2017
DOI: 10.1109/tie.2016.2608897
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Distributed Hybrid Particle/FIR Filtering for Mitigating NLOS Effects in TOA-Based Localization Using Wireless Sensor Networks

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Cited by 143 publications
(88 citation statements)
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“…Both centralized and distributed cooperative localization algorithms are IIR filtering approach. Compared to FIR filter approach, such as hybrid particle/FIR filtering [11], composite particle/FIR filtering [12], and deadbeat dissipative FIR filtering [13], the presented algorithms have greater mean square error when there are model uncertainty and/or numerical error in the system, but these proposed algorithms can still meet the needs of practical positioning. And to design filters with the same parameters, FIR approaches need more parameters than these proposed algorithms; this will increase the amount of computation of the DSP.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Both centralized and distributed cooperative localization algorithms are IIR filtering approach. Compared to FIR filter approach, such as hybrid particle/FIR filtering [11], composite particle/FIR filtering [12], and deadbeat dissipative FIR filtering [13], the presented algorithms have greater mean square error when there are model uncertainty and/or numerical error in the system, but these proposed algorithms can still meet the needs of practical positioning. And to design filters with the same parameters, FIR approaches need more parameters than these proposed algorithms; this will increase the amount of computation of the DSP.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…A recurrent neural network was proposed in Choi et al 3 ; it proposed a recurrent neural network (RNN) model, which takes a series of channel state information (CSI) to identify the corresponding channel condition. Based on distributed filter, a new NLOS recognition algorithm was proposed in Pak et al 4 ; it proposes a new NLOS identification algorithm based on distributed filtering to mitigate NLOS effects, including localization failures. Momtaz et al 5 proposed a new algorithm based on subspace method to identify and eliminate NLOS errors.…”
Section: Introductionmentioning
confidence: 99%
“…Practically, these three parameters are manually tuned by matching the parameters with the operating system and are fixed for all state of operation (Jerome Mendes & Araujo, ). Until now, many methods have been proposed to overcome the dynamic system such as Kalman filter (Yang et al, ) and particle filter (Pak, Ahn, Shi, Shmaliy, & Lim, ; Pak, Ahn, Shmaliy, Shi, & Lim, ; Zhang, Zang, Zhao, Fan, & Hao, ). However, in the system with the PID controller, the PID parameters still need to be tuned for each different operation.…”
Section: Introductionmentioning
confidence: 99%