基于IMM固定滞后平滑的多传感器融合定位蟋蟀传感器网络

H. Song, V. Shin
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引用次数: 2

摘要

我们提出了一种通过分布式交互多模型固定滞后平滑器结合使用三边定位算法获得的多个伪测量值来估计在时间延迟传感器场上移动的目标位置的方法。利用三边定位方法的结果定义了间接测量目标位置的伪测量方法,在蟋蟀传感器网络中,由于单个节点只能测量到目标的距离,节点需要组成三个组才能进行三边测量。此外,由于三边测量方法忽略了距离测量误差,因此使用自调谐方法对伪测量模型估计了足够的误差协方差信息。每个不同的组进行局部伪测量,并使用矩阵权融合进行融合。在此基础上,提高了运动目标的定位性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localization Using Multisensor Fusion of IMM Fixed Lag Smoother in a Cricket Sensor Network
We propose an approach for estimating the location of target moving over a time delayed sensor field via a distributed interacting multiple model fixed-lag smoother in conjunction with multiple pseudo measurements obtained using a trilateration positioning algorithm. Proposed pseudo measurements that indirectly measure the target position are defined using the results of trilateration positioning method, in a Cricket sensor network, as single nodes only can measure the distance to the target, the nodes need to form groups of three to be able to perform trilateration. Also, since the trilateration method ignores distance-measurement errors, adequate error covariance information is estimated for pseudo measurement model using a self-tuning method. Each distinct group makes local pseudo measurements with a time delay and fused using matrix weight fusion. Based on these algorithms, localization performance enhancement of a moving target is achieved.
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