Multi-Sensor Integrated Navigation in Urban and Indoor Environments

Measurement Unit ◽

Indoor Environments ◽

Integrated Navigation ◽

Satellite Systems ◽

Tightly Coupled ◽

Sensor Processing ◽

Dense Urban Environment

The art of multi-sensor processing, or “sensor-fusion,” is the ability to optimally infer state information from multiple noisy streams of data. One major application area where sensor fusion is commonly used is navigation technology. While global navigation satellite systems (GNSS) can provide centimeter-level location accuracy worldwide, they suffer from signal availability problems in dense urban environment and they hardly work indoors. While several alternative backups have been proposed, so far, no single sensor or technology can provide the desirable precise localization in such environments under reasonable costs and affordable infrastructures. Therefore, to navigate through these complex areas, combining sensors is beneficial. Common sensors used to augment/replace GNSS in complex environments include inertial measurement unit (IMU), range sensors, and vision sensors. This chapter discusses the design and implementation of tightly coupled sensor fusion of GNSS, IMU, and light detection and ranging (LiDAR) measurements to navigate in complex urban and indoor environments.

Seamless Indoor-Outdoor Navigation based on GNSS, INS and Terrestrial Ranging Techniques

Journal of Navigation ◽

10.1017/s037346331700042x ◽

2017 ◽

Vol 70 (6) ◽

pp. 1183-1204 ◽

Cited By ~ 6

Author(s):

Wei Jiang ◽

Yong Li ◽

Chris Rizos ◽

Baigen Cai ◽

Wei Shangguan

Keyword(s):

Navigation System ◽

Indoor Environments ◽

Integrated Navigation ◽

Satellite Systems ◽

Integrated Navigation System ◽

Outdoor Environments ◽

Federated Kalman Filter ◽

Indoor And Outdoor Environments ◽

We describe an integrated navigation system based on Global Navigation Satellite Systems (GNSS), an Inertial Navigation System (INS) and terrestrial ranging technologies that can support accurate and seamless indoor-outdoor positioning. To overcome severe multipath disturbance in indoor environments, Locata technology is used in this navigation system. Such a “Locata-augmented” navigation system can operate in different positioning modes in both indoor and outdoor environments. In environments where GNSS is unavailable, e.g. indoors, the proposed system is designed to operate in the Locata/INS “loosely-integrated” mode. On the other hand, in outdoor environments, all GNSS, Locata and INS measurements are available, and all useful information can be fused via a decentralised Federated Kalman filter. To evaluate the proposed system for seamless indoor-outdoor positioning, an indoor-outdoor test was conducted at a metal-clad warehouse. The test results confirmed that the proposed navigation system can provide continuous and reliable position and attitude solutions, with the positioning accuracy being better than five centimetres.

Performance Characterization of GNSS/IMU/DVL Integration under Real Maritime Jamming Conditions

Sensors ◽

10.3390/s18092954 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2954 ◽

Cited By ~ 8

Author(s):

Ralf Ziebold ◽

Daniel Medina ◽

Michailas Romanovas ◽

Christoph Lass ◽

Stefan Gewies

Keyword(s):

Inertial Sensors ◽

Unscented Kalman Filter ◽

Low Cost ◽

Primary Source ◽

Measurement Unit ◽

Doppler Velocity ◽

Satellite Systems ◽

Tightly Coupled ◽

The Baltic

Currently Global Navigation Satellite Systems (GNSSs) are the primary source for the determination of absolute position, navigation, and time (PNT) for merchant vessel navigation. Nevertheless, the performance of GNSSs can strongly degrade due to space weather events, jamming, and spoofing. Especially the increasing availability and adoption of low cost jammers lead to the question of how a continuous provision of PNT data can be realized in the vicinity of these devices. In general, three possible solutions for that challenge can be seen: (i) a jamming-resistant GNSS receiver; (ii) the usage of a terrestrial backup system; or (iii) the integration of GNSS with other onboard navigation sensors such as a speed log, a gyrocompass, and inertial sensors (inertial measurement unit—IMU). The present paper focuses on the third option by augmenting a classical IMU/GNSS sensor fusion scheme with a Doppler velocity log. Although the benefits of integrated IMU/GNSS navigation system have been already demonstrated for marine applications, a performance evaluation of such a multi-sensor system under real jamming conditions on a vessel seems to be still missing. The paper evaluates both loosely and tightly coupled fusion strategies implemented using an unscented Kalman filter (UKF). The performance of the proposed scheme is evaluated using the civilian maritime jamming testbed in the Baltic Sea.

