Distributed Radar Target Tracking with Low Communication Cost

In distributed radar,most of existing radar networks operate in the tracking fusion mode which combines radar target tracks for a higher positioning accuracy.However,as the filtering covariance matrix indicating positioning accuracy often occupies many bits,the communication cost from local sensors to the fusion is not always sufficiently low for some wireless communication chan-nels.This paper studies how to compress data for distributed tracking fusion algorithms.Based on the K-singular value decomposition(K-SVD)algorithm,a sparse coding algorithm is presented to sparsely represent the filtering covariance matrix.Then the least square quantization(LSQ)algo-rithm is used to quantize the data according to the statistical characteristics of the sparse coeffi-cients.Quantized results are then coded with an arithmetic coding method which can further com-press data.Numerical results indicate that this tracking data compression algorithm drops the com-munication bandwidth to 4%at the cost of a 16%root mean squared error(RMSE)loss.

Thermal History of Rocks in the Shiwandashan Basin, Southern China: Evidence from Apatite Fission Track Analysis

Based on interpretations of the apatite fission track analysis data for 10 outcrop samples and forward modeling of confined fission track length distributions, the thermal history of rocks in the Shiwandashan basin and its adjacent area, southern China, has been qualitatively and semi quantitatively studied. The results reflect several features of the thermal history. Firstly, all the samples have experienced temperatures higher than 60-70 ℃. Secondly, the time that the basement strata (T 1 b ) on the northwestern side of the Shiwandashan basin were uplifted and exhumed to the unannealed upper crust (with a paleogeotemperature of below 60-70 ℃) is much earlier than the basement rocks ( γ 1 5) on the southeastern side of the basin. Thirdly, the thermal history of samples from the basin can be divided into six stages, i.e., the fast burial and heating stage (220-145 Ma), the transient cooling stage (145-135 Ma), the burial and heating stage (135-70 Ma), the rapid cooling stage (70-50 Ma), the relatively stable stage (50-20 Ma) and another rapid cooling stage (20 Ma to present).

带有CVaR罚的分布鲁棒指数跟踪模型:易求解的转化

提出了一种带有条件在险价值(CVaR)惩罚的分布鲁棒指数跟踪模型,该模型将分布鲁棒优化的思想与CVaR惩罚相结合。模型中概率的不确定性通过随机向量的一阶和二阶矩的置信区域来描述。将该模型由一个“min-max-min”形式的优化问题,等价转化为一个非光滑最小化问题。同时提供了一个近似求解带有连续型随机向量的非光滑极小化问题的离散化方案,通过该方案离散化之后的目标函数包含众多但有限个的非光滑函数的最大化。在较弱的条件下证明了离散化之后的模型收敛到原问题等价转化后的非光滑连续分布模型。采用了光滑投影梯度(Smoothing Projected Gradient,SPG)方法求解离散化后的模型,并证明了由SPG方法产生的迭代点序列的任何聚点都是离散化之后模型的全局最小值点。在2008年1月至2023年7月的纳斯达克日度指数数据集上与先进模型进行比较,数值结果验证了所提模型以及SPG方法的有效性。

Design of a Level-3 electric vehicle charging station using a 1-MW solar system via the distributed maximum power point tracking technique

Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.

不确定环境下含云计算数据中心的电网韧性增强调度

为解决飓风来临前路径不确定时输电线路随机故障等带来的难题,提出了适用于含云计算数据中心的电网韧性增强日前调度策略,并将其构建为两阶段风险规避的分布鲁棒优化问题。以飓风对输电线路的时空影响为出发点,采用蒙特卡洛模拟获得飓风路径不确定时线路的离散故障集合,并构建基于L1距离度量的分布鲁棒模糊集合。然后,在日前调度中,对机组和数据中心进行优化以平衡经济性和电网韧性,并采用追索问题量化其对日间调度的影响,形成两阶段优化问题。随后,对优化问题进行确定性转换与解耦求解。最后,以含4个数据中心的IEEE-RTS系统为测试算例,验证了所提韧性增强策略应对模糊不确定性的有效性。

Semi-global weighted output average tracking of discrete-time heterogeneous multi-agent systems subject to input saturation and external disturbances

In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents.We design both the state feedback and output feedback control protocols for each follower agent.In particular,a distributed state observer is designed for each follower agent that estimates the state of each leader agent.In the output feedback case,state observer is also designed for each follower agent to estimate its own state.With these estimates,we design low gain-based distributed control protocols,parameterized in a scalar low gain parameter.It is shown that,for any bounded set of the initial conditions,these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small.Simulation results illustrate the validity of the theoretical results.

DISTRIBUTED KALMAN FILTERING FUSION WITH PACKET LOSS OR INTERMITTENT COMMUNICATIONS FROM LOCAL ESTIMATORS TO FUSION CENTER

This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.

Multi-Agent Control:A Graph-Theoretic Perspective

Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective.Attention is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph statistics.Some emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development recently.There are over 200 references listed,mostly to recent contributions.

基于无线传感器网络的分散目标跟踪:实际测试平台的开发应用(英文)

In the real world,centralized tracking in a large-scale wireless sensor network (WSN) may not be feasible due to the possible failure of fusion centre and the large communication delay in forwarding measurement data to the fusion centre. Distributed target tracking techniques can be employed by tasking sensor nodes near to the target to perform sensing,target state estimation and selection of future tasking sensor nodes. In this paper,the development and implementation of a prototype ultrasonic WSN test-bed to demonstrate distributed target tracking using the Extended Kalman Filter (EKF) algorithm is described. In the test-bed,a mobile robot is used to simulate the moving target,and static/mobile sensor nodes are deployed to detect and track the target. The sensor nodes and robots are equipped with sonar and MICAZ to receive and process instructions. Experimental evaluation of a number of sensor scheduling schemes are reported which shows the superior tracking performance of our distributed competition based sensor scheduling scheme.