基于随机和多智能体方法的传感器网络控制问题及其应用

A. Sergeenko, O. Granichin
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引用次数: 0

摘要

多目标跟踪是一个经典的信号处理问题,在空中、海上和交通管制等许多应用中都存在。自主传感器网络具有冗余性和可重构性,是多用途跟踪的理想平台。然而,网络实现使得不可能使用经典的集中式方法进行过滤,因为每个传感器的计算能力有限,并且对其他传感器的测量数据的访问有限。除了拓扑限制(每个传感器只能与几个相邻的网络节点通信)之外,传感器之间的通信也会受到限制,例如,由于通信信道的带宽有限,延迟和数据失真。本文提出了一种新的传感器网络多目标分布式跟踪算法,该算法将SPSA算法与局部投票协议相结合。在噪声未知但有限的条件下巩固了算法,优化了算法步长,并进行仿真验证了算法的性能。还描述了该算法的可能应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Problem of Sensor Network Control Based on Randomized and Multi-Agent Approaches and Its Applications
Tracking multiple targets is a classic signal processing problem that occurs in many applications such as air, maritime and traffic control. Autonomous sensor networks serve as desirable platforms for multipurpose tracking due to their redundancy and reconfigurability. However, the network implementation makes it impossible to use the classical centralized approaches to filtering, since each sensor has limited computing power and limited access to the measurements of other sensors. In addition to topological limitations (each sensor can only communicate with several neighboring network nodes), communication between sensors can be limited, for example, due to limited bandwidth of communication channels, delay and data distortion. This article proposes a new algorithm for distributed tracking of multiple targets in a sensor network, which is a combination of the SPSA algorithm and the local voting protocol. The algorithm is consolidated under conditions of unknown but limited noise, the algorithm step size is optimized, and simulation is carried out to confirm the algorithm’s performance. Possible applications for the algorithm are also described.
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