L1-norm optimisation of rank deficient GNSS networks by an improved Grey Wolf method

IF 1.2 4区地球科学 Q3 ENGINEERING, CIVIL

Survey Review Pub Date : 2024-03-12 DOI:10.1080/00396265.2024.2327124

V. Mahboub, S. Ebrahimzadeh, A. Baghani, A. Rastegar, M. Zanganeh

引用次数: 0

Abstract

An improved grey wolf optimization (GWO) is proposed for direct L1-norm optimization in rank deficient GNSS networks to detect outliers since the standard GWO and the global optimization (GO) algor...

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用改进的灰狼法优化等级不足的全球导航卫星系统网络的 L1 准则

由于标准灰狼优化（GWO）算法和全局优化（GO）算法都是在GNSS网络中直接进行L1正则优化以检测异常值，因此提出了一种改进的灰狼优化（GWO）算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Survey Review 地学-地球科学综合

CiteScore

3.50

自引率

6.20%

发文量

审稿时长

6 months

期刊介绍： Survey Review is an international journal that has been published since 1931, until recently under the auspices of the Commonwealth Association of Surveying and Land Economy (CASLE). The journal is now published for Survey Review Ltd and brings together research, theory and practice of positioning and measurement, engineering surveying, cadastre and land management, and spatial information management. All papers are peer reviewed and are drawn from an international community, including government, private industry and academia. Survey Review is invaluable to practitioners, academics, researchers and students who are anxious to maintain their currency of knowledge in a rapidly developing field.