A Vehicle-Carried INS Positioning Accuracy Improvement Method by Using Lateral Constraint in GPS-Denied Environment

Sun, Chenyan; Li, Kui

doi:10.1109/tvt.2022.3205047

Cited by 7 publications

(2 citation statements)

References 24 publications

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“…Compared to prior research, this study's novelty resides in utilizing speed limit data and trajectory data to estimate container positions during GPS-denied periods. Sun et al [16] proposed a navigation solution for GPS-absent scenarios, reporting errors below 100 m within 60 min. However, this solution necessitates employing relatively sophisticated onboard INS equipment and is confined to a singular testing route.…”

Section: Discussionmentioning

confidence: 99%

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ConGPS: A Smart Container Positioning System Using Inertial Sensor and Electronic Map with Infrequent GPS

Huang,

Song,

Choi

et al. 2023

Sensors

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Real-time global positioning is important for container-based logistics. However, a challenge in real-time global positioning arises from the frequency of both global positioning system (GPS) calls and GPS-denied environments during transportation. This paper proposes a novel system named ConGPS that integrates both inertial sensor and electronic map data. ConGPS estimates the speed and heading direction of a moving container based on the inertial sensor data, the container trajectory, and the speed limit information provided by an electronic map. The directional information from magnetometers, coupled with map-matching algorithms, is employed to compute container trajectories and current positions. ConGPS significantly reduces the frequency of GPS calls required to maintain an accurate current position. To evaluate the accuracy of the system, 280 min of driving data, covering a distance of 360 km, are collected. The results demonstrate that ConGPS can maintain positioning accuracy within a GPS-call interval of 15 min, even if using low-cost inertial sensors in GPS-denied environments.

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Section: Discussionmentioning

confidence: 99%

“…If the GPS call frequency is too low, the container may fail to report those important events. A more innovative approach involves utilizing vehicle state data to predict vehicle location during GPS unavailability [9,16]. This approach primarily relies on state prediction through the application of Kalman filtering.…”

Section: Introductionmentioning

confidence: 99%

ConGPS: A Smart Container Positioning System Using Inertial Sensor and Electronic Map with Infrequent GPS

Huang,

Song,

Choi

et al. 2023

Sensors

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3D localization of wireless sensor IoT nodes based on weighted DV‐Hop algorithm

Zhang,

Cui,

Yan

2024

Adv Control Appl

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With the widespread popularity of smart wearable devices and the rise of emerging Internet of Things applications, such as smart cities, smart homes, and smart cars, the demand for Internet of Things devices is growing. The technology for positioning Internet of Things nodes using traditional wireless sensors only provides approximate location information, which is insufficient for high‐precision applications. To achieve accurate sensor node location in a specific area, this study proposes an advanced weighted distance vector jump location algorithm. This paper proposes using optical wireless networks, a new wireless communication technology, to enhance the distance vector jump algorithm. It is considered the core technology in researching the three‐dimensional positioning of wireless sensor IoT nodes. The experimental data validated that by comparing with existing positioning algorithms, the improved algorithm significantly improved the location accuracy, and its average orientation error was significantly lower than other algorithms. In three cases where the wireless sensor communication radius was between 10 and 30 m, the average positioning errors of the improved algorithm were 0.363, 0.264, and 0.258, respectively. Compared with the pre improved Distance Vector Hop algorithm, its accuracy has increased by 41.1%, indicating the better positioning performance. Overall, the improved weighted algorithm significantly improves the positioning effect, providing strong technical support for the three‐dimensional positioning of wireless sensor Internet of Things nodes.

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Navigating the Future of Agriculture: A Comprehensive Review of Automatic All-Terrain Vehicles in Precision Farming

Padhiary,

Kumar,

Sethi

2024

J. Inst. Eng. India Ser. A

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A Vehicle-Carried INS Positioning Accuracy Improvement Method by Using Lateral Constraint in GPS-Denied Environment

Cited by 7 publications

References 24 publications

ConGPS: A Smart Container Positioning System Using Inertial Sensor and Electronic Map with Infrequent GPS

ConGPS: A Smart Container Positioning System Using Inertial Sensor and Electronic Map with Infrequent GPS

3D localization of wireless sensor IoT nodes based on weighted DV‐Hop algorithm

Navigating the Future of Agriculture: A Comprehensive Review of Automatic All-Terrain Vehicles in Precision Farming

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