利用丢失一个或两个分量的矢量观测进行方向估计

IF 1.6 4区 工程技术 Q3 INSTRUMENTS & INSTRUMENTATION
Gang Shi, Honglei Shang
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引用次数: 0

摘要

目的传统算法需要至少两个完整的矢量观测值来估计方向参数。然而,传感器故障和干扰可能导致矢量观测的某些分量不可用。本文提出了一种利用丢失一个或两个分量的矢量观测来实现方向估计的算法。该方法的基本原理是利用范数方程和点积方程来估计损失分量,然后利用改进的三分量法来计算姿态矩阵。分别构造了一种和两种丢失分量情况下的具体算法,并从几何角度分析了方向估计的非唯一性。最后,通过实验对所提算法进行了验证。组件的丢失导致了方向信息的丢失。范数方程和点积方程的引入可以部分弥补信息的损失。实验结果和分析表明,所提算法能够提供有效的方向估计,并且在绝大多数应用中,所提算法能够在一个丢失分量情况下提供唯一解,在两个丢失分量情况下提供双解。提出的方法解决了当矢量观测的一个或两个分量不可用时的方向估计问题。范数方程和点积方程的引入降低了计算成本,而从几何角度的分析使非唯一性的研究更加直观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orientation estimation using vector observations with one or two components lost

Purpose

Traditional algorithms require at least two complete vector observations to estimate orientation parameters. However, sensor faults and disturbances may cause some components of vector observations unavailable. This paper aims to propose algorithms to realize orientation estimation using vector observations with one or two components lost.

Design/methodology/approach

The fundamental of the proposed method is using norm equation and dot product equation to estimate the lost components, then, using an improved TRIAD to calculate attitude matrix. Specific algorithms for one and two lost components cases are constructed respectively, and the nonuniqueness of orientation estimation is analyzed from a geometric point of view. At last, experiments are performed to test the proposed algorithms.

Findings

The loss of components results in the loss of orientation information. The introduction of the norm equation and dot product equation can partially compensate for the loss of information. Experiment results and analysis show that the proposed algorithms can provide effective orientation estimation, and in vast majority of applications, the proposed algorithms can provide a unique solution in one lost component case and double solutions in two lost components case.

Originality/value

The proposed method addresses the problem of orientation estimation when one or two components of vector observations are unavailable. The introduction of the norm equation and dot product equation makes the calculation cost low, while the analyses from a geometric point of view makes the study of nonuniqueness more intuitive.

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来源期刊
Sensor Review
Sensor Review 工程技术-仪器仪表
CiteScore
3.40
自引率
6.20%
发文量
50
审稿时长
3.7 months
期刊介绍: Sensor Review publishes peer reviewed state-of-the-art articles and specially commissioned technology reviews. Each issue of this multidisciplinary journal includes high quality original content covering all aspects of sensors and their applications, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of high technology sensor developments. Emphasis is placed on detailed independent regular and review articles identifying the full range of sensors currently available for specific applications, as well as highlighting those areas of technology showing great potential for the future. The journal encourages authors to consider the practical and social implications of their articles. All articles undergo a rigorous double-blind peer review process which involves an initial assessment of suitability of an article for the journal followed by sending it to, at least two reviewers in the field if deemed suitable. Sensor Review’s coverage includes, but is not restricted to: Mechanical sensors – position, displacement, proximity, velocity, acceleration, vibration, force, torque, pressure, and flow sensors Electric and magnetic sensors – resistance, inductive, capacitive, piezoelectric, eddy-current, electromagnetic, photoelectric, and thermoelectric sensors Temperature sensors, infrared sensors, humidity sensors Optical, electro-optical and fibre-optic sensors and systems, photonic sensors Biosensors, wearable and implantable sensors and systems, immunosensors Gas and chemical sensors and systems, polymer sensors Acoustic and ultrasonic sensors Haptic sensors and devices Smart and intelligent sensors and systems Nanosensors, NEMS, MEMS, and BioMEMS Quantum sensors Sensor systems: sensor data fusion, signals, processing and interfacing, signal conditioning.
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