arXiv subjects

Lei Jing

Publications and source records attributed to Lei Jing.

18 recordsLinked to original sources

arXiv2026

Quaternion-Averaging-Based Adaptive Complementary Filter for Pedestrian Dead Reckoning With a Foot-Mounted AHRS

Pedestrian Dead Reckoning (PDR) can be applied to indoor navigation systems. GPS suffers from signal degradation due to roofs and high-rise buildings, whereas PDR can estimate positions without being affected by such signal degradation. The accuracy of a foot-mounted AHRS(Attitude and Heading Reference System)-based PDR depends on the accuracy of the attitude estimation algorithm used in the AHRS. In this article, a Quaternion-Averaging-Based Adaptive Complementary Filter (QAACF) for PDR with a foot-mounted AHRS is proposed to improve estimation accuracy while reducing computational cost. QAACF fuses a quaternion derived from angular velocity with quaternions derived from acceleration and magnetic field measurements using Markley's quaternion averaging, which combines two quaternions more rigorously than linear interpolation. In addition, QAACF adaptively adjusts the weights of angular velocity, acceleration, and magnetic field measurements according to gait phases and the level of magnetic disturbances. Experimental results showed that the proposed QAACF achieves low Root Mean Square Errors (RMSEs) compared to existing attitude estimation filters while requiring lower computational cost than Kalman filters.

cs.RO↗

arXiv2026

Multimodal User Authentication Method via Fusion of Keystroke Dynamics and Glove-Based Hand Kinematics

Although keystroke dynamics are cost-effective behavioral biometrics, their practical deployment is hindered by susceptibility to environmental variations. To address this, we propose a robust multimodal authentication framework that augments traditional keystroke dynamics using 19-dimensional hand kinematics. Features are captured using a bespoke data glove equipped with 10 piezoresistive pressure sensors and a 9-axis IMU. A hybrid CNN-LSTM architecture effectively fuses these heterogeneous time-series streams. To ensure real-world applicability, we implemented a rigorous "unseen" evaluation protocol: the model was trained on a desktop keyboard using data from 1 target user and 8 "known" impostors, but evaluated on a laptop keyboard (cross-domain) against the target and an "unknown" impostor excluded from training. Averaged over five trials, the multimodal method achieved a mean Equal Error Rate (EER) of 2.12% for individual 600-ms authentication events (Window 1). Crucially, aggregating scores over 10 events (6 seconds) using a temporal smoothing window yielded perfect authentication (0.00% EER). While our ablation study showed IMU kinematics alone achieved equivalent performance in a static laboratory, error analysis confirmed that pressure and IMU sensors, despite strong physical correlation, possess distinct sensitivities to error factors. Fusing these modalities establishes a vital fail-safe against real-world vulnerabilities like spatial spoofing and environmental noise, highlighting that combined physical traits provide much stronger biometric discrimination than timing features alone.

cs.CR↗

arXiv2026

A Lightweight Cubature Kalman Filter for Attitude and Heading Reference Systems Using Simplified Prediction Equations

Attitude and Heading Reference Systems (AHRSs) are broadly applied wherever reliable orientation and motion sensing is required. In this paper, we present an improved Cubature Kalman Filter (CKF) with lower computational cost while maintaining estimation accuracy, which is named "Kaisoku Cubature Kalman Filter (KCKF)". The computationally efficient equations of the KCKF are derived by simplifying those of the CKF, while preserving equivalent mathematical relations. The lightweight prediction equations in the KCKF are derived by expanding the summation terms in the CKF and simplifying the result. This paper shows that the KCKF requires fewer floating-point operations (FLOPs) than the CKF. The controlled experimental results show that the KCKF reduces the computation time by approximately 19% compared to the CKF on a high-performance computer, whereas the KCKF reduces the computation time by approximately 15% compared to the CKF on a low-cost single-board computer. In addition, the KCKF maintains the attitude estimation accuracy of the CKF.