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

UAVS ENHANCED NAVIGATION IN OUTDOOR GNSS DENIED ENVIRONMENT USING UWB AND MONOCULAR CAMERA SYSTEMS

10.5194/isprs-archives-xlii-2-w13-665-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 665-672 ◽

Cited By ~ 1

Author(s):

S. Zahran ◽

A. Masiero ◽

M. M. Mostafa ◽

A. M. Moussa ◽

A. Vettore ◽

...

Keyword(s):

Navigation System ◽

Low Cost ◽

Ultra Wideband ◽

Measurement Unit ◽

Satellite Systems ◽

Monocular Camera ◽

Camera Systems ◽

The Cost

<p><strong>Abstract.</strong> The demand for small Unmanned Aerial Vehicles (UAVs) is massively increasing these days, due to the wide variety of applications utilizing such vehicles to perform tasks that may be dangerous or just to save time, effort, or cost. Small UAVs navigation system mainly depends on the integration between Global Navigation Satellite Systems (GNSS) and Inertial Measurement Unit (INS) to estimate the Positions, Velocities, and Attitudes (PVT) of the vehicle. Without GNSS such UAVs cannot navigate for long periods of time depending on INS alone, as the low-cost INS typically exhibits massive accumulation of errors during GNSS absence. Given the importance of ensuring full operability of the UAVs even during GNSS signals unavailability, other sensors must be used to bound the INS errors and enhance the navigation system performance. This paper proposes an enhanced UAV navigation system based on integration between monocular camera, Ultra-Wideband (UWB) system, and INS. In addition to using variable EKF weighting scheme. The paper also investigates this integration in the case of low density of UWB anchors, to reduce the cost required for such UWB system infrastructure. A GoPro Camera and UWB rover were attached to the belly of a quadcopter, an on the shelf commercial drone (3DR Solo), during the experimental flight. The velocity of the vehicle is estimated with Optical Flow (OF) from camera successive images, while the range measurements between the UWB rover and the stationary UWB anchors, which were distributed on the field, were used to estimate UAV position.</p>

DESIGN AND VALIDATION OF A SURFACE PROFILING APPARATUS FOR AGRICULTURAL TERRAIN ROUGHNESS MEASUREMENTS

INMATEH Agricultural Engineering ◽

10.35633/inmateh-59-19 ◽

2019 ◽

Vol 59 (3) ◽

pp. 169-180 ◽

Cited By ~ 1

Author(s):

Jianguo Yan ◽

Chunguang Wang ◽

Shengshi Xie ◽

Lijuan Wang

Keyword(s):

Sensor Data ◽

Measurement Unit ◽

Full Description ◽

Ongoing Research ◽

Satellite Systems ◽

Surface Profiling ◽

Laser Sensors ◽

Flat Section

How to accurately and efficiently measure the profiles of the terrain on which agricultural machines operate has been an ongoing research topic. In this study, a surface profiling apparatus (profiler) was developed to measure agricultural terrain profiles along parallel tracks. The profiler is mainly composed of sensor frames, an RTK-GNSS system (Real Time Kinematics-Global Navigation Satellite Systems), laser sensors, an Inertial Measurement Unit (IMU) sensor and a data acquisition system. Along with a full description of how the terrain profiles were produced, a methodology to compensate for the tractor motion was included in the sensor data analysis. In field profiling validation, two trapezoidal bumps with known dimensions were used to assess the ability of the terrain profiler to reproduce the vertical profiles of the bumps, resulting in root mean square error (RMSE) of 3.6-4.7 mm and 4.5-5.1 mm with profiling speeds of 1.02 and 2.56 km/h, respectively. In addition, a validation test was also conducted on an asphalt road by profiling a flat road with the measuring wheels of the profiler rolling on the flat section but with the tractor wheels driving over a trapezoidal bump to excite the tractor pitch and roll motion. The measured profiles then also exhibited a flat road, which showed the ability of the profiler to remove the tractor motion from the profiling measurements.

