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首页> 外文期刊>Sensors Journal, IEEE >Robust Deployment of Dynamic Sensor Networks for Cooperative Track Detection
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Robust Deployment of Dynamic Sensor Networks for Cooperative Track Detection

机译：稳健部署动态传感器网络以进行协作轨道检测

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摘要

The problem of cooperative track detection by a dynamic sensor network arises in many applications, including security and surveillance, and tracking of endangered species. Several authors have recently shown that the quality-of-service of these networks can be statically optimized by placing the sensors in the region of interest (ROI) via mathematical programming. However, if the sensors are subject to external forcing, such as winds or currents, they may be rapidly displaced, and their quality-of-service may be significantly deteriorated over time. The novel approach presented in this paper consists of placing the sensors in the ROI based on their future displacement, which can be estimated from environmental forecasts and sensor dynamic models. The sensor network deployment is viewed as a new problem in dynamic computational geometry, in which the initial positions of a family of circles with time-varying radii and positions are to be optimized subject to sets of algebraic and differential equations. When these equations are nonlinear and time-varying, the optimization problem does not have an exact solution, or global optimum, but can be approximated as a finite-dimensional nonlinear program by discretizing the quality-of-service and the dynamic models with respect to time. Then, a near-optimal solution for the initial sensor positions is sought by means of sequential quadratic programming. The numerical results show that this approach can improve quality-of-service by up to a factor of five compared to existing techniques, and its performance is robust to propagated modeling and deployment errors.
机译：由动态传感器网络进行的协同跟踪检测的问题出现在许多应用中，包括安全性和监视以及对濒危物种的跟踪。几位作者最近表明，可以通过数学编程将传感器放在目标区域（ROI）中，从而静态优化这些网络的服务质量。但是，如果传感器受到外部力（例如风或海流）的影响，它们可能会迅速移位，并且其服务质量可能会随着时间的推移而显着降低。本文提出的新颖方法包括根据传感器的未来位移将它们放置在ROI中，这可以根据环境预测和传感器动态模型进行估算。传感器网络的部署被视为动态计算几何学中的一个新问题，其中具有时变半径的圆族的初始位置和位置将根据代数和微分方程组进行优化。当这些方程是非线性且随时间变化的时，优化问题没有精确的解决方案或全局最优方法，但可以通过离散化服务质量和动态模型来近似为有限维非线性程序。时间。然后，借助于顺序二次编程来寻找初始传感器位置的接近最佳的解决方案。数值结果表明，与现有技术相比，该方法最多可将服务质量提高五倍，并且其性能对于传播的建模和部署错误具有鲁棒性。

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