International Journal of Image and Data Fusion最新文献_第9页

GNSS/MIMU tightly coupled integrated with improved multi-state ZUPT/DZUPT constraints for a Land vehicle in GNSS-denied enviroments GNSS/MIMU与改进的多状态ZUPT/DZUPT约束紧密耦合，用于拒绝GNSS环境中的陆地车辆

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-10-13 DOI: 10.1080/19479832.2020.1829718

Yipeng Ning, Wengang Sang, Guobiao Yao, Jingxue Bi, Shida Wang

{"title":"GNSS/MIMU tightly coupled integrated with improved multi-state ZUPT/DZUPT constraints for a Land vehicle in GNSS-denied enviroments","authors":"Yipeng Ning, Wengang Sang, Guobiao Yao, Jingxue Bi, Shida Wang","doi":"10.1080/19479832.2020.1829718","DOIUrl":"https://doi.org/10.1080/19479832.2020.1829718","url":null,"abstract":"ABSTRACT A GNSS/INS integrated navigation system has been intensively developed and widely applied in multiple areas. It can provide high accuracy position, velocity and attitude for vehicle with appropriate data fusion algorithm. However, the overall performance of a low-cost GNSS/MEMS IMU frequently degrades in shaded environment. The traditional constraints GNSS/MIMU algorithm based on zero-velocity detection can effectively increase positioning performance, but easily be susceptible to false detection. This article aims to improve a ZUPT/DZUPT constraints model to improve the accuracy of navigation solutions during satellites signal blockages for different motion states. Firstly, we present a tightly coupled strategy to integrate GPS/BDS and INS by applying EKF. Then, a compositive static zero-velocity detection scheme is carried out by using the Vondrak low pass filter, GNSS/INS calculated velocity and the original data of INS. Meanwhile, a dynamic ZUPT constraint model is also constructed based on the motion characteristics of vehicle. An vehicle test was performed to validate the new algorithm. The results indicate that proposed method can effectively improve the success rate of zero-velocity detection. When the satellite signal is interrupted for 120 s, the position and velocity accuracy of the vehicle are improved by 74.7%~ 96% and 47%~ 86.2% respectively.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1829718","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48800079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

WiFi indoor positioning based on regularized online sequence extreme learning machine 基于正则化在线序列极限学习机的WiFi室内定位

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-10-01 DOI: 10.1080/19479832.2020.1821100

Ye Tao, Long Zhao, Xiaorong Shen, Zhinpeng Chen, Qieqie Zhang

{"title":"WiFi indoor positioning based on regularized online sequence extreme learning machine","authors":"Ye Tao, Long Zhao, Xiaorong Shen, Zhinpeng Chen, Qieqie Zhang","doi":"10.1080/19479832.2020.1821100","DOIUrl":"https://doi.org/10.1080/19479832.2020.1821100","url":null,"abstract":"ABSTRACT WiFi positioning based on fingerprint has received widespread attention and practical applications. However, the fingerprints are susceptible to environmental changes, such as shadowing, multipath, temperature, humidity and obstacles. Due to the instability of received signal strength (RSS), it brings plenty of difficult for WiFi positioning with high accuracy. In this paper, a regularised online sequence extreme learning machine with forgetting parameters (FP-ELM) is adopted to solve the issue accordingly. Forgetting factor and regular factor are adopted in FP-ELM to cope with the time-varying nature of RSS and overcome the issue of irreversible matrix in OS-ELM. The fast running speed of the online sequence extreme learning machine (OS-ELM) is also maintained in FP-ELM. Extensive experiments are carried out in simulation and real experimental areas to explore the characteristics of FP-ELM. Moreover, the positioning results of FP-ELM are compared with the conventional algorithms (OS-ELM and KNN). The simulation and experimental results show when the regular factor is set properly, the positioning result based on FP-ELM algorithm is better than conventional algorithms Figures 1.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1821100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43307138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Robust Unscented Kalman Filter applied to Ultra-wideband Positioning 一种鲁棒无气味卡尔曼滤波在超宽带定位中的应用

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-09-22 DOI: 10.1080/19479832.2020.1813816

Chuanyang Wang, Yipeng Ning, Xin Li, Haobo Li

{"title":"A Robust Unscented Kalman Filter applied to Ultra-wideband Positioning","authors":"Chuanyang Wang, Yipeng Ning, Xin Li, Haobo Li","doi":"10.1080/19479832.2020.1813816","DOIUrl":"https://doi.org/10.1080/19479832.2020.1813816","url":null,"abstract":"ABSTRACT Ultra-wideband (UWB) is well suited for indoor positioning due to its high resolution and good penetration through objects. As one of nonlinear filter algorithms, unscented Kalman filter (UKF) is widely used to estimate the position. However, UKF cannot resist the effect of outliers. The performance of the filter algorithm will be inevitably influenced. In this study, a robust UKF (RUKF) method accompanied by hypothesis test and robust estimation is proposed. Furthermore, the simulation and measurement experiments are performed to verify the effectiveness and feasibility of the proposed RUKF. Simulation experiment results are given to demonstrate that the RUKF can effectively control the influences of the outliers being treated as systematic errors and large variance random errors. When the outliers come from the thick-tailed distribution, the robust estimation does not play a role, and the RUKF does not work well. The measured experiment results show that the outliers will be generated in the non-line-of-sight environment whose impact is abnormally serious. The robust estimation can provide relatively reliable optimised residuals and control the influences of the outliers caused by gross errors. We can believe that the proposed RUKF is effective to resist the effects of outliers and improves the positioning accuracy.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1813816","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44470314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Reference trajectory-based coverage analysis method in three-dimensional space for multi-radio integrated navigation systems 基于参考轨迹的多无线电组合导航系统三维空间覆盖分析方法

