Intelligent Positioning for a Commercial Mobile Platform in Seamless Indoor/Outdoor Scenes based on Multi-sensor Fusion

Wang, Dongsheng; Lu, Yongjie; Zhang, Lei; Jiang, Guoping

doi:10.3390/s19071696

Cited by 13 publications

(4 citation statements)

References 24 publications

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“…The global navigation satellite system (GNSS) can provide outdoor positioning information with meter-level accuracy, which basically meets the needs of outdoor location-based service (LBS) [1]. However, it is not practical to rely on GNSS to provide LBS indoors due to building occlusion [2]. With the large-scale development of indoor/underground space, people are increasingly active in the indoor environment.…”

Section: Introductionmentioning

confidence: 99%

Research on High Precision Positioning Method for Pedestrians in Indoor Complex Environments Based on UWB/IMU

Zhang

Wang

et al. 2023

Remote Sensing

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Location information is the core data in IoT applications, which is the essential foundation for scene interpretation and interconnection of everything, and thus high-precision positioning is becoming an immediate need. However, the non-line-of-sight (NLOS) effect of indoor complex environment on UWB signal occlusion has been a major factor limiting the improvement in ultra-wideband (UWB) positioning accuracy, and the optimization of NLOS error has not yet been studied in a targeted manner. To this end, this paper deeply analyzes indoor scenes, divides NLOS into two forms of spatial occlusion and human occlusion, and proposes a particle filtering algorithm based on LOS/NLOS mapping and NLOS error optimization. This algorithm is targeted to optimize the influence of two different forms of NLOS, using spatial a priori information to accurately judge the LOS/NLOS situation of the anchor, optimizing the NLOS anchor ranging using IMU to project the virtual position, judging whether the LOS anchor is affected by human occlusion, and correcting the affected LOS anchor using the established human occlusion error model. Through experimental verification, the algorithm can effectively suppress two different NLOS errors of spatial structure and human occlusion and can achieve continuous and reliable high-precision positioning and tracking in complex indoor environments.

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Section: Introductionmentioning

confidence: 99%

Research on High Precision Positioning Method for Pedestrians in Indoor Complex Environments Based on UWB/IMU

Zhang

Wang

et al. 2023

Remote Sensing

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“…At present, there are many methods for processing gyroscope signal noise, which can be roughly divided into two categories: one is the based on the model compensation method, that is, modeling the random noise of the gyroscope and offsetting it in accordance with the model, e.g., the Kalman filter method [1,2,3], statistical filtering, etc. ; the other is the direct filtering method, which directly filters the output signal of the gyroscope, e.g., low-pass filtering, Wavelet filtering [4,5,6,7], adaptive filtering [8], and so on.…”

Section: Introductionmentioning

confidence: 99%

Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion

Guo

Hong

2019

Sensors

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As an important inertial sensor, the gyroscope is mainly used to measure angular velocity in inertial space. However, due to the influence of semiconductor thermal noise and electromagnetic interference, the output of the gyroscope has a certain random noise and drift, which affects the accuracy of the detected angular velocity signal, thus interfering with the accuracy of the stability of the whole system. In order to reduce the noise and compensate for the drift of the MEMS (Micro Electromechanical System) gyroscope during usage, this paper proposes a Kalman filtering method based on information fusion, which uses the MEMS gyroscope and line accelerometer signals to implement the filtering function under the Kalman algorithm. The experimental results show that compared with the commonly used filtering methods, this method allows significant reduction of the noise of the gyroscope signal and accurate estimation of the drift of the gyroscope signal, and thus improves the control performance of the system and the stability accuracy.

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“…The system deceives the GNSS receiver by arranging the inverse GNSS sources and transmitting the inversely derived GNSS signal. This technology is used to provide calibration for the inertial navigation system (INS)/magnetometer 46 which is commonly equipped in smartphones and provides continuous positioning. 47 The subsequent structure of this article is organized as follows: section ''Overview'' gives a general introduction to the inverse GNSS positioning method and briefly describes the positioning process and the composition of the system.…”

Section: Introductionmentioning

confidence: 99%

A smart city used low-latency seamless positioning system based on inverse global navigation satellite system technology

Zou

Niu

Chen

et al. 2019

International Journal of Distributed Sensor Networks

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People have to move between indoor and outdoor frequently in city scenarios. The global navigation satellite system signal cannot provide reliable indoor positioning services. To solve the problem, this article proposes a seamless positioning system based on an inverse global navigation satellite system signal, which can extend the global navigation satellite system service into the indoor scenario. In this method, a signal source is arranged at a key position in the room, and the inverse global navigation satellite system signal is transmitted to the global navigation satellite system receiver to obtain a preset positioning result. The indoor positioning service is continued with the inertial navigation system after leaving the key position. The inverse global navigation satellite system seamless positioning system proposed in this article can unify indoor and outdoor positioning using the same receiver. The receiver does not need to re-receive navigation information when the scene changes, which avoids the switching process. Through the design of signal layer coverage, the receiver is in a warm start state, and the users can quickly fix the position when the scenario changes, realizing quick access in a true sense. This enables the ordinary commercial global navigation satellite system receiver to obtain indoor positioning capability without modification, and the algorithm can perform accurate positioning indoors and outdoors without switching.

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Intelligent Positioning for a Commercial Mobile Platform in Seamless Indoor/Outdoor Scenes based on Multi-sensor Fusion

Cited by 13 publications

References 24 publications

Research on High Precision Positioning Method for Pedestrians in Indoor Complex Environments Based on UWB/IMU

Research on High Precision Positioning Method for Pedestrians in Indoor Complex Environments Based on UWB/IMU

Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion

A smart city used low-latency seamless positioning system based on inverse global navigation satellite system technology

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