不可观测数据包丢失情况下交互多模型估计器的性能和稳定性分析。

Hong Lin, James Lam, Zidong Wang, Zhan Shu
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引用次数: 0

摘要

对于有数据包丢失的系统,如果估计器无法观测到数据包丢失状态(PLS),则称该系统为不可观测数据包丢失(UPL)系统。反之,则称为可观测丢包(OPL)系统。本文研究了 UPL 系统的交互多模型(IMM)估计器,主要有两方面的贡献。(i) 不可观测 PLS 的估计精度。对于不稳定的 UPL 系统,我们证明 UPL 系统会随着时间的推移而变成 OPL 系统,因为 PLS 可以随着时间的推移而精确估计。对于稳定的 UPL 系统,存在一个精度阈值,使得 PLS 的估计精度不能优于该阈值。(ii) IMM 估计器的稳定性。对于不稳定的 UPL 系统,我们建立了一个必要条件和充分条件:存在一个阈值,当且仅当数据包到达率大于该阈值时,IMM 估计器几乎在所有地方都是稳定的。对于稳定的 UPL 系统,我们证明了 IMM 估计器是稳定的,无论数据包到达率的值是多少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance and stability analysis of interacting multiple model estimator under unobservable packet loss.

For a system with packet loss, if the estimator cannot observe the packet-loss status (PLS), the system is called an unobservable-packet-loss (UPL) system. Otherwise, it is called an observable-packet-loss (OPL) system. This paper studies the interacting multiple model (IMM) estimator for UPL systems, and the main contributions are twofold. (i) Estimation accuracy of the unobservable PLS. For an unstable UPL system, we prove that the UPL system will become an OPL one with time, since the PLS can be exactly estimated with time. For a stable UPL system, there exists an accuracy threshold such that the estimation accuracy of the PLS cannot be better than this threshold. (ii) Stability of the IMM estimator. For an unstable UPL system, we establish a necessary and sufficient condition: there exists a threshold such that the IMM estimator is stable almost everywhere if and only if the packet-arrival rate is greater than this threshold. For a stable UPL system, we show that the IMM estimator is stable, no matter what value the packet-arrival rate is.

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