无嗅卡尔曼滤波的噪声无源遥测系统参数估计

Kyung-Yup Kim, John-Tark Lee, Dong-Kuk Yu, Young-Sik Park
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引用次数: 3

摘要

本文提出了一种基于无气味卡尔曼滤波(UKF)的噪声无源遥测系统。为了克服一般含IC芯片的无源遥测系统存在的功率限制和估计复杂性等问题,将电感耦合原理应用于无源遥测系统的建模中,并采用UKF算法对其电容参数进行估计。特别地,为了证明UKF的有效跟踪性能,我们将其与线性化的递推最小二乘估计(RLSE)的跟踪性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter Estimation of Noisy Passive Telemetry Sensor System Using Unscented Kalman Filter
In this paper, a noisy passive telemetry sensor system using Unscented Kalman Filter (UKF) is proposed. To overcome these trouble problems such as a power limitation and a estimation complexity that the general passive telemetry sensor system including IC chip has, the principle of inductive coupling was applied to the modelling of a passive telemetry sensor system (PTSS) and its noisy capacitive parameter was estimated by the UKF algorithm. Specially, to show the effective tracking performance of the UKF, we compared with the tracking performance of Recursive Least Square Estimation (RLSE) using linearization.
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