Dynamically Adjusting Filter Gain Method for Suppressing GNSS Observation Outliers in Integrated Navigation

Journal of Navigation ◽

10.1017/s0373463318000334 ◽

2018 ◽

Vol 71 (6) ◽

pp. 1396-1412 ◽

Cited By ~ 2

Author(s):

Lihui Wang ◽

Kangyi Zhi ◽

Bin Li ◽

Yuexin Zhang

Keyword(s):

Inertial Navigation System ◽

Normal Values ◽

External Environment ◽

Processing Method ◽

Integrated Navigation ◽

Satellite Systems ◽

Loosely Coupled ◽

The Impact

Global Navigation Satellite Systems (GNSSs) are easily influenced by the external environment. Signals may be lost or become abnormal thereby causing outliers. The filter gain of the standard Kalman filter of a loosely coupled GNSS/inertial navigation system cannot change with the outliers of the GNSS, causing large deviations in the filtering results. In this paper, a method based on a χ2-test and a dynamically adjusting filter gain method are proposed to detect and separately to suppress GNSS observation outliers in integrated navigation. An indicator of an innovation vector is constructed, and a χ2-test is performed for this indicator. If it fails the test, the corresponding observation value is considered as an outlier. A scale factor is constructed according to this outlier, which is then used to lower the filter gain dynamically to decrease the influence of outliers. The simulation results demonstrate that the observation outlier processing method does not affect the normal values under normal circumstances; it can also discriminate between single and continuous outliers without errors or omissions. The impact time of outliers is greatly reduced, and the system performance is improved by more than 90%. Experimental results indicate that the proposed methods are effective in suppressing GNSS observation outliers in integrated navigation.

An efficient positioning solution in urban canyons using enhanced extended Kalman particle filter

Sensor Review ◽

10.1108/sr-04-2018-0104 ◽

2019 ◽

Vol 39 (3) ◽

pp. 407-416

Author(s):

Qimin Xu ◽

Rong Jiang

Keyword(s):

Particle Filter ◽

Inertial Sensor ◽

Fusion Algorithm ◽

Content Type ◽

Satellite Systems ◽

Tightly Coupled ◽

Reduced Inertial Sensor System ◽

Particle Filter Algorithm ◽

Purpose This paper aims to propose a 3D-map aided tightly coupled positioning solution for land vehicles to reduce the errors caused by non-line-of-sight (NLOS) and multipath interference in urban canyons. Design/methodology/approach First, a simple but efficient 3D-map is created by adding the building height information to the existing 2D-map. Then, through a designed effective satellite selection method, the distinct NLOS pseudo-range measurements can be excluded. Further, an enhanced extended Kalman particle filter algorithm is proposed to fuse the information from dual-constellation Global Navigation Satellite Systems and reduced inertial sensor system. The dependable degree of each selected satellite is adjusted through fuzzy logic to further mitigate the effect of misjudged LOS and multipath. Findings The proposed solution can improve positioning accuracy in urban canyons. The experimental results evaluate the effectiveness of the proposed solution and indicate that the proposed solution outperforms all the compared counterparts. Originality/value The effect of NLOS and multipath is addressed from both the observation level and fusion level. To the authors’ knowledge, mitigating the effect of misjudged LOS and multipath in the fusion algorithm of tightly coupled integration is seldom considered in existing literature.

Measuring the Uncertainty of Probabilistic Maps Representing Human Motion for Indoor Navigation

Mobile Information Systems ◽

10.1155/2016/9595306 ◽

2016 ◽

Vol 2016 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Susanna Kaiser ◽

Maria Garcia Puyol ◽

Patrick Robertson

Keyword(s):

Human Motion ◽

Indoor Navigation ◽

Indoor Environments ◽

Satellite Systems ◽

Mapping Algorithm ◽

Localization And Mapping ◽

History Of ◽

Important Field ◽

Indoor navigation and mapping have recently become an important field of interest for researchers because global navigation satellite systems (GNSS) are very often unavailable inside buildings. FootSLAM, a SLAM (Simultaneous Localization and Mapping) algorithm for pedestrians based on step measurements, addresses the indoor mapping and positioning problem and can provide accurate positioning in many structured indoor environments. In this paper, we investigate how to compare FootSLAM maps via two entropy metrics. Since collaborative FootSLAM requires the alignment and combination of several individual FootSLAM maps, we also investigate measures that help to align maps that partially overlap. We distinguish between the map entropy conditioned on the sequence of pedestrian’s poses, which is a measure of the uncertainty of the estimated map, and the entropy rate of the pedestrian’s steps conditioned on the history of poses and conditioned on the estimated map. Because FootSLAM maps are built on a hexagon grid, the entropy and relative entropy metrics are derived for the special case of hexagonal transition maps. The entropy gives us a new insight on the performance of FootSLAM’s map estimation process.

