一种新的移动自组织网络TOA-DOA节点定位:实现高性能和低复杂度

Zhonghai Wang, S. Zekavat
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引用次数: 7

摘要

提出了一种应用于移动自组织网络的节点定位新方法。网络由基本节点和目标节点组成。配备天线阵列的基节点能够通过综合到达时间(TOA)和到达方向(DOA)估计独立定位目标节点。此外,基本节点相互配合,通过融合估计的目标节点位置来提高定位精度。将卡尔曼滤波与融合相结合,进一步提高定位性能。将该技术与基于扩展卡尔曼滤波(EKF)的定位技术进行了比较,后者直接融合了多个测量的TOA-DOA。比较标准包括基于误差累积分布函数(CDF)和近似后验Cramer Rao下界(APCRLB)的定位精度、滤波器稳定性和计算复杂度。对比表明,该方法的计算复杂度较小,但PCRLB略大;但与EKF相比,其稳定性更高。这使得它成为移动ad-hoc网络中定位多个目标节点的理想选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new TOA-DOA node localization for mobile ad-hoc networks: Achieving high performance and low complexity
This paper proposes a novel approach for node localization with applications in mobile ad-hoc networks. The network consists of base nodes and target nodes. Base nodes equipped with antenna arrays are capable of localizing target nodes independently via integrated time-of-arrival (TOA) and direction-of-arrival (DOA) estimation. In addition, base nodes cooperate to improve the localization accuracy by fusing the estimated target node positions. Kalman filter is integrated with the fusion to further improve the localization performance. The proposed technique is compared to a localization technique based on extended Kalman filter (EKF), which directly fuses the multiple measured TOA-DOA. The comparison criteria include localization accuracy in terms of error cumulative distribution function (CDF) and approximate posterior Cramer Rao lower bound (APCRLB), filter stability and computational complexity. The comparison confirms that the proposed method involves minor computational complexity, while it demonstrates slightly larger PCRLB; however, compared to EKF its stability is higher. This makes it a good candidate for localizing multiple target nodes in mobile ad-hoc networks.
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