基于无人机航测数据的放射源定位算法研究

IF 1.6 3区物理与天体物理 Q2 NUCLEAR SCIENCE & TECHNOLOGY

Radiation Measurements Pub Date : 2025-04-14 DOI:10.1016/j.radmeas.2025.107437

Jialong Chen , Ai Chen , Jiayue Wang , Yang Liu

{"title":"基于无人机航测数据的放射源定位算法研究","authors":"Jialong Chen , Ai Chen , Jiayue Wang , Yang Liu","doi":"10.1016/j.radmeas.2025.107437","DOIUrl":null,"url":null,"abstract":"<div><div>To improve the accuracy and efficiency of unmanned aerial vehicles (UAVs) in radioactive source detection, a novel localization algorithm is proposed. This algorithm, which is based on the inverse square law and employs the least squares method and clustering techniques to select data points, is capable of quickly and accurately locating point sources in vast open areas. Based on the verification ofthe accuracy of UAV aerial survey data, the feasibility of the algorithm using this data is evaluated. The results indicate that within an area of 150m by 150m, the localization error of the algorithm is less than 1 m. Furthermore, by employing the Kriging interpolation algorithm to reconstruct the radiation field, the localization error can be further reduced to below 0.1 m. These results demonstrate the algorithm's potential for accurately locating radioactive sources.</div></div>","PeriodicalId":21055,"journal":{"name":"Radiation Measurements","volume":"184 ","pages":"Article 107437"},"PeriodicalIF":1.6000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on a radioactive source localization algorithm based on UAV aerial survey data\",\"authors\":\"Jialong Chen , Ai Chen , Jiayue Wang , Yang Liu\",\"doi\":\"10.1016/j.radmeas.2025.107437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>To improve the accuracy and efficiency of unmanned aerial vehicles (UAVs) in radioactive source detection, a novel localization algorithm is proposed. This algorithm, which is based on the inverse square law and employs the least squares method and clustering techniques to select data points, is capable of quickly and accurately locating point sources in vast open areas. Based on the verification ofthe accuracy of UAV aerial survey data, the feasibility of the algorithm using this data is evaluated. The results indicate that within an area of 150m by 150m, the localization error of the algorithm is less than 1 m. Furthermore, by employing the Kriging interpolation algorithm to reconstruct the radiation field, the localization error can be further reduced to below 0.1 m. These results demonstrate the algorithm's potential for accurately locating radioactive sources.</div></div>\",\"PeriodicalId\":21055,\"journal\":{\"name\":\"Radiation Measurements\",\"volume\":\"184 \",\"pages\":\"Article 107437\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2025-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiation Measurements\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1350448725000666\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUCLEAR SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiation Measurements","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1350448725000666","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

为了提高无人机辐射源探测的精度和效率，提出了一种新的辐射源定位算法。该算法基于平方反比定律，采用最小二乘法和聚类技术选择数据点，能够快速准确地定位广大开阔区域的点源。在验证无人机航测数据精度的基础上，对该算法利用该数据的可行性进行了评价。结果表明，在150m × 150m的区域内，该算法的定位误差小于1 m。利用Kriging插值算法重建辐射场，进一步将定位误差降低到0.1 m以下。这些结果证明了该算法在精确定位放射源方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Research on a radioactive source localization algorithm based on UAV aerial survey data

To improve the accuracy and efficiency of unmanned aerial vehicles (UAVs) in radioactive source detection, a novel localization algorithm is proposed. This algorithm, which is based on the inverse square law and employs the least squares method and clustering techniques to select data points, is capable of quickly and accurately locating point sources in vast open areas. Based on the verification ofthe accuracy of UAV aerial survey data, the feasibility of the algorithm using this data is evaluated. The results indicate that within an area of 150m by 150m, the localization error of the algorithm is less than 1 m. Furthermore, by employing the Kriging interpolation algorithm to reconstruct the radiation field, the localization error can be further reduced to below 0.1 m. These results demonstrate the algorithm's potential for accurately locating radioactive sources.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Radiation Measurements 工程技术-核科学技术

CiteScore

4.10

自引率

20.00%

发文量

116

审稿时长

48 days

期刊介绍： The journal seeks to publish papers that present advances in the following areas: spontaneous and stimulated luminescence (including scintillating materials, thermoluminescence, and optically stimulated luminescence); electron spin resonance of natural and synthetic materials; the physics, design and performance of radiation measurements (including computational modelling such as electronic transport simulations); the novel basic aspects of radiation measurement in medical physics. Studies of energy-transfer phenomena, track physics and microdosimetry are also of interest to the journal. Applications relevant to the journal, particularly where they present novel detection techniques, novel analytical approaches or novel materials, include: personal dosimetry (including dosimetric quantities, active/electronic and passive monitoring techniques for photon, neutron and charged-particle exposures); environmental dosimetry (including methodological advances and predictive models related to radon, but generally excluding local survey results of radon where the main aim is to establish the radiation risk to populations); cosmic and high-energy radiation measurements (including dosimetry, space radiation effects, and single event upsets); dosimetry-based archaeological and Quaternary dating; dosimetry-based approaches to thermochronometry; accident and retrospective dosimetry (including activation detectors), and dosimetry and measurements related to medical applications.