scholarly journals Pedestrian Positioning Using a Double-Stacked Particle Filter in Indoor Wireless Networks

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3907 ◽  
Author(s):  
Kwangjae Sung ◽  
Hyung Kyu Lee ◽  
Hwangnam Kim
Keyword(s):  
Particle Filter ◽  
Microelectromechanical Systems ◽  
Computational Cost ◽  
Dead Reckoning ◽  
Computation Time ◽  
Multipath Fading ◽  
Indoor Environments ◽  
Mems Devices ◽  
Proposal Distribution ◽  
Localization Scheme

The indoor pedestrian positioning methods are affected by substantial bias and errors because of the use of cheap microelectromechanical systems (MEMS) devices (e.g., gyroscope and accelerometer) and the users’ movements. Moreover, because radio-frequency (RF) signal values are changed drastically due to multipath fading and obstruction, the performance of RF-based localization systems may deteriorate in practice. To deal with this problem, various indoor localization methods that integrate the positional information gained from received signal strength (RSS) fingerprinting scheme and the motion of the user inferred by dead reckoning (DR) approach via Bayes filters have been suggested to accomplish more accurate localization results indoors. Among the Bayes filters, while the particle filter (PF) can offer the most accurate positioning performance, it may require substantial computation time due to use of many samples (particles) for high positioning accuracy. This paper introduces a pedestrian localization scheme performed on a mobile phone that leverages the RSS fingerprint-based method, dead reckoning (DR), and improved PF called a double-stacked particle filter (DSPF) in indoor environments. As a key element of our system, the DSPF algorithm is employed to correct the position of the user by fusing noisy location data gained by the RSS fingerprinting and DR schemes. By estimating the position of the user through the proposal distribution and target distribution obtained from multiple measurements, the DSPF method can offer better localization results compared to the Kalman filtering-based methods, and it can achieve competitive localization accuracy compared with PF while offering higher computational efficiency than PF. Experimental results demonstrate that the DSPF algorithm can achieve accurate and reliable localization with higher efficiency in computational cost compared with PF in indoor environments.

scholarly journals Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Chen Wang ◽  
Xiaoxiao Song ◽  
Weidong Fang ◽  
Fang Chen ◽  
Ioannis Zeimpekis ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Degrees Of Freedom ◽  
Microelectromechanical Systems ◽  
Computation Time ◽  
High Sensitivity ◽  
Mems Devices ◽  
Mechanical Motion ◽  
Parameter Mismatch ◽  
Mems Accelerometer ◽  
Large Bandwidth

AbstractThis paper describes a novel, semiautomated design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sensitivity, large bandwidth, and large fabrication tolerances. The proposed method does not require much computation time or memory. The use of freeform geometries allows more degrees of freedom in the design process, improving the diversity and performance of MEMS devices. A MEMS accelerometer comprising a mechanical motion amplifier is presented to demonstrate the effectiveness of the design approach. Experimental results show an improvement in the product of sensitivity and bandwidth by 100% and a sensitivity improvement by 141% compared to the case of a device designed with conventional orthogonal shapes. Furthermore, excellent immunities to fabrication tolerance and parameter mismatch are achieved.

scholarly journals Combining a Modified Particle Filter Method and Indoor Magnetic Fingerprint Map to Assist Pedestrian Dead Reckoning for Indoor Positioning and Navigation

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 185
Author(s):  
Fang-Shii Ning ◽  
Yu-Chun Chen
Keyword(s):  
Magnetic Field ◽  
Particle Filter ◽  
Dead Reckoning ◽  
Step Length ◽  
Indoor Positioning ◽  
Global Navigation Satellite Systems ◽  
Filter Method ◽  
Indoor Environments ◽  
Positioning Accuracy ◽  
Pedestrian Dead Reckoning

Although advancement has been observed in global navigation satellite systems and these systems are widely used, they cannot provide effective navigation and positioning services in covered areas and areas that lack strong signals, such as indoor environments. Therefore, in recent years, indoor positioning technology has become the focus of research and development. The magnetic field of the Earth is quite stable in an open environment. Due to differences in building and internal structures, this type of three-dimensional vector magnetic field is widely available indoors for indoor positioning. A smartphone magnetometer was used in this study to collect magnetic field data for constructing indoor magnetic field maps. Moreover, an acceleration sensor and a gyroscope were used to identify the position of a mobile phone and detect the number of steps travelled by users with the phone. This study designed a procedure for measuring the step length of users. All obtained information was input into a pedestrian dead reckoning (PDR) algorithm for calculating the position of the device. The indoor positioning accuracy of the PDR algorithm was optimised using magnetic gradients of magnetic field maps with a modified particle filter algorithm. Experimental results reveal that the indoor positioning accuracy was between 0.6 and 0.8 m for a testing area that was 85 m long and 33 m wide. This study effectively improved the indoor positioning accuracy and efficiency by using the particle filter method in combination with the PDR algorithm with the magnetic fingerprint map.

