摘要
传感器网络环境下的融合系统在进行信息采集、传输和处理的过程中,将不可避免的受到网络约束,如节点信息的相关性,信息传输的延迟无序性等。延迟的随机性必然使得有序采样的信息到达融合中心时呈现无序的现象,而信息的无序将导致传统基于有序到达的Kalman滤波算法无法直接有效的应用于无序信息系统。然而,现有的基于传统Kalman滤波框架下的无序量测更新算法的研究复杂性相当高,其推导过程和最后的算法公式也都比较复杂,所以,开展新型框架下的融合算法显得非常迫切,也是当前亟待解决的问题。本文较详细的介绍了当前国内外网络环境下无序量测融合算法的研究现状以及存在的问题,并在此基础上提出了进一步研究的方向以及未来的发展趋势。
Fusion system based on sensor networks will face several network constraints when it is collecting,transmission and processing information from local sensors.Such as communication correlation of local sensor information,the random delay disordered arrival of information transmission,and so on.The random of transmission delay must make that the local information sampled orderly arrive in the fusion center out-of-sequence.So the Out-Of-Sequence Information （OOSI） will result that the traditional Kalman filter based on ordered information can not be used effectively for the OOSI system.However,the complexity of the Out-Of-Sequence Measurement （OOSM） algorithms based on the traditional Kalman filter is quite high,and the derivation and the final algorithm formula are also complex.So develop new framework of fusion algorithms are very urgent,which are also the problems to be solved currently.This paper introduces the OOSM fusion algorithms based on the network environment under the domestic,and the existing problems.On this basis,it develops the direction of further study next and the future trend of development.
出处
《自动化与仪器仪表》
2010年第4期134-137,146,共5页
Automation & Instrumentation