eess.SY↗

arXiv2025

WPTrack: A Wi-Fi and Pressure Insole Fusion System for Single Target Tracking

As the Internet of Things (IoT) continues to evolve, indoor location has become a critical element for enabling smart homes, behavioral monitoring, and elderly care. Existing WiFi-based human tracking solutions typically require specialized equipment or multiple Wi-Fi links, a limitation in most indoor settings where only a single pair of Wi-Fi devices is usually available. However, despite efforts to implement human tracking using one Wi-Fi link, significant challenges remain, such as difficulties in acquiring initial positions and blind spots in DFS estimation of tangent direction. To address these challenges, this paper proposes WPTrack, the first Wi-Fi and Pressure Insoles Fusion System for Single Target Tracking. WPTrack collects Channel State Information (CSI) from a single Wi-Fi link and pressure data from 90 insole sensors. The phase difference and Doppler velocity are computed from the CSI, while the pressure sensor data is used to calculate walking velocity. Then, we propose the CSI-pressure fusion model, integrating CSI and pressure data to accurately determine initial positions and facilitate precise human tracking. The simulation results show that the initial position localization accuracy ranges from 0.02 cm to 42.55 cm. The trajectory tracking results obtained from experimental data collected in a real-world environment closely align with the actual trajectory.

cs.NI↗

arXiv2025

P2P-Insole: Human Pose Estimation Using Foot Pressure Distribution and Motion Sensors

This work presents P2P-Insole, a low-cost approach for estimating and visualizing 3D human skeletal data using insole-type sensors integrated with IMUs. Each insole, fabricated with e-textile garment techniques, costs under USD 1, making it significantly cheaper than commercial alternatives and ideal for large-scale production. Our approach uses foot pressure distribution, acceleration, and rotation data to overcome limitations, providing a lightweight, minimally intrusive, and privacy-aware solution. The system employs a Transformer model for efficient temporal feature extraction, enriched by first and second derivatives in the input stream. Including multimodal information, such as accelerometers and rotational measurements, improves the accuracy of complex motion pattern recognition. These facts are demonstrated experimentally, while error metrics show the robustness of the approach in various posture estimation tasks. This work could be the foundation for a low-cost, practical application in rehabilitation, injury prevention, and health monitoring while enabling further development through sensor optimization and expanded datasets.

cs.CV↗

arXiv2025

A Time-Series Data Augmentation Model through Diffusion and Transformer Integration

With the development of Artificial Intelligence, numerous real-world tasks have been accomplished using technology integrated with deep learning. To achieve optimal performance, deep neural networks typically require large volumes of data for training. Although advances in data augmentation have facilitated the acquisition of vast datasets, most of this data is concentrated in domains like images and speech. However, there has been relatively less focus on augmenting time-series data. To address this gap and generate a substantial amount of time-series data, we propose a simple and effective method that combines the Diffusion and Transformer models. By utilizing an adjusted diffusion denoising model to generate a large volume of initial time-step action data, followed by employing a Transformer model to predict subsequent actions, and incorporating a weighted loss function to achieve convergence, the method demonstrates its effectiveness. Using the performance improvement of the model after applying augmented data as a benchmark, and comparing the results with those obtained without data augmentation or using traditional data augmentation methods, this approach shows its capability to produce high-quality augmented data.

cs.LG↗

arXiv2023

Enhanced measurement precision with continuous interrogation during dynamical decoupling

Dynamical decoupling (DD) is normally ineffective when applied to DC measurement. In its straightforward implementation, DD nulls out DC signal as well while suppressing noise. This work proposes a phase relay method (PRM) that is capable of continuously interrogating the DC signal over many DD cycles. We illustrate its efficacy when applied to measurement of a weak DC magnetic field with an atomic spinor Bose-Einstein condensate. Sensitivities approaching standard quantum limit (SQL) or Heisenberg limit (HL) are potentially realizable for a coherent spin state (CSS) or a squeezed spin state (SSS) of 10,000 atoms respectively, while ambient laboratory level noise is suppressed by DD. Our work offers a practical approach to mitigate the limitations of DD to DC measurement and will like find other applications for resorting coherence in quantum sensing and quantum information processing research.