Conjugate Unscented Particle Filter Based Monte Carlo Localization for Mobile Robots

2014 ◽  
Vol 556-562 ◽  
pp. 2266-2269
Author(s):  
Jiang Xue Fei ◽  
Song Yu
Keyword(s):  
Monte Carlo ◽  
Particle Filter ◽  
Dead Reckoning ◽  
Transition Density ◽  
Robot Localization ◽  
Proposal Distribution ◽  
Unscented Transform ◽  
Unscented Particle Filter ◽  
Mobile Robot Localization ◽  
Monte Carlo Localization

For mobile robot localization in known environment, the 5th-order Conjugate Unscented Particle Filter Monte Carlo Localization (CUPF-MCL) algorithm is proposed. CUPF-MCL combines the 5th-order Conjugate Unscented Transform (5th CUT) with Kalman Filter to generate more accuracy particle filter proposal distribution, calculating the transition density up to the 5th-order nonlinearity. In simulation, the performance of CUPF-MCL is compared with that of dead reckoning, PF-MCL, EPF-MCL and UPF-MCL. Results show that CUPF-MCL improves the accuracy of localization.

A New “Bounce-Normal” Boundary in DPD Calculations for the Reduction of Density Fluctuations

2008 ◽  
Author(s):  
Emadaldin Moeendarbary ◽  
K. Y. Lam ◽  
T. Y. Ng
Keyword(s):  
Shear Stress ◽  
Protein Separation ◽  
Dissipative Particle Dynamics ◽  
Computational Cost ◽  
Colloidal Suspensions ◽  
Density Fluctuations ◽  
Polymer Chains ◽  
New Method ◽  
Mems Devices ◽  
Macroscopic Properties

Dissipative Particle Dynamics (DPD) is a mesoscopic fluid modeling method, which facilitates the simulation of the statics and dynamics of complex fluid systems at physically interesting length and time scales. Currently, there are various applications of DPD, such as colloidal suspensions, multi-phase flow, rheology of polymer chains, DNA macromolecular suspension, etc., which employ this technique for their numerical simulation. The DPD technique is capable of modeling macroscopic properties of the bulk flow very well, but difficulties arise if the flows are confined through wall-bounded regions, or when different boundaries simultaneously exist in the simulation domain. These boundaries cause negative effects on the macroscopic temperature, density and velocity profiles, as well as the shear stress and pressure distributions. In particular, the interaction of DPD particles with solid boundaries causes large density fluctuations at the near wall regions. This density distortion leads to pronounced fluctuations in the pressure and shear stress, which are not actually present. To overcome these serious deficiencies, we introduce a new method in this work, which uses a combination of randomly distributed wall particles and a novel reflection adaptation at the wall. This new methodology is simple to implement and incurs no additional computational cost. More importantly, it does not cause any distortion in the macroscopic properties. This novel reflection adaptation is a novel version of the bounce back reflection, which we shall term the bounce-normal reflection. The most important characteristic of this method is that it reduces density fluctuations near the boundaries without affecting the velocity and temperature profiles. This new method is easily applicable to any wall-bounded problem with stationary boundaries and it has a very good consistency with macroscopic features. The eventual objective of this numerical development work is to investigate suspension flow through micro/nano channels of fluidic NEMS/MEMS devices, with applications to DNA and protein separation. These micro/nano channel devices, consisting of many entropic traps, are designed and fabricated for the separation of proteins and long DNA molecules.

