examine the effects of five between-floor structural factors that may impede the accuracy of humans’ ability to build multilevel cognitive maps. Results from Experiments 1 and 2 (of three experiments) revealed that difficulties in developing multilevel cognitive maps are not solely caused by the z-axis offset, as is suggested in the literature, but are due to the factorial combination of a between-floor overlap and a z-axis offset. Results from Experiment 2 showed that this process becomes substantially more difficult when the reference directions between different floors have an angular offset from each other. Finally, results from Experiment 3 demonstrated that confusing between-floor heading shifts in aligned buildings did not make it reliably harder to build multilevel cognitive maps. The implications of these findings are discussed in terms of theories of mental representations in multilayered three-dimensional spaces, as well as for architectural design.     

Coordinating signs and eye gaze in the depiction of directions and spatial scenes by fluent and L2 signers of Norwegian Sign Language

The current study investigates the coordination of signs and eye gaze during depictions of directions and spatial scenes by fluent and second language (L2) signers of Norwegian Sign Language. First, findings show that fluent and L2 signers make different choices regarding the perspective they use to depict spatial scenes. Second, there is variation within and across groups in relation to how eye gaze is directed during these depictions. Findings suggest that eye gaze is used to establish a vantage point upon a depicted scene, but L2 learners may not always engage in this type of coordination. This study contributes to our understanding of how visual perspective is depicted in signed languages and has implications for signed language pedagogy.     

实数域中的投影法及其在单次快摄阵处理中的应用

阵列处理中计算简单的投影法避免了矩阵特征分解(ＥＶＤ)的庞大计算量,然而仍需进行复数计算。为了进一步减小计算量,提出一种实数域中的投影法,它将投影矩阵及空间谱的计算均简化为实数的计算,从而。使阵处理的计算量大大减少,而且使估计性能保持不变。计算机模拟与实际外场实验数据的计算结果表明了算法的有效性。     

一种低复杂度的Multi-h CPM相干解调算法及FPGA实现

多调制指数连续相位调制（Multi-h Continuous Phase Modulation,Multi-h CPM）是一种恒包络调制,具有多个周期出现的调制指数,因此其频谱效率和功率效率比单调制指数CPM更高,但其接收机的复杂度也随之增加。本文在倾斜相位（Tilted Phase,TP）的基础上采用频率脉冲截断（Frequency Pulse Truncation,FPT）和状态空间分割（State Space Partition,SSP）相结合的方法来降低多调制指数连续相位调制的复杂度,使相位状态由512降低到16,理论损耗约为0.8 dB。同时,对降低复杂度的解调算法在现场可编程门阵列（Field Programmable Gate Arrays, FPGA）上进行了验证。仿真和在线测试的误码率曲线接近理论分析曲线,和常用的128状态解调算法相比,资源消耗降低了约59%。     

基于双时相遥感影像差异信息的深度学习滑坡检测

目前利用高分辨率卫星影像进行滑坡等地质灾害识别逐渐成为研究热点,滑坡目视解译依赖于解译人员的经验,耗时费力且提取精度低,而传统的滑坡自动识别方法易将滑坡和道路、裸地、建筑等多种具有相似光谱信息的地物混淆。针对以上问题,文章使用一种双时相高分辨率卫星影像差异信息的深度学习滑坡检测算法,获取时序影像各个波段和归一化植被指数（Normalized Difference Vegetation Index,NDVI）的差异影像作为深度学习的输入特征。为充分挖掘滑坡前后影像多种信息差异特征,采用了U-net网络模型耦合空洞空间金字塔池化和嵌入注意力机制模块相结合进行滑坡特征提取的方法,该方法增强了滑坡边界信息的保存,能够有效地提取滑坡边界信息和发生剧烈变化的区域。利用上述方法对恩施市和九寨沟进行了滑坡检测,实验结果显示,所取得的综合评价指标值（F1-Score）分别为88.4%和90.53%,误差较小、精度较高。表明该方法能够准确检测出高分卫星数据的滑坡边界,且能保持滑坡的完整性。     

基于事件驱动的容积卡尔曼滤波定位算法

以网络化非线性滤波系统为研究对象,为了平衡系统的通信率和滤波精度之间的矛盾,引入随机事件驱动（stochastic event-triggered）的思想,并在此基础上建立了基于残差检测的事件驱动（detected event-triggered）模型。针对系统的强非线性,将线性随机事件驱动滤波系统中的更新结论推广至非线性系统,推导了两种事件驱动机制在容积卡尔曼滤波（CKF）算法框架中的滤波更新过程,得到了检测事件驱动CKF（DECKF）和随机事件驱动CKF（SECKF）两种算法。最后,通过天基平台空间目标跟踪问题对算法性能进行检验。仿真结果表明,当通信率下降20.64%时,DECKF算法的位置跟踪精度和速度跟踪精度相比标准CKF仅下降了5.50%和7.74%。此外,在通信率相同的情形下,DECKF比SECKF的精度高40%以上,证明检测事件驱动模式优于随机事件驱动模式。