quant-ph↗

arXiv2023

Noise-resistant quantum memory enabled by Hamiltonian engineering

Nuclear spins in quantum dots are promising candidates for fast and scalable quantum memory. By utilizing the hyperfine interaction between the central electron and its surrounding nuclei, quantum information can be transferred to the collective state of the nuclei and be stored for a long time. However, nuclear spin fluctuations in a partially polarized nuclear bath deteriorate the quantum memory fidelity. Here we introduce a noise-resistant protocol to realize fast and high-fidelity quantum memory through Hamiltonian engineering. With analytics and numerics, we show that high-fidelity quantum state transfer between the electron and the nuclear spins is achievable at relatively low nuclear polarizations, due to the strong suppression of nuclear spin noises. For a realistic quantum dot with $10^4$ nuclear spins, a fidelity surpassing 80% is possible at a polarization as low as 30%. Our approach reduces the demand for high nuclear polarization, making experimentally realizing quantum memory in quantum dots more feasible.

cond-mat.mes-hall↗

arXiv2022

Optical-plug-assisted spin vortex in a $^{87}$Rb dipolar spinor Bose-Einstein condensate

Generating a spin vortex in a $^{87}$Rb dipolar spinor Bose-Einstein condensate in a controllable way is still experimentally challenging. We propose an experimentally easy and tunable way to produce spin vortex by varying the potential barrier height and the width of an additionally applied optical plug. A topological phase transition occurs from the trivial single mode approximation phase to the optical-plug-assisted-vortex one, as the barrier height increases and the width lies in an appropriate range. The optical plug causes radial density variation thus the spin vortex is favored by significantly lowering the intrinsic magnetic dipolar energy. A type of coreless spin vortex, different from the conventional polar core vortex, is predicted by our numerical results. Our proposal removes a major obstacle to investigate the topological phase transition in a $^{87}$Rb dipolar spinor BEC.

cond-mat.quant-gas↗

arXiv2014

Transport Measurement of Landau level Gaps in Bilayer Graphene

Landau level gaps are important parameters for understanding electronic interactions and symmetry-broken processes in bilayer graphene (BLG). Here we present transport spectroscopy measurements of LL gaps in double-gated suspended BLG with high mobilities in the quantum Hall regime. By using bias as a spectroscopic tool, we measure the gap Δ for the quantum Hall (QH) state at filling factor ν={\pm}4 and -2. The single-particle gap for ν=4 scales linearly with magnetic field B and is independent of the out-of-plane electric field E. For the symmetry-broken ν=-2 state, the measured values of gap are 1.1 meV/T and 0.17 meV/T for singly-gated geometry and dual-gated geometry at E=0, respectively. The difference between the two values arises from the E-dependence of the gap, suggesting that the ν=-2 state is layer polarized. Our studies provide the first measurements of the gaps of the broken symmetry QH states in BLG with well-controlled E, and establish a robust method that can be implemented for studying similar states in other layered materials.

cond-mat.mes-hall↗

arXiv2012

Broken Symmetry Quantum Hall States in Dual Gated ABA Trilayer Graphene

We present low temperature transport measurements on dual-gated suspended trilayer graphene in the quantum Hall (QH) regime. We observe QH plateaus at filling factors ν=-8, -2, 2, 6, and 10, in agreement with the full-parameter tight binding calculations. In high magnetic fields, odd-integer plateaus are also resolved, indicating almost complete lifting of the 12-fold degeneracy of the lowest Landau levels (LL). Under an out-of-plane electric field E, we observe degeneracy breaking and transitions between QH plateaus. Interestingly, depending on its direction, E selectively breaks the LL degeneracies in the electron-doped or hole-doped regimes. Our results underscore the rich interaction-induced phenomena in trilayer graphene.

cond-mat.mes-hall↗

arXiv2012

Visualizing Electrical Breakdown and ON/OFF States in Electrically Switchable Suspended Graphene Break Junctions

Narrow gaps are formed in suspended single to few layer graphene devices using a pulsed electrical breakdown technique. The conductance of the resulting devices can be programmed by the application of voltage pulses, with a voltage of 2.5V~4.5V corresponding to an ON pulse and voltages ~8V corresponding to OFF pulses. Electron microscope imaging of the devices shows that the graphene sheets typically remain suspended and that the device conductance tends to zero when the observed gap is large. The switching rate is strongly temperature dependent, which rules out a purely electromechanical switching mechanism. This observed switching in suspended graphene devices strongly suggests a switching mechanism via atomic movement and/or chemical rearrangement, and underscores the potential of all-carbon devices for integration with graphene electronics.

cond-mat.mes-hall↗

arXiv2012

Minimum Conductivity and Evidence for Phase Transitions in Ultra-clean Bilayer Graphene

Bilayer graphene (BLG) at the charge neutrality point (CNP) is strongly susceptible to electronic interactions, and expected to undergo a phase transition into a state with spontaneous broken symmetries. By systematically investigating a large number of singly- and doubly-gated bilayer graphene (BLG) devices, we show that an insulating state appears only in devices with high mobility and low extrinsic doping. This insulating state has an associated transition temperature Tc~5K and an energy gap of ~3 meV, thus strongly suggesting a gapped broken symmetry state that is destroyed by very weak disorder. The transition to the intrinsic broken symmetry state can be tuned by disorder, out-of-plane electric field, or carrier density.

cond-mat.mes-hall↗

arXiv2010

Magnetoconductance Oscillations in High-Mobility Suspended Bilayer and Trilayer Graphene

We report pronounced magnetoconductance oscillations observed on suspended bilayer and trilayer graphene devices with mobilities up to 270,000 cm2/Vs. For bilayer devices, we observe conductance minima at all integer filling factors nu between 0 and -8, as well as a small plateau at ν=1/3. For trilayer devices, we observe features at nu=-1, -2, -3 and -4, and at ν~0.5 that persist to 4.5K at B=8T. All of these features persist for all accessible values of Vg and B, and could suggest the onset of symmetry breaking of the first few Landau (LL) levels and fractional quantum Hall states.

cond-mat.mes-hall↗

arXiv2010

Suspension and Measurement of Graphene and Bi2Se3 Atomic Membranes

Coupling high quality, suspended atomic membranes to specialized electrodes enables investigation of many novel phenomena, such as spin or Cooper pair transport in these two dimensional systems. However, many electrode materials are not stable in acids that are used to dissolve underlying substrates. Here we present a versatile and powerful multi-level lithographical technique to suspend atomic membranes, which can be applied to the vast majority of substrate, membrane and electrode materials. Using this technique, we fabricated suspended graphene devices with Al electrodes and mobility of 5500 cm^2/Vs. We also demonstrate, for the first time, fabrication and measurement of a free-standing thin Bi2Se3 membrane, which has low contact resistance to electrodes and a mobility of >~500 cm^2/Vs.

cond-mat.mes-hall↗

arXiv2010

Quantum Transport and Field Induced Insulating States in Bilayer Graphene pnp Junctions

We perform transport measurements in high quality bilayer graphene pnp junctions with suspended top gates. At a magnetic field B=0, we demonstrate band gap opening by an applied perpendicular electric field, with an On/Off ratio up to 20,000 at 260mK. Within the band gap, the conductance decreases exponentially by 3 orders of magnitude with increasing electric field, and can be accounted for by variable range hopping with a gate-tunable density of states, effective mass, and localization length. At large B, we observe quantum Hall conductance with fractional values, which arise from equilibration of edge states between differentially-doped regions, and the presence of an insulating state at filling factor ν=0. Our work underscores the importance of bilayer graphene for both fundamental interest and technological applications.

cond-mat.mes-hall↗

arXiv2009

Probing Charging and Localization in the Quantum Hall Regime by Graphene pnp Junctions

Using high quality graphene pnp junctions, we observe prominent conductance fluctuations on transitions between quantum Hall (QH) plateaus as the top gate voltage Vtg is varied. In the Vtg-B plane, the fluctuations form crisscrossing lines that are parallel to those of the adjacent plateaus, with different temperature dependences for the conductance peaks and valleys. These fluctuations arise from Coulomb-induced charging of electron- or hole-doped localized states when the device bulk is delocalized, underscoring the importance of electronic interactions in graphene in the QH regime.

cond-mat.mes-hall↗

arXiv2007

Average Density of States in Disordered Graphene systems

In this paper, the average density of states (ADOS) with a binary alloy disorder in disordered graphene systems are calculated based on the recursion method. We observe an obvious resonant peak caused by interactions with surrounding impurities and an anti-resonance dip in ADOS curves near the Dirac point. We also find that the resonance energy (Er) and the dip position are sensitive to the concentration of disorders (x) and their on-site potentials (v). An linear relation, not only holds when the impurity concentration is low but this relation can be further extended to high impurity concentration regime with certain constraints. We also calculate the ADOS with a finite density of vacancies and compare our results with the previous theoretical results.

cond-mat.mes-hall↗