High accuracy and reliable navigation in the underwater environment is very critical for the operations of autonomous underwater vehicles (AUVs). This paper proposes an adaptive federated interacting multiple model (IMM) filter, which combines adapti...
The data privacy leakage problem of federated learning has attracted widespread attention. Using differential privacy can protect the data privacy of each node in the federated learning, but adding noise to the model parameters will reduce the accura...
The inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation. In order to improve the computational efficiency and the localization performance...
Among the methods of the multi-source navigation filter, as a distributed method, the federated filter has a small calculation amount with Gaussian state noise, and it is easy to achieve global optimization. However, when the state noise is time-vary...
Aiming at the problem of the low cooperative positioning accuracy and robustness of multi-UAV formation, a cooperative positioning method of a multi-UAV based on an adaptive fault-tolerant federated filter is proposed. Combined with the position of t...
To achieve autonomous and reliable all-weather cross-domain aerospace navigation, this study proposes an adaptive fault-tolerant federated Kalman filter (AFTFKF) for an INS/SRNS/CNS integrated navigation system to enhance system robustness against me...
This paper offers a solution to challenge navigation in the indoor environment by making use of the existing infrastructure. Estimating pedestrian trajectory using pedestrian dead reckoning (PDR) and WiFi is a very popular technique. However, cumulat...
Efficient fusion of navigation sensor data with different output frequencies and data types is critical for ensuring that vehicle-mounted integrated navigation systems consistently provide stable, reliable navigation solutions in complex dynamic oper...
To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS...
The detection of track geometry parameters is essential for the safety of high-speed railway operation. To improve the accuracy and efficiency of the state detector of track geometry parameters, in this study we propose an inertial GNSS odometer inte...
This article examines the positioning effect of integrated navigation after adding an LEO constellation signal source and a 5G ranging signal source in the context of China’s new infrastructure construction. The tightly coupled Kalman federal f...
To address the issue of low positioning accuracy in unmanned vehicles navigating in obstructed spaces due to easily contaminated navigation measurement information, an improved adaptive federated Kalman filtering INS/GNSS/VNS integrated navigation al...
Unmanned aerial vehicle (UAV) navigation systems face significant challenges in complex environments, such as sensor degradation and signal loss. This study proposes the NSDDI-AFF (Normalized Single-Dimensional Degradation Isolation with Adaptive Fed...
Precise orbit determination for multi-spacecraft deep space missions faces challenges including long communication delays, sparse tracking, dynamic model uncertainties, and inefficient data fusion. Presenting a hybrid estimation architecture, this st...
The integration of an inertial navigation system (INS) with the Global Navigation Satellite System (GNSS) is crucial for suppressing the error drift of the INS. However, traditional fusion methods based on the extended Kalman filter (EKF) suffer from...
The quadruped robots have superior adaptability to complex terrains, compared with tracked and wheeled robots. Therefore, leader-following can help quadruped robots accomplish long-distance transportation tasks. However, long-term following has to fa...
Relative to single Global Navigation Satellite System (GNSS) measurements, i.e., the measurements from a single GNSS system, a single GNSS code, and a single GNSS receiver, multi-GNSS measurements for time transfer could improve reliability and provi...
Vehicle running state parameters and road surface state are crucial to the stability of four-wheel independent drive and steering electric vehicle control. Therefore, this study explores the estimation of vehicle driving state parameters and road sur...
To enhance the precision and reliability of integrated navigation systems, a novel fault-tolerant information fusion algorithm based on a federated filter is proposed. Decentralized filtering architecture is employed to fuse information from differen...
As an emerging artificial intelligence technology, federated learning plays a significant role in privacy preservation in machine learning, although its main objective is to prevent peers from peeping data. However, attackers from the outside can ste...
Cross-domain collaborative filtering effectively alleviates the data sparsity issue but raises serious privacy concerns. Federated learning has been integrated into cross-domain collaborative filtering to reduce these risks by securely exchanging emb...
Autonomous unmanned aerial vehicles (UAVs) require highly reliable navigation information. Generally, navigation systems with the inertial navigation system (INS) and global navigation satellite system (GNSS) have been widely used. However, the GNSS...
The accelerating progress of the Internet of Vehicles (IoV) has put forward a higher demand for distributed model training and data sharing in vehicular networks. Traditional centralized approaches are no longer applicable in the face of drivers&rsqu...
A single low cost inertial measurement unit (IMU) is often used in conjunction with GPS to increase the accuracy and improve the availability of the navigation solution for a pedestrian navigation system. This paper develops several fusion algorithms...
China is promoting the construction of an integrated positioning, navigation, and timing (PNT) systems with the BeiDou Navigation Satellite System (BDS) as its core. To expand the positioning coverage area and improve the positioning performance by t...
Targeting the range defined by the FCC (Federal Communication Commission) in 2002 for ultra-passband bandpass filters, i.e., 3.1 to 10.6 GHz, this article presents a simple compact multipoles ultra-wideband bandpass filter (range starting from 2.9 GH...
To improve the reliability of strapdown inertial navigation system (SINS)/Doppler radar/odometer integrated navigation system, the federated Kalman filter with two-stage fault detection structure is designed, and a fault-tolerant SINS/Doppler radar/o...
The existing asynchronous federated learning methods have effectively addressed the issue of low training efficiency in synchronous methods. However, due to the centralized trust model constraints, they often need to pay more attention to the incenti...
Background: Chest X-ray imaging is a widely used diagnostic modality for identifying various lung diseases. Accurate multiclass classification of lung diseases enables timely treatment and improves patient survival. However, disease detection using c...
Cooperative localization provides a promising solution for multi-UAV navigation in GNSS-denied environments. However, centralized cooperative localization and exact cross-covariance-based distributed methods usually require global state management or...
To address the issues of decreased accuracy and poor stability in distributed transfer alignment caused by factors such as wing deflection and deformation in complex flight environments, this paper proposes a wing-distributed transfer alignment metho...
Federated learning has been popular for its ability to train centralized models while protecting clients’ data privacy. However, federated learning is highly susceptible to poisoning attacks, which can result in a decrease in model performance...
A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids...
Autonomous vehicles are expected to completely change the development model of the transportation industry and bring great convenience to our lives. Autonomous vehicles need to constantly obtain the motion status information with on-board sensors in...
To address the urgent demand for autonomous rapid initial alignment of vehicular inertial navigation systems in complex battlefield environments, this study overcomes the technical limitations of traditional stationary base alignment methods by propo...
Federated learning, as an emerging machine-learning method, has received widespread attention because it allows users to train locally during the training process and uses relevant cryptographic knowledge to safeguard the privacy of data during model...
Federated object detection over multi-site remote-sensing imagