Connectivity-Based Sensor Localization for Anisotropic Networks by Stress Relaxation

Shioda, Shigeo; Komatsu, Junya; Nishihara, Keiichi

doi:10.1109/vtcfall.2015.7390878

Cited by 6 publications

(1 citation statement)

References 19 publications

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“…These methods use a centralized algorithm in which a central processor collects the sensor data, solves the optimization problems, and localizes all the sensors. One of the range-free-based cooperative localization methods is connectivity-based localization [16]- [18]. This method defines two sensors that can receive wireless signals as "near" and then localizes the sensors based on the connection relationship expressed by the "near/far" binary value.…”

Section: Related Workmentioning

confidence: 99%

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

et al. 2021

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A sensor response-based localization technology that uses the non-geotagged responses of environmental object detection sensors to estimate the positions of sensors in a defined observation area was proposed in a previous study. That method is based on the concept that the proximity relationships among sensors obtained from the closeness of the sensor response times or collected data similarities. However, since that study was limited to simulation-based experiments, this study extends the scheme to experiments involving real devices, simulated environments, and ideal environments to ascertain the accuracy of localization estimates produced using real devices. We also aimed at extracting the problems that must be resolved before the proposed technology can be put into practical use. Even if clock synchronization between the sensors was impossible, the proximity relationships among them could be estimated using before-after detection time relationships, thus confirming that sensor locations could be estimated based on these proximity relationships. In a real device experiment using 20 sensors indoors at 20.25 2 , we confirmed that the average localization error was 0.84 m. Based on those results and other findings resulting from this study, we determined that the primary factor related to increased sensor localization errors was the number of incorrectly constructed sensor pairs. The results of this study are expected to facilitate the realization of physical world sensing using sensor response-based localization technology.

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Section: Related Workmentioning

confidence: 99%

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

et al. 2021

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Environment Sensing Based on Non-Geotagged Sensor Data

Shioda

Ohashi

2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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Sensor Response-Based Localization Using Spatial Correlation of Nongeotagged Data

Shiraki,

Shioda,

Matsuda

2024

IEEE Sensors J.

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Sensor devices in future wireless communication systems such as beyond fifth generation (Beyond 5G) and sixth generation (6G) require highly accurate location information. Owing to high power consumption and cost, global navigation satellite system receivers may not be installed on sensor devices, requiring the localization of sensor devices on a wireless sensor network (WSN). In many WSN applications, a spatially dense sensor installation is required to achieve satisfactory coverage. When object detectiontype sensor devices are installed at high density, the responses of spatially proximate sensors are highly correlated. In other words, these sensor responses indirectly include location information. Based on this consideration, we proposed a sensor localization method using the spatial correlation of nongeotagged sensor response data and evaluated its performance. Our method enables location estimation from the response data obtained during environmental monitoring, even for sensors that are not equipped with range functions. The simulation experiments showed that a more accurate sensor localization is possible with an error of 1 m using a wider sensor detection range, even with rough proximity pair ratio settings. In addition, we verified that there is a trade-off between localizability and observability during environmental monitoring, such as the visualization of vehicle positions from sensor responses. Our proposed method may be applied to future urban environments with a large number of sensor devices installed for environmental monitoring.

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Connectivity-Based Sensor Localization for Anisotropic Networks by Stress Relaxation

Cited by 6 publications

References 19 publications

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

Environment Sensing Based on Non-Geotagged Sensor Data

Sensor Response-Based Localization Using Spatial Correlation of Nongeotagged Data

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