| 1. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Chen, Hui, 1992, et al.
(författare)
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Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization
- 2022
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Ingår i: GLOBECOM - IEEE Global Telecommunications Conference. ; , s. 6469-6474
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Konferensbidrag (refereegranskat)abstract
- Radio localization is a key enabler for joint communication and sensing in the fifth/sixth generation (5G/6G) communication systems. With the help of multipath components (MPCs), localization and mapping tasks can be done with a single base station (BS) and single unsynchronized user equipment (UE) if both of them are equipped with an antenna array. However, the antenna array at the UE side increases the hardware and computational cost, preventing localization functionality. In this work, we show that with Doppler estimation and MPCs, localization and mapping tasks can be performed even with a singleantenna mobile UE. Furthermore, we show that the localization and mapping performance will improve and then saturate at a certain level with an increased UE speed. Both theoretical Cram´er-Rao bound analysis and simulation results show the potential of localization under mobility and the effectiveness of the proposed localization algorithm.
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| 3. |
- Ge, Yu, 1995, et al.
(författare)
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A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
- 2022
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Ingår i: IEEE Journal on Selected Areas in Communications. - 0733-8716 .- 1558-0008. ; 40:7, s. 2179-2192
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Tidskriftsartikel (refereegranskat)abstract
- 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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| 4. |
- Kim, Hyowon, 1987, et al.
(författare)
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Cooperative mmWave PHD-SLAM with Moving Scatterers
- 2022
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Ingår i: 2022 25th International Conference on Information Fusion, FUSION 2022.
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Konferensbidrag (refereegranskat)abstract
- Simultaneous localization and mapping (SLAM) using multipath at mmWave frequencies can provide accurate localization in the presence of static landmarks. When radio signals reflected from moving vehicle scatterers (VSs) are observed, the standard SLAM filters exhibit a degraded performance. To address this problem, we propose a probability hypothesis density (PHD)-based SLAM filter, where separate maps are maintained for VS and other types of landmarks. Through a combination of developed (i) local PHD-SLAM and (ii) global map fusion, we demonstrate that the proposed filter can handle the problem.
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| 5. |
- Bartoletti, Stefania, et al.
(författare)
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Introduction and fundamentals
- 2024
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Ingår i: Positioning and Location-based Analytics in 5G and Beyond. - 9781119911463 ; , s. 1-18
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter introduces the book and presents the main principles and fundamentals for positioning and location-based analytics, thus effectively providing the basis for the following chapters. After a brief introduction and motivation for the book, we present the main use cases, verticals, and applications for positioning and location-based analytics. Then, we provide the technical fundamentals for understanding positioning and navigation algorithms, as well as location-based analytics. An introduction to the architectural principles is presented. Finally, an outline of the book chapters is provided.
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| 6. |
- Bartoletti, Stefania, et al.
(författare)
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Positioning methods
- 2024
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Ingår i: Positioning and Location-based Analytics in 5G and Beyond. - 9781119911463 ; , s. 21-50
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter introduces the main positioning methods, starting from the state-of-the-art and following a statistical estimation perspective. This is followed by an in-depth treatment of radio positioning, first focusing on device-based positioning and then on device-free positioning. Finally, recent approaches based on artificial intelligence methods for positioning are detailed.
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| 7. |
- Chen, Hui, et al.
(författare)
-
Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization
- 2022
-
Ingår i: 2022 IEEE Global Communications Conference (GLOBECOM). - Piscataway : IEEE. - 9781665435406 ; , s. 6469-6474
-
Konferensbidrag (refereegranskat)abstract
- Radio localization is a key enabler for joint communication and sensing in the fifth/sixth generation (SG/6G) communication systems. With the help of multipath components (MPCs), localization and mapping tasks can be done with a singlebase station (BS) and single unsynchronized user equipment (UE) if both of them are equipped with an antenna array. However, the antenna array at the UE side increases the hardware and computational cost, preventing localization functionality. In thiswork we show that with Doppler estimation and MPCs, localization and mapping tasks can be performed even with a single antenna mobile UE. Furthermore, we show that the localization and mapping performance will improve and then saturate ata certain level with an increased UE speed. Both theoretical Cramer-Rao bound analysis and simulation results show the potential of localization under mobility and the effectiveness of the proposed localization algorithm. © 2022 IEEE
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| 8. |
- Ge, Yu, 1995, et al.
(författare)
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5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath
- 2020
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 20:16, s. 1-31
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Tidskriftsartikel (refereegranskat)abstract
- 5G communication systems operating above 24 GHz have promising properties for user localization and environment mapping. Existing studies have either relied on simplified abstract models of the signal propagation and the measurements, or are based on direct positioning approaches, which directly map the received waveform to a position. In this study, we consider an intermediate approach, which consists of four phases-downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function. This approach can decompose the problem into simpler steps, thus leading to lower complexity. At the same time, by considering an end-to-end processing chain, we are accounting for a wide variety of practical impairments. Simulation results demonstrate the efficacy of the proposed approach.
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| 9. |
- Ge, Yu, 1995, et al.
(författare)
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5G SLAM with Low-complexity Channel Estimation
- 2021
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Ingår i: 15th European Conference on Antennas and Propagation, EuCAP 2021.
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Konferensbidrag (refereegranskat)abstract
- 5G millimeter-wave signals are beneficial for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment. Channel estimators can exploit received signals to estimate multipath components in terms of delays and angles, which can be used in localization and mapping. Thus, a good channel estimator is essential for 5G SLAM. This paper presents a novel low-complexity multidimensional ESPRIT-based channel estimator and applies it to a 5G SLAM framework. Simulation results demonstrate that the proposed channel estimator can accurately estimate channel information with low computational cost, with limited impact on mapping performance, compared to a tensor-ESPRIT benchmark.
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| 10. |
- Ge, Yu, et al.
(författare)
-
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
- 2022
-
Ingår i: IEEE Journal on Selected Areas in Communications. - Piscataway : IEEE. - 0733-8716 .- 1558-0008. ; 40:7, s. 2179-2192
-
Tidskriftsartikel (refereegranskat)abstract
- 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. © 1983-2012 IEEE.
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