Direct Target Tracking by Distributed Gaussian Particle Filtering for Heterogeneous Networks

Xia, Wei; Sun, Meiqiu; Wang, Qian

doi:10.1109/tsp.2020.2971449

Cited by 20 publications

(5 citation statements)

References 33 publications

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“…This algorithm, which is based on a state transition model has been proven to obtain good levels of gas diffusion boundary for early warning, as well as to reduce communication delay time between layers and maximise the energy efficiency of perception layer, i.e., energy consumption for data reporting. Extensive simulation results highlighted how, compared with other gas detection algorithms presented in literature [36], [37], the proposed gas detection algorithm achieve better performances in terms of average communication delay, reduced energy consummation, and lower error detection.…”

Section: A Dt In the Context Of Iotmentioning

confidence: 95%

Digital Twin for 6G: Taxonomy, Research Challenges, and the Road Ahead

Masaracchia

Sharma

Canberk

et al. 2022

IEEE Open J. Commun. Soc.

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The concept of digital twin (DT) is constantly revealing as a key enabling technology for the deployment of mobile communication services envisaged for the sixth-generation (6G) Internet-of-Things (IoT). This paper aims at providing a comprehensive review of the current state-of-the-art DT-enabled 6G oriented network services. The main characteristics of this new key enabling technology and its critical aspects are highlighted. An overview of the 6G network requirements for the deployment of its innovative envisioned services is firstly provided, emphasizing how the DT concept represents a complementary key enabling technology for them. This is followed by a brief introduction of the DT technology. Subsequently, a comprehensive classification and analysis of the research advancements on DT-enabled 6G services currently available in literature is provided. This paper is concluded by highlighting the most representative challenges and future directions necessary for the deployment of this promising and innovative technology.INDEX TERMS Beyond fifth-generation (5G) network, Digital Twin (DT), Internet of Things (IoT), Internet of Vehicles (IoV), sixth-generation (6G) network.

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Section: A Dt In the Context Of Iotmentioning

confidence: 95%

Digital Twin for 6G: Taxonomy, Research Challenges, and the Road Ahead

Masaracchia

Sharma

Canberk

et al. 2022

IEEE Open J. Commun. Soc.

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“…Remark 1. In addition to the proposed likelihood, another possibility is to adopt the GLRT-based likelihood which can be easily obtained by extending the results of [21]. The derivation details of the GLRT-based likelihood for DJDT are detailed in Appendix A.…”

Section: Compute the Likelihood Ratio With Equationmentioning

confidence: 99%

“…In [19], a new likelihood was derived on the basis of an unknown deterministic signal and an unknown random Gaussian signal, which is radiated by moving the transmitter impinging on receivers and the posterior CRB (PCRB). In [20], an adaptive Gaussian particle filter was proposed for direct target tracking based on distributed sensor networks, and its further extended work can be referred to in [21], wherein the diffusion strategy has been incorporated for information delivery among sensor networks. In addition, the particle number adaptation strategy has also been discussed.…”

Section: Introductionmentioning

confidence: 99%

Direct Target Joint Detection and Tracking Based on Passive Multi-Static Radar

et al. 2023

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Traditional target tracking is carried out based on the point measurements extracted from the radar resolution cells. This is not suitable for situations of low signal-to-noise ratio (SNR). In this paper, we aim to investigate the problem of the joint detection and tracking (JDT) of a target by directly using the received signals of passive multi-static radar without feeding the signals to matched filters. To this end, a novel likelihood function is proposed exploiting the statistical properties of coherent processing between the reference and surveillance signals. With such a likelihood function, the particle Bernoulli filter is employed to perform direct JDT (DJDT) of the target. A remarkable feature of the proposed method is that it is able to achieve satisfactory performance when the SNR of received signals is low. Furthermore, the proposed method cannot only achieve the existence and kinematic state of the target, but also the time-varying SNR of each receiver, which serves as an important input for sensor adjustment. The performance of the proposed method is verified via simulations.

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“…In order to overcome the aforementioned drawbacks, it has been proposed, in the context of emitter localization, to estimate emitter state directly from the received signals, which has resulted in the direct localization methods. Recently, multiple sensors based direct target tracking algorithms has been proposed exploiting the time delay and/or Copyright © 2022 The Institute of Electronics, Information and Communication Engineers Doppler effects [31]- [33]. These solutions make full use of the information provided by the received signal and their superiority has been proven [34], [35].…”

Section: Introductionmentioning

confidence: 99%

Emitter Tracking via Direct Target Motion Analysis

CHEN

Wei

et al. 2022

IEICE Trans. Fundamentals

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This paper considers tracking of a non-cooperative emitter based on a single sensor. To this end, the direct target motion analysis (DTMA) approach, where the target state is straightforwardly achieved from the received signal, is exploited. In order to achieve observability, the sensor has to perform a maneuver relative to the emitter. By suitably building an approximated likelihood function, the unscented Kalman filter (UKF), which is able to work under high nonlinearity of the measurement model, is adopted to recursively estimate the target state. Besides, the posterior Cramér-Rao bound (PCRB) of DTMA, which can be used as performance benchmark, is also achieved. The effectiveness of proposed method is verified via simulation experiments.

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Direct Target Tracking by Distributed Gaussian Particle Filtering for Heterogeneous Networks

Cited by 20 publications

References 33 publications

Digital Twin for 6G: Taxonomy, Research Challenges, and the Road Ahead

Digital Twin for 6G: Taxonomy, Research Challenges, and the Road Ahead

Direct Target Joint Detection and Tracking Based on Passive Multi-Static Radar

Emitter Tracking via Direct Target Motion Analysis

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