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A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM

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Title: A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Authors: Ge, Yu, 1995, Kaltiokallio, Ossi, Kim, Hyowon, 1987, Jiang, Fan, 1987, Talvitie, Jukka, Valkama, M., Svensson, Lennart, 1976, Kim, Sunwoo, Wymeersch, Henk, 1976
Source: 5G mobil positionering för fordonssäkerhet IEEE Journal on Selected Areas in Communications. 40(7):2179-2192
Subject Terms: Complexity theory, mmWave sensing, simultaneous localization and mapping, Poisson multi-Bernoulli mixture filter, Bistatic sensing, Simultaneous localization and mapping, Kalman filters, Filtering algorithms, Sensors, Computational modeling, extended Kalman filter, Receivers
Description: Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel. To solve the SLAM problem, existing approaches rely on sigma-point or particle-based approximations, leading to high computational complexity, precluding real-time execution. We propose a novel low-complexity SLAM filter, based on the Poisson multi-Bernoulli mixture (PMBM) filter. It utilizes the extended Kalman (EK) first-order Taylor series based Gaussian approximation of the filtering distribution, and applies the track-oriented marginal multi-Bernoulli/Poisson (TOMB/P) algorithm to approximate the resulting PMBM as a Poisson multi-Bernoulli (PMB). The filter can account for different landmark types in radio SLAM and multiple data association hypotheses. Hence, it has an adjustable complexity/performance trade-off. Simulation results show that the developed SLAM filter can greatly reduce the computational cost, while it keeps the good performance of mapping and user state estimation.
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Items – Name: Title
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  Data: A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ge%2C+Yu%22">Ge, Yu</searchLink>, 1995<br /><searchLink fieldCode="AR" term="%22Kaltiokallio%2C+Ossi%22">Kaltiokallio, Ossi</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Hyowon%22">Kim, Hyowon</searchLink>, 1987<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Fan%22">Jiang, Fan</searchLink>, 1987<br /><searchLink fieldCode="AR" term="%22Talvitie%2C+Jukka%22">Talvitie, Jukka</searchLink><br /><searchLink fieldCode="AR" term="%22Valkama%2C+M%2E%22">Valkama, M.</searchLink><br /><searchLink fieldCode="AR" term="%22Svensson%2C+Lennart%22">Svensson, Lennart</searchLink>, 1976<br /><searchLink fieldCode="AR" term="%22Kim%2C+Sunwoo%22">Kim, Sunwoo</searchLink><br /><searchLink fieldCode="AR" term="%22Wymeersch%2C+Henk%22">Wymeersch, Henk</searchLink>, 1976
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>5G mobil positionering för fordonssäkerhet IEEE Journal on Selected Areas in Communications</i>. 40(7):2179-2192
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Complexity+theory%22">Complexity theory</searchLink><br /><searchLink fieldCode="DE" term="%22mmWave+sensing%22">mmWave sensing</searchLink><br /><searchLink fieldCode="DE" term="%22simultaneous+localization+and+mapping%22">simultaneous localization and mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Poisson+multi-Bernoulli+mixture+filter%22">Poisson multi-Bernoulli mixture filter</searchLink><br /><searchLink fieldCode="DE" term="%22Bistatic+sensing%22">Bistatic sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Simultaneous+localization+and+mapping%22">Simultaneous localization and mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filters%22">Kalman filters</searchLink><br /><searchLink fieldCode="DE" term="%22Filtering+algorithms%22">Filtering algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Sensors%22">Sensors</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+modeling%22">Computational modeling</searchLink><br /><searchLink fieldCode="DE" term="%22extended+Kalman+filter%22">extended Kalman filter</searchLink><br /><searchLink fieldCode="DE" term="%22Receivers%22">Receivers</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel. To solve the SLAM problem, existing approaches rely on sigma-point or particle-based approximations, leading to high computational complexity, precluding real-time execution. We propose a novel low-complexity SLAM filter, based on the Poisson multi-Bernoulli mixture (PMBM) filter. It utilizes the extended Kalman (EK) first-order Taylor series based Gaussian approximation of the filtering distribution, and applies the track-oriented marginal multi-Bernoulli/Poisson (TOMB/P) algorithm to approximate the resulting PMBM as a Poisson multi-Bernoulli (PMB). The filter can account for different landmark types in radio SLAM and multiple data association hypotheses. Hence, it has an adjustable complexity/performance trade-off. Simulation results show that the developed SLAM filter can greatly reduce the computational cost, while it keeps the good performance of mapping and user state estimation.
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        Value: 10.1109/JSAC.2022.3155504
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      – Text: English
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        PageCount: 14
        StartPage: 2179
    Subjects:
      – SubjectFull: Complexity theory
        Type: general
      – SubjectFull: mmWave sensing
        Type: general
      – SubjectFull: simultaneous localization and mapping
        Type: general
      – SubjectFull: Poisson multi-Bernoulli mixture filter
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      – SubjectFull: Bistatic sensing
        Type: general
      – SubjectFull: Simultaneous localization and mapping
        Type: general
      – SubjectFull: Kalman filters
        Type: general
      – SubjectFull: Filtering algorithms
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      – SubjectFull: Sensors
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      – SubjectFull: Computational modeling
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      – SubjectFull: extended Kalman filter
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      – SubjectFull: Receivers
        Type: general
    Titles:
      – TitleFull: A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
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            NameFull: Ge, Yu
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              Y: 2022
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            – TitleFull: 5G mobil positionering för fordonssäkerhet IEEE Journal on Selected Areas in Communications
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