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Article

Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability

1
Department of Electrical Engineering, Indian Institute of Technology Patna, Patna 801106, India
2
Department of Mathematics, Brunel University London, Uxbridge UB83PH, UK
3
Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S4L8, Canada
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(19), 5689; https://doi.org/10.3390/s20195689
Received: 19 August 2020 / Revised: 14 September 2020 / Accepted: 15 September 2020 / Published: 6 October 2020
This paper focuses on developing a particle filter based solution for randomly delayed measurements with an unknown latency probability. A generalized measurement model that includes measurements randomly delayed by an arbitrary but fixed maximum number of time steps along with random packet drops is proposed. Owing to random delays and packet drops in receiving the measurements, the measurement noise sequence becomes correlated. A model for the modified noise is formulated and subsequently its probability density function (pdf) is derived. The recursion equation for the importance weights is developed using pdf of the modified measurement noise in the presence of random delays. Offline and online algorithms for identification of the unknown latency parameter using the maximum likelihood criterion are proposed. Further, this work explores the conditions that ensure the convergence of the proposed particle filter. Finally, three numerical examples, one with a non-stationary growth model and two others with target tracking, are simulated to show the effectiveness and the superiority of the proposed filter over the state-of-the-art. View Full-Text
Keywords: nonlinear estimation; particle filte; randomly delayed measurements; latency probability nonlinear estimation; particle filte; randomly delayed measurements; latency probability
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MDPI and ACS Style

Tiwari, R.K.; Bhaumik, S.; Date, P.; Kirubarajan, T. Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability. Sensors 2020, 20, 5689. https://doi.org/10.3390/s20195689

AMA Style

Tiwari RK, Bhaumik S, Date P, Kirubarajan T. Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability. Sensors. 2020; 20(19):5689. https://doi.org/10.3390/s20195689

Chicago/Turabian Style

Tiwari, Ranjeet K., Shovan Bhaumik, Paresh Date, and Thiagalingam Kirubarajan. 2020. "Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability" Sensors 20, no. 19: 5689. https://doi.org/10.3390/s20195689

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