An Improved Gaussian Filter for Dynamic Positioning Ships With Colored Noises and Random Measurements Loss

Lin, Xin; Jiao, Yuzhao; Zhao, Ding

doi:10.1109/access.2018.2789336

Cited by 23 publications

(5 citation statements)

References 22 publications

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“…22 The author proposed an asynchronous physical layer network coding algorithm for relay nodes considering colored noise and improved packet error rate performance. 26 From the above-surveyed literature, we observed that the physical layer key generation could be applied as a security mechanism for resource constraint networks like IoT, WSN, etc. 24 Luo confirms the presence of colored noise in wireless signals and suggests a Kalman filter-based noise removal technique for the real-time application like localization.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This proposed filter has better performance than the Kalman filter technique. 26 From the above-surveyed literature, we observed that the physical layer key generation could be applied as a security mechanism for resource constraint networks like IoT, WSN, etc. Also, the studies discussed above cover various ways of improving the performance of the key generation system.…”

Section: Literature Reviewmentioning

confidence: 99%

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Performance improvement of wireless secret key generation with colored noise for IoT

Soni

Upadhyay

Kumar

2019

Int J Communication

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Achieving security in the Internet of things (IoT) networks by generating symmetric keys from the wireless channel parameters like received signal strength (RSS) is a promising approach. Despite the easy acquisition of the RSS signal, RSS-based security is less explored for IoT. In this work, we analyze the performance of RSS-based wireless physical layer key generation with correlated colored noise components and proposed a low complexity filtering approach to improve the performance for the IoT network. We started with providing a survey of various recent researches related to RSS-based key generation and also discussed correlated colored noise components with a few of the recent works considering them. Further, we analyze various colored noise components in the time domain by the Allan variance and Ljung-Box test. Furthermore, we develop a key generation model and proposed a moving window averaging-based filtering followed by Lloyd max quantization to improve the BDR performance, degraded due to the presence of correlated colored noise components. The simulation results show that the proposed preprocessing technique has a considerable improvement in the BDR performance, and the keys generated have sufficient randomness, which is verified by NIST test.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Performance improvement of wireless secret key generation with colored noise for IoT

Soni

Upadhyay

Kumar

2019

Int J Communication

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“…Theoretically, a centralized Kalman filter can obtain the optimal estimation of the system state error. However, the centralized Kalman filter needs to process the measurement data of all sensors in a centralized manner; it has computationally intensive and poor fault tolerance [10,11]. Compared with a centralized filter, a decentralized filter has the advantages of less computation and better fault tolerance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive weighted federated Kalman filtering based on Mahalanobis distance and its application in navigation

Gao,

Zong

et al. 2023

IET Communications

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Due to the federal Kalman filter is used to directly fuse the measurement information into the main filter without processing, resulting in the problem of reduced filtering accuracy. An adaptive weighted federated Kalman filtering based on Mahalanobis distance was proposed in this paper. By calculating the Mahalanobis distance between the predicted value and the measurements of the system, the random fluctuation of the measurements is detected. The statistical characteristics of the system measurement noise are adjusted at any time according to random fluctuations in the measurements. And then by using a adaptive amplification factor to dynamically adjust the measurement noise in the subsystems, and reduce the impact of measurement information contamination in subfilters on the main filter. The adaptive federated information distribution coefficient is used to realize the global information fusion of the federal Kalman filter method, to reduce the influence of inaccurate estimation of subfilters on the main filter.Simulation results and comparison analysis prove that the filtering performance of the proposed is better than the traditional federated Kalman filter (FKF) and adaptive FKF, which can improve the accuracy of the integrated navigation system.

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“…Unfortunately, MEMS-based IMUs produce inevitably faulty readings [5]. To tackle the problem, different filters have been already designed and new filters are still emerging [6,7]. The same IMU may be suitable for tracking one kind of motion and insufficient for another.…”

Section: Introductionmentioning

confidence: 99%

A Potrace-based Tracing Algorithm for Prescribing Two-dimensional Trajectories in Inertial Sensors Simulation Software

Ціж¹,

Biotechnologies²,

Marusenkova³

2021

IJMECS

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Inertial measurement units based on microelectromechanical systems are perspectives for motion capture applications due to their numerous advantages. A motion trajectory is restored using a well-known navigation algorithm, which assumes integration of the signals from accelerometers and gyroscopes. Readings of both sensors contain errors, which quickly accumulate due to integration. The applicability of an inertial measurement unit for motion capture depends on the trajectory being tracked and can be predicted due to the simulation of signals from inertial sensors. The first simulation step is prescribing a motion trajectory and corresponding velocities. The existing simulation software provides no user-friendly graphical tools for the completion of this step. This work introduces an algorithm for the simulation of accelerometer signals upon a two-dimensional trajectory drawn with a computer mouse and then vectorized. We propose a modification of the Potrace algorithm for tracing motion trajectories. Thus, a trajectory and velocities can be set simultaneously. The obtained results form a basis for simulating three-dimensional motion trajectories since the latter can be represented by three mutually orthogonal two-dimensional projections.

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An Improved Gaussian Filter for Dynamic Positioning Ships With Colored Noises and Random Measurements Loss

Cited by 23 publications

References 22 publications

Performance improvement of wireless secret key generation with colored noise for IoT

Performance improvement of wireless secret key generation with colored noise for IoT

Adaptive weighted federated Kalman filtering based on Mahalanobis distance and its application in navigation

A Potrace-based Tracing Algorithm for Prescribing Two-dimensional Trajectories in Inertial Sensors Simulation Software

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