Problems of creating autonomous navigation systems on geophysical fields

E3S Web of Conferences ◽

10.1051/e3sconf/202131003008 ◽

2021 ◽

Vol 310 ◽

pp. 03008

Author(s):

Vyacheslav Fateev ◽

Dmitrii Bobrov ◽

Murat Murzabekov ◽

Ruslan Davlatov

Keyword(s):

Autonomous Navigation ◽

Navigation Systems ◽

Integrated Navigation ◽

Geophysical Fields ◽

Satellite Systems ◽

Integrated Navigation System ◽

New Methods ◽

The Stability ◽

Global navigation satellite systems, which provide high accuracy of navigation, in certain conditions (in tunnels, in closed rooms, in conditions of interference, etc.) have restrictions on their use. In this regard, in order to ensure “seamless” navigation in any conditions of the situation, it becomes necessary to develop new methods and means to increase the stability of navigation definitions. The article is devoted to the consideration of the problems of creating an integrated navigation system using measurements of the parameters of the Earth’s gravitational and magnetic fields. Requirements for meters of parameters of geophysical fields and navigation charts are considered, a number of new navigation meters, new methods and means of preparing navigation charts are proposed. The ways of development of relativistic geodesy and the possibility of using the achievements of gravitational-wave astronomy in gravimetry are considered.

Low-Cost Indoor Positioning Application Based on Map Assistance and Mobile Phone Sensors

Sensors ◽

10.3390/s18124285 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4285 ◽

Cited By ~ 5

Author(s):

Yi-Shan Li ◽

Fang-Shii Ning

Keyword(s):

Mobile Phone ◽

Indoor Positioning ◽

Navigation Satellite ◽

Indoor Environments ◽

Linear Calibration ◽

Positioning Accuracy ◽

Satellite Systems ◽

Global Navigation ◽

Current mainstream navigation and positioning equipment, intended for providing accurate positioning signals, comprise global navigation satellite systems, maps, and geospatial databases. Although global navigation satellite systems have matured and are widespread, they cannot provide effective navigation and positioning services in covered areas or areas lacking strong signals, such as indoor environments. To solve the problem of positioning in environments lacking satellite signals and achieve cost-effective indoor positioning, this study aimed to develop an inexpensive indoor positioning program, in which the positions of users were calculated by pedestrian dead reckoning (PDR) using the built-in accelerometer and gyroscope in a mobile phone. In addition, the corner and linear calibration points were established to correct the positions with the map assistance. Distance, azimuth, and rotation angle detections were conducted for analyzing the indoor positioning results. The results revealed that the closure accuracy of the PDR positioning was enhanced by more than 90% with a root mean square error of 0.6 m after calibration. Ninety-four percent of the corrected PDR positioning results exhibited errors of <1 m, revealing a desk-level positioning accuracy. Accordingly, this study successfully combined mobile phone sensors with map assistance for improving indoor positioning accuracy.

Accuracy Benchmark of Galileo and EGNOS for Inland Waterways

10.24868/issn.2631-8741.2020.009 ◽

2020 ◽

Author(s):

G Yayla ◽

S Van Baelen ◽

G Peeters

Keyword(s):

Sensor Fusion ◽

Autonomous Navigation ◽

Navigation Systems ◽

Inland Waterways ◽

Satellite Systems ◽

Coordinate Measurement ◽

Measurement Units ◽

Satellite Navigation Systems ◽

While Global Navigation Satellite Systems (GNSS) serve as a fundamental positioning technology for autonomous ships in Inland Waterways (IWW), in order to compensate for unexpected signal outages from constellations due to structures such as bridges and high buildings, it is not uncommon to use a sensor fusion setup with GNSS and Inertial Measurement Units (IMU)/Inertial Navigation Systems (INS). However, the accuracy of this fusion relies on the accuracy of the main localization technology itself. In Europe, Galileo and the European Geostationary Navigation Overlay Service (EGNOS) are two satellite navigation systems under civil control and they provide European users with independent access to a reliable positioning satellite signal, claiming better accuracy than what is offered by other accessible systems. Therefore, considering the potential utilization of these systems for autonomous navigation, in this paper, we discuss the results of a case study for benchmarking the accuracy of Galileo and EGNOS in IWW. We used a Coordinate Measurement Machine (CMM) and a sub-cm Real-Time Kinematic (RTK) service which is available in Flanders to quantify the benchmark reference. The results with and without sensor fusion show that Galileo has a better horizontal accuracy profile than standalone Global Positioning System (GPS), and its augmentation with EGNOS is likely to provide European IWW users more accurate positioning levels in the future.