Navigation-Journal of the Institute of Navigation最新文献_第5页

Navigation Safety Assurance of a KF-Based GNSS/IMU System: Protection Levels Against IMU Failure 基于kf的GNSS/IMU系统导航安全保障:IMU失效防护等级

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.612

Jinsil Lee, Minchan Kim, D. Min, Sam Pullen,, Jiyun Lee

引用次数: 0

Multi-layered Multi-Constellation Global Navigation Satellite System Interference Mitigation 多层多星座全球导航卫星系统干扰抑制

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.596

C. Gioia, D. Borio

引用次数: 0

Learning GNSS Positioning Corrections for Smartphones Using Graph Convolution Neural Networks 使用图卷积神经网络学习智能手机GNSS定位校正

3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.622

Adyasha Mohanty, Grace Gao

{"title":"Learning GNSS Positioning Corrections for Smartphones Using Graph Convolution Neural Networks","authors":"Adyasha Mohanty, Grace Gao","doi":"10.33012/navi.622","DOIUrl":"https://doi.org/10.33012/navi.622","url":null,"abstract":"<h3>Abstract</h3> Smartphone receivers comprise approximately 1.5 billion global navigation satellite system receivers currently manufactured worldwide. Smartphone receivers provide measurements with lower signal levels and higher noise than commercial receivers. Because of constraints on size, weight, power consumption, and cost, it is challenging to achieve accurate positioning with these receivers, particularly in urban environments. Traditionally, global positioning system measurements are processed via model-based approaches, such as weighted least-squares and Kalman filtering approaches. While model-based approaches can provide meter-level positioning accuracy in a postprocessing manner, these approaches require strong assumptions on the corresponding noise models and require manual tuning of parameters such as covariances. In contrast, learning-based approaches have been proposed that make fewer assumptions about the data structure and can accurately model environment-specific errors. However, these approaches provide lower accuracy than model-based methods and are sensitive to initialization. In this paper, we propose a hybrid framework for learning position correction, which corresponds to the offset between the true receiver position and the estimated position. For a learning-based approach, we propose a graph convolution neural network (GCNN) that can learn different graph structures with multi-constellation and multi-frequency signals. For better initialization of the GCNN, we use a Kalman filter to estimate a coarse receiver position. We then use this coarse receiver position to condition the input features to the graph. We test our proposed approach on real-world data sets from the Google Smartphone Decimeter Challenge and show improved positioning performance over model-based methods such as the weighted least-squares and Kalman filter methods.","PeriodicalId":56075,"journal":{"name":"Navigation-Journal of the Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135445424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Euclidean Distance Matrix-Based Rapid Fault Detection and Exclusion 基于欧氏距离矩阵的快速故障检测与排除

3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.555

Derek Knowles, Grace Gao

引用次数: 1

Probabilistic Map Matching for Robust Inertial Navigation Aiding 鲁棒惯性导航辅助的概率映射匹配

3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.583

Xuezhi Wang, Christopher Gilliam, Allison Kealy, John Close,, Bill Moran

{"title":"Probabilistic Map Matching for Robust Inertial Navigation Aiding","authors":"Xuezhi Wang, Christopher Gilliam, Allison Kealy, John Close,, Bill Moran","doi":"10.33012/navi.583","DOIUrl":"https://doi.org/10.33012/navi.583","url":null,"abstract":"<h3>Abstract</h3> Robust aiding of inertial navigation systems in GNSS-denied environments is critical for the removal of accumulated navigation error caused by the drift and bias inherent in inertial sensors. One way to perform such an aiding uses matching of geophysical measurements, such as gravimetry, gravity gradiometry or magnetometry, with a known geo-referenced map. Although simple in concept, this map-matching procedure is challenging: The measurements themselves are noisy, their associated spatial location is uncertain, and the measurements may match multiple points within the map (i.e., non-unique solution). In this paper, we propose a probabilistic multiple-hypotheses tracker to solve the map-matching problem and allow robust inertial navigation aiding. Our approach addresses the problem both locally, via probabilistic data association, and temporally by incorporating the underlying platform kinematic constraints into the tracker. The estimated platform position from the output of map matching is then integrated into the navigation state using an unscented Kalman filter. Additionally, we present a statistical measure of local map information density — the map feature variability — and use it to weight the output covariance of the proposed algorithm. The effectiveness and robustness of the proposed algorithm are demonstrated using a navigation scenario involving gravitational map matching.","PeriodicalId":56075,"journal":{"name":"Navigation-Journal of the Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136298148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Multi-Epoch Kriging-Based 3D Mapping-Aided GNSS and Doppler Measurement Fusion using Factor Graph Optimization 基于多历元克里格的三维测绘辅助GNSS与多普勒测量融合因子图优化

3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.617

Hoi-Fung Ng, Li-Ta Hsu,, Guohao Zhang

{"title":"Multi-Epoch Kriging-Based 3D Mapping-Aided GNSS and Doppler Measurement Fusion using Factor Graph Optimization","authors":"Hoi-Fung Ng, Li-Ta Hsu,, Guohao Zhang","doi":"10.33012/navi.617","DOIUrl":"https://doi.org/10.33012/navi.617","url":null,"abstract":"<h3>Abstract</h3> Global navigation satellite system (GNSS) signal reflection over buildings degrades positioning performance in urban canyons. Different three-dimensional (3D) mapping-aided (3DMA) GNSS algorithms have been proposed, which utilize 3D building models to aid in positioning. Recently, the candidate-based 3DMA GNSS framework has been applied to examine evenly spaced distributed particles. The particles that best match the observed measurements, that is, with the minimum cost, are identified as the receiver location. However, such particle sampling approaches incur a high computational load and are not robust. In this study, a Kriging-based interpolation method is applied to model the cost function of a 3DMA GNSS based on sampled particles, and the modeled cost function is then integrated with Doppler measurements through factor graph optimization. The regressed model can reduce the computational load by sparsely distributing the particles. Designed experiments with smartphone and commercial-level GNSS receivers demonstrate that the positioning performance can achieve a root mean square error of less than 10 m in Hong Kong and New York City urban canyons.","PeriodicalId":56075,"journal":{"name":"Navigation-Journal of the Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136008778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preliminary Analysis of BDS-3 Performance for ARAIM 基于ARAIM的北斗三号系统性能初步分析

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.553

Hengwei Zhang, Yiping Jiang, Ling Yang

引用次数: 0

Low-Cost, Triple-Frequency, Multi-GNSS PPP and MEMS IMU Integration for Continuous Navigation in Simulated Urban Environments 低成本，三频，多gnss PPP和MEMS IMU集成在模拟城市环境中的连续导航

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.578

Sudha Vana, S. Bisnath

引用次数: 3

Ambiguity-Fixing in Frequency-Varying Carrier Phase Measurements: Global Navigation Satellite System and Terrestrial Examples 变频载波相位测量中的模糊定位:全球导航卫星系统和地面实例

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.580

A. Khodabandeh, P. Teunissen

引用次数: 0

Global Navigation Satellite System Channel Coding Structures for Rapid Signal Acquisition in Harsh Environmental Conditions 恶劣环境下快速信号采集的全球卫星导航系统信道编码结构

IF 2.2 3区地球科学

Navigation-Journal of the Institute of Navigation Pub Date : 2023-01-01 DOI: 10.33012/navi.585

L. Ortega, C. Poulliat

{"title":"Global Navigation Satellite System Channel Coding Structures for Rapid Signal Acquisition in Harsh Environmental Conditions","authors":"L. Ortega, C. Poulliat","doi":"10.33012/navi.585","DOIUrl":"https://doi.org/10.33012/navi.585","url":null,"abstract":"In this article, we present the design of a new navigation message system that includes an error-correcting scheme. This design exploits the “carousel” nature of the broadcast navigation message and facilitates (i) a reduction in the time to first fix (TTFF) and (ii) enhanced error-correcting performance under both favorable and challenging channel conditions. We show here that this combination design requires error-correcting schemes characterized by maxi - mum distance separable (MDS) and full diversity properties. Error-correcting Root low density parity check (Root-LDPC) codes operate efficiently to block various channels and thus can permit efficient and rapid recovery of infor - mation over potentially non-ergodic channels. Finally, to ensure appropriate data demodulation in harsh environmental conditions, we propose the use of Root-LDPC codes endowed with a nested property which will permit them to adjust the channel coding rate depending on the number of information blocks received. The proposed error-correcting combination design was then simulated and compared with the well-known GPS L1C subframe 2 using sev - eral different transmission scenarios. The results of these simulations revealed some enhancement of the error-correcting performance and reductions in TTFF in several specific situations.","PeriodicalId":56075,"journal":{"name":"Navigation-Journal of the Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86164905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0