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-09-15 DOI: 10.1080/19479832.2020.1813814

J. Son, S. Oh, D. Hwang

引用次数: 0

Performance evaluation of low-cost GPS/INS in-motion alignment model under ECEF frame 低成本GPS/INS在ECEF帧下运动对准模型中的性能评估

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-09-02 DOI: 10.1080/19479832.2020.1813815

Yunrui Zhang, Qiuzhao Zhang, Chun Ma

{"title":"Performance evaluation of low-cost GPS/INS in-motion alignment model under ECEF frame","authors":"Yunrui Zhang, Qiuzhao Zhang, Chun Ma","doi":"10.1080/19479832.2020.1813815","DOIUrl":"https://doi.org/10.1080/19479832.2020.1813815","url":null,"abstract":"ABSTRACT Low-cost GPS/INS integration system is the ideal combination of navigation and positioning. However, the sensitivity of low-cost INS is not good enough for the initial alignment in statics base before navigation. Considering this problem, this paper presents an arbitrary misalignment angle error propagation model which does not rely on small misalignment angles assumption and two simplified versions. These models are presented in the ECEF frame approach and are suitable to implement the in-motion alignment with GPS aided. Another three error models based on quaternion, Rodrigues parameters and modified Rodrigues parameters were also proposed. Three experiments were designed to verify the accuracy and computational efficiency of these error models. The experiments’ results showed that the small misalignment angle model was applicable to the small misalignment angle for higher computational efficiency but without improvement of accuracy. And the large misalignment angle is the best error model for the initial alignment of the arbitrary misalignment angle.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1813815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47603137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A fusion method for infrared and visible images based on iterative guided filtering and two channel adaptive pulse coupled neural network 基于迭代引导滤波和双通道自适应脉冲耦合神经网络的红外和可见光图像融合方法

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-08-31 DOI: 10.1080/19479832.2020.1814877

Qiufeng Fan, F. Hou, Feng Shi

引用次数: 1

A multi-focus image fusion method based on watershed segmentation and IHS image fusion 一种基于分水岭分割和IHS图像融合的多焦点图像融合方法

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-07-29 DOI: 10.1080/19479832.2020.1791262

Shaheera Rashwan, A.E. Youssef, B. A. Youssef

引用次数: 3

Practical applications on sustainable development goals in IJIDF 可持续发展目标在IJIDF中的实际应用

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-07-02 DOI: 10.1080/19479832.2020.1755083

Jixian Zhang

引用次数: 0

Accuracy analysis of Bluetooth-Low-Energy ranging and positioning in NLOS environment 近视距环境下蓝牙低能量测距定位精度分析

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-05-25 DOI: 10.1080/19479832.2020.1752314

Deng Yang, Jian Wang, Minmin Wang, Houzeng Han, Yalei Zhang

{"title":"Accuracy analysis of Bluetooth-Low-Energy ranging and positioning in NLOS environment","authors":"Deng Yang, Jian Wang, Minmin Wang, Houzeng Han, Yalei Zhang","doi":"10.1080/19479832.2020.1752314","DOIUrl":"https://doi.org/10.1080/19479832.2020.1752314","url":null,"abstract":"ABSTRACT Aiming at the low accuracy of Bluetooth-Low-Energy ranging and positioning in NLOS environment, a non-line of sight (NLOS) Bluetooth-Low-Energy ranging method based on the NLOS Bluetooth-Low-Energy ranging model and an NLOS Bluetooth-Low-Energy positioning algorithm based on the TLS method and the triangular positioning algorithm are proposed. Firstly, an line-of-sight (LOS) Bluetooth-Low-Energy ranging model is established by RSSI value and actual distance between the Bluetooth-Low-Energy beacon and the terminal equipment. Secondly, based on the LOS Bluetooth-Low-Energy ranging model and the threshold-corrected RSSI peak, an NLOS Bluetooth-Low-Energy ranging model is established. Thirdly, the NLOS RSSI value is processed by the NLOS Bluetooth-Low-Energy ranging model to obtain the optimal ranging value. Finally, high precision positioning coordinates can be obtained by using NLOS Bluetooth-Low-Energy positioning algorithm and optimal Bluetooth-Low-Energy ranging. In this paper, two experiments are carried out, and the experimental results show that: in the range of 7 m, the average ranging accuracy of the improved NLOS Bluetooth-Low-Energy ranging method is 0.37 m, which is improved 49.19% when compared to the traditional method’s results. The average positioning accuracy is 0.4 m using the positioning algorithm proposed in this paper. Therefore, in NLOS environment, the proposed ranging method and positioning algorithm can significantly improve the accuracy of Bluetooth-Low-Energy ranging and positioning.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1752314","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48013980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Enabling real-time and high accuracy tracking with COTS RFID devices 使用COTS RFID设备实现实时高精度跟踪

IF 2.3

International Journal of Image and Data Fusion Pub Date : 2020-04-21 DOI: 10.1080/19479832.2020.1752315

K. Zhao, Binghao Li

引用次数: 3