Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energy-efficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle (UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying large-system analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.     

航空电子限时令牌太赫兹互连的实时性能分析

在航空电子设备内部采用太赫兹通信技术实现cm级的板间或芯片互连可以减少引脚和接插件，缩小电子设备的体积，并降低维护成本。针对采用全向天线收发和开关键控（OOK）调制的近距离太赫兹通信网络，通过考虑分子吸收噪声和损耗的点到点通信链路分析，给出太赫兹信道容量计算结果；结合节点间的限时令牌多路访问协议，依据信道容量采用服务曲线模型进行最坏情况下总流量分析（TFA）和隔离流量分析（SFA）；充分考虑概率保证下应用层通信任务的突发度，得到限时令牌太赫兹互连的实时性能分析方法。案例研究表明：相较于时分多址（TDMA）方式，基于限时令牌协议的无冲突多路访问机制可以适应物理层容量和应用层负载的随机变化，保证了更小的延迟，有利于实现航空电子芯片间和板间的太赫兹互连组网和实时通信。     

基于EMD-TFPF的仿生偏振光罗盘去噪方法

为了提高仿生偏振光罗盘定向精度,降低罗盘在进行航向角测量时存在的高斯白噪声,基于经验模态分解(EMD)和时频峰值滤波(TFPF),设计了一种用于仿生偏振光罗盘的EMD-TFPF联合去噪方法.在去噪过程中,首先将含噪声的航向角信号分解为不同的模态,对不同模态采用不同窗长进行时频峰值滤波,进而改善了单一窗长去噪对有用信号造成的衰减,有效提高了去噪算法的自适应能力.经过机载实验验证,采用该方法去噪后的仿生偏振光罗盘可以实现定向精度0.3259°,比原始信号精度提升了18.4％.     

一种基于改进太阳子午线拟合方法的仿生偏振光定向系统

为设计一种自主性强、精度高、抗电磁干扰能力强的定向系统,以昆虫获取大气偏振模式的感知机理为基础,设计了一种新型的成像式仿生偏振光定向系统.该系统使用具有微偏振阵列结构的CMOS相机作为主要的偏振信息采集设备,使用DSP/ARM架构的NVIDIA JETSON TX2嵌入式处理器进行信息解算,具有体积小、运算能力强等优点.通过研究大气偏振模式中偏振度和偏振角图像的对称性,针对已有航向角解算方法在太阳子午线提取精度方面的不足,设计了一种对称轴粗提取之后通过连续旋转法精确提取太阳子午线的算法,最终实现定向精度0.3335°,在最小二乘对称轴粗提取法的基础上定向精度提升了19.05％.     

Pose matters: Pose guided graph attention network for person re-identification

Person re-Identification (reID), aiming at retrieving a person across different cameras, has been playing a more and more important role in the construction of smart city and social security. For deep-learning-based reID methods, it has been proved that using local feature together with global feature could help to give robust representation for person retrieval. Human pose information can provide the locations of human skeleton to effectively guide the network to pay more attention to these key areas, and can also help to reduce the noise distractions from background or occlusions. Based on human pose, a Pose Guided Graph Attention (PGGA) network is proposed in this paper, which is a multi-branch architecture consisting of one branch for global feature and two branches for local key-point features. A graph attention convolution layer is carefully designed to re-assign the contribution weight of each extracted local feature by modeling the similarity relations. The experimental results demonstrate the effectiveness of our approach on discriminative feature learning. Our model achieves the state-of-the-art performance on several mainstream evaluation datasets. A plenty of ablation studies and different kinds of comparison experiments are conducted to prove the effectiveness of this work, including the tests on occluded datasets and cross-domain datasets. Moreover, we further design supplementary tests in practical scenario to indicate the advantage of our work in real-word applications.     

Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

Mobile robots are often subject to multiplicative noise in the target tracking tasks, where the multiplicative measurement noise is correlated with additive measurement noise. In this paper,first, a correlation multiplicative measurement noise model is established. It is able to more accurately represent the measurement error caused by the distance sensor dependence state. Then, the estimated performance mismatch problem of Cubature Kalman Filter(CKF) under multiplicative noise is analyzed. An i...     

Effects of input method and display mode of situation map on early warning aircraft reconnaissance task performance with different information complexities

Early Warning Aircraft(EWA) are the main force for air detection and its Human-Machine Interface(HMI) should be designed to support task efficiency and safety. With the application of advanced input method and interface design in EWA, little is known about their actual usability in terms of human factors and ergonomics. The aim of this study was to investigate the effects of the input method and display mode of the situation map on EWA reconnaissance task performance with different information c...     

一种基于多基线载波相位差测量的欺骗干扰检测方法

由于卫星导航信号到达地面的信号功率较低,且民用部分信息公开,极易受到欺骗干扰信号的影响,从而导致接收机解算出错误的位置、速度或时间.针对传统的欺骗干扰检测与抑制方法不能对欺骗干扰进行测向的问题,提出了一种基于阵列多天线接收信号的载波相位差进行欺骗信号检测与抑制的方法.该方法能够在缺少先验知识的条件下,借鉴相关干涉仪测向...