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The INS and UWB Fusion System Based on Kalman Filter

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Advances in Intelligent, Interactive Systems and Applications (IISA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 885))

Abstract

Location information is very important for warehouse management, robot or pedestrian positioning. Because of the poor indoor environment, global position system (GPS) cannot reflect the advantages. Therefore, in this paper, a position system based on Kalman Filter (KF) algorithm is proposed, which integrates the information of inertial navigation system (INS) and ultra-wideband system (UWB) to improve the position accuracy. The most critical part of the Kalman Filter is prediction and measuring feedback. At present, inertial navigation technology and ultra-wideband technology have a major part in indoor positioning technology. However, due to their respective disadvantages, it cannot have high precision when using one of them separately. The error of inertial measurement unit (IMU) will increase with time and the ultra-wideband will be affected by multipath effect. The system designed in this paper uses InvenSense’s MPU9150 module and DW1000 module, the UWB measurement information is used to correct the error from IMU. The experimental result show that the positioning accuracy of the fusion system proposed in this paper is obviously higher than that of a single system.

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Authors and Affiliations

  1. University of Science and Technology Bei**g, Bei**g, 100083, China

    Guoxiang Xu, Cheng Xu, Cui Yao, Yue Qi & Jie He

  2. Bei**g Key Laboratory of Knowledge Engineering for Materials Science, Bei**g, 100083, China

    Guoxiang Xu, Cheng Xu, Cui Yao, Yue Qi & Jie He

Authors
  1. Guoxiang Xu
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  2. Cheng Xu
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  3. Cui Yao
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  4. Yue Qi
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  5. Jie He
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Corresponding author

Correspondence to Yue Qi .

Editor information

Editors and Affiliations

  1. Department de Ciències de la Computació, Universitat Politècnica de Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

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Xu, G., Xu, C., Yao, C., Qi, Y., He, J. (2019). The INS and UWB Fusion System Based on Kalman Filter. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_62

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