Low-complexity 3D target tracking in Wireless Aerial Sensor Networks

S. Uludag, Murat Karakus, Evrim Guler
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引用次数: 9

Abstract

With the proliferation of the application areas of the Wireless Sensor Networks (WSNs) and the technological advances in sensor electronics, target tracking has become one of the most important functions in WSNs. The overwhelming majority of moving target tracking studies in WSNs has assumed either one-dimensional space (lineland), or two-dimensional domain (flat-land). However, many existing, such as environmental monitoring of rugged terrain, structural health monitoring of buildings, underground and underwater WSN applications, and emerging applications, such as search-and-rescue via Micro Aerial Vehicles, reconnaissance by insect-sized flying robots, need target tracking in three-dimensional space. In this study, we assume a Wireless Aerial Sensor Network (WASN) with conventional low-power and low-complexity features and devise a low spatial and temporal complexity moving target tracking mechanism in 3D based on g-h filter that considers measurement errors. Our prefatory simulations show promising preliminary results for our approach in terms of very low inaccuracy rates between the true location of the target and the forecasts at the sink node as well as negligible estimate errors in terms of Euclidean distance.
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无线航空传感器网络中的低复杂度三维目标跟踪
随着无线传感器网络应用领域的不断扩大和传感器电子技术的不断进步,目标跟踪已成为无线传感器网络的重要功能之一。绝大多数无线传感器网络的运动目标跟踪研究要么假设一维空间(直线空间),要么假设二维空间(平面空间)。然而,许多现有的应用,如崎岖地形的环境监测、建筑物结构健康监测、地下和水下WSN应用,以及新兴应用,如微型飞行器的搜索和救援、昆虫大小的飞行机器人的侦察,都需要在三维空间中跟踪目标。在本研究中,我们假设无线航空传感器网络(Wireless Aerial Sensor Network, n)具有传统的低功耗、低复杂度特征,并基于考虑测量误差的g-h滤波器设计了一种低时空复杂度的三维运动目标跟踪机制。我们的初步模拟表明,我们的方法在目标的真实位置与汇聚节点的预测之间的不准确率非常低,并且在欧几里得距离方面的估计误差可以忽略不计。
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