• 제목/요약/키워드: Directional Probabilistic Data Association

검색결과 1건 처리시간 0.015초

An Indoor Localization Algorithm based on Improved Particle Filter and Directional Probabilistic Data Association for Wireless Sensor Network

  • Long Cheng;Jiayin Guan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권11호
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    • pp.3145-3162
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    • 2023
  • As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.