Accelerated 3D blind separation of convolved mixtures based on the fast iterative shrinkage thresholding algorithm for adaptive multiple subtraction

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. V99-V113 ◽  
Author(s):  
Zhong-Xiao Li ◽  
Zhen-Chun Li
Keyword(s):  
Field Data ◽  
Optimization Problem ◽  
Computational Cost ◽  
Computation Time ◽  
Blind Separation ◽  
L1 Norm ◽  
Norm Minimization ◽  
Iterative Shrinkage ◽  
Thresholding Algorithm ◽  
Iterative Shrinkage Thresholding

After multiple prediction, adaptive multiple subtraction is essential for the success of multiple removal. The 3D blind separation of convolved mixtures (3D BSCM) method, which is effective in conducting adaptive multiple subtraction, needs to solve an optimization problem containing L1-norm minimization constraints on primaries by the iterative reweighted least-squares (IRLS) algorithm. The 3D BSCM method can better separate primaries and multiples than the 1D/2D BSCM method and the method with energy minimization constraints on primaries. However, the 3D BSCM method has high computational cost because the IRLS algorithm achieves nonquadratic optimization with an LS optimization problem solved in each iteration. In general, it is good to have a faster 3D BSCM method. To improve the adaptability of field data processing, the fast iterative shrinkage thresholding algorithm (FISTA) is introduced into the 3D BSCM method. The proximity operator of FISTA can solve the L1-norm minimization problem efficiently. We demonstrate that our FISTA-based 3D BSCM method achieves similar accuracy of estimating primaries as that of the reference IRLS-based 3D BSCM method. Furthermore, our FISTA-based 3D BSCM method reduces computation time by approximately 60% compared with the reference IRLS-based 3D BSCM method in the synthetic and field data examples.

scholarly journals A Cost-Effective Method for Bulge Prediction in Two Point Incremental Forming

2021 ◽  
Author(s):  
Jaekwang Shin ◽  
Ankush Bansal ◽  
Randy Cheng ◽  
Alan Taub ◽  
Mihaela Banu
Keyword(s):  
Shape Function ◽  
Incremental Forming ◽  
Computational Cost ◽  
Region Of Interest ◽  
Computation Time ◽  
Mesh Size ◽  
Cost Effective ◽  
Summation Method ◽  
Fem Modeling ◽  
Forming Defects

Accurate prediction of the defects occurring in incrementally formed parts has been gaining attention in recent years. This interest is because accurate predictions can overcome the limitation in the advancement of incremental forming in industrial-scale implementation, which has been held back by the increase in the cost and development time due to trial and error methods. The finite element method has been widely utilized to predict the defects in the formed part, e.g., bulge. However, the computation time of running these models and their mesh-size dependency in predicting the forming defects represent barriers in adopting these models as part of CAD-FEM-CAE platforms. Thus, robust analytical and data-driven algorithms must be developed for a cost-effective design of complex parts. In this paper, a new analytical model is proposed to predict the bulge location and geometry in two point incremental forming of an aerospace aluminum alloy AA7075-O for a 67° truncated cone. First, the algorithm calculates the region of interest based on the part geometry. A novel shape function and weighted summation method are then utilized to calculate the amplitude of the instability produced by material accumulation during forming, leading to a bulge on the unformed portion of the sample. It was found that the geometric profile of the part influences the shape function, which is a function created to incorporate the effects of process parameter and boundary condition. The calculated profile in each direction is finalized into one 3-dimensional profile, compared with the experimental results for validation. The proposed model has proven to predict an accurate bulge profile with 95% accuracy comparing with experiments with less than 5% computational cost of FEM modeling.

Microsensors, MEMS and NEMS Based Complex Adaptive Smart Devices and Systems

2001 ◽  
Author(s):  
Vijay K. Varadan
Keyword(s):  
Self Assembly ◽  
Communication Systems ◽  
Microelectromechanical Systems ◽  
System Level ◽  
Smart Devices ◽  
Mems Devices ◽  
Wafer Level ◽  
Sensors And Actuators ◽  
Complex Adaptive ◽  
Microelectronics Industry

Abstract The microelectronics industry has seen explosive growth during the last thirty years. Extremely large markets for logic and memory devices have driven the development of new materials, and technologies for the fabrication of even more complex devices with features sizes now down at the sub micron level. Recent interest has arisen in employing these materials, tools and technologies for the fabrication of miniature sensors and actuators and their integration with electronic circuits to produce smart devices and MicroElectroMechanical Systems (MEMS). This effort offers the promise of: 1. Increasing the performance and manufacturability of both sensors and actuators by exploiting new batch fabrication processes developed for the IC and microelectronics industry. Examples include micro stereo lithographic and micro molding techniques. 2. Developing novel classes of materials and mechanical structures not possible previously, such as diamond like carbon, silicon carbide and carbon nanotubes, micro-turbines and micro-engines. 3. Development of technologies for the system level and wafer level integration of micro components at the nanometer precision, such as self-assembly techniques and robotic manipulation. 4. Development of control and communication systems for MEMS devices, such as optical and RF wireless, and power delivery systems.

MEMS-Enabled Smart Beam-Steering Antennas

2014 ◽  
pp. 183-203
Author(s):  
Hadi Mirzajani ◽  
Habib Badri Ghavifekr ◽  
Esmaeil Najafi Aghdam
Keyword(s):  
Microelectromechanical Systems ◽  
Rf Mems ◽  
Beam Steering ◽  
Smart Antennas ◽  
Phase Shifters ◽  
Rapid Rate ◽  
Mems Devices ◽  
Batch Fabrication ◽  
Mems Technology ◽  
Smart Beam

In recent years, Microelectromechanical Systems (MEMS) technology has seen a rapid rate of evolution because of its great potential for advancing new products in a broad range of applications. The RF and microwave devices and components fabricated by this technology offer unsurpassed performance such as near-zero power consumption, high linearity, and cost effectiveness by batch fabrication in respect to their conventional counterparts. This chapter aims to give an in-depth overview of the most recently published methods of designing MEMS-based smart antennas. Before embarking into the different techniques of beam steering, the concept of smart antennas is introduced. Then, some fundamental concepts of MEMS technology such as micromachining technologies (bulk and surface micromachining) are briefly discussed. After that, a number of RF MEMS devices such as switches and phase shifters that have applications in beam steering antennas are introduced and their operating principals are completely explained. Finally, various configurations of MEMS-enabled beam steering antennas are discussed in detail.

Mobile Agent-Based Collaborative Computing Framework for Handling Constraint Resources

2012 ◽  
pp. 113-134
Author(s):  
Anil Kakarla ◽  
Sanjeev Agarwal ◽  
Sanjay Kumar Madria
Keyword(s):  
Information Processing ◽  
Distributed Computing ◽  
Mobile Agent ◽  
Computational Cost ◽  
Computation Time ◽  
Distributed Network ◽  
Collaborative Computing ◽  
Agent Based ◽  
Computing Framework ◽  
Viable System

Information processing and collaborative computing using agents over a distributed network of heterogeneous platforms are important for many defense and civil applications. In this chapter, a mobile agent based collaborative and distributed computing framework for network centric information processing is presented using a military application. In this environment, the challenge is to continue processing efficiently while satisfying multiple constraints like computational cost, communication bandwidth, and energy in a distributed network. The authors use mobile agent technology for distributed computing to speed up data processing using the available systems resources in the network. The proposed framework provides a mechanism to bridge the gap between computation resources and dispersed data sources under variable bandwidth constraints. For every computation task raised in the network, a viable system that has resources and data to compute the task is identified and sent to the viable system for completion. Experimental evaluation under the real platform is reported. It shows that in spite of an increase of the communication load in comparison with other solutions the proposed framework leads to a decrease of the computation time.

A Renewal Weakest-Link Model of Strength Distribution of Polycrystalline Silicon MEMS Structures

2019 ◽  
Vol 86 (8) ◽  
Author(s):  
Zhifeng Xu ◽  
Roberto Ballarini ◽  
Jia-Liang Le
Keyword(s):  
Experimental Data ◽  
Polycrystalline Silicon ◽  
Microelectromechanical Systems ◽  
Strength Distribution ◽  
Material Strength ◽  
Mems Devices ◽  
Efficient Computation ◽  
Weakest Link ◽  
Large Size ◽  
The Stability

Experimental data have made it abundantly clear that the strength of polycrystalline silicon (poly-Si) microelectromechanical systems (MEMS) structures exhibits significant variability, which arises from the random distribution of the size and shape of sidewall defects created by the manufacturing process. Test data also indicated that the strength statistics of MEMS structures depends strongly on the structure size. Understanding the size effect on the strength distribution is of paramount importance if experimental data obtained using specimens of one size are to be used with confidence to predict the strength statistics of MEMS devices of other sizes. In this paper, we present a renewal weakest-link statistical model for the failure strength of poly-Si MEMS structures. The model takes into account the detailed statistical information of randomly distributed sidewall defects, including their geometry and spacing, in addition to the local random material strength. The large-size asymptotic behavior of the model is derived based on the stability postulate. Through the comparison with the measured strength distributions of MEMS specimens of different sizes, we show that the model is capable of capturing the size dependence of strength distribution. Based on the properties of simulated random stress field and random number of sidewall defects, a simplified method is developed for efficient computation of strength distribution of MEMS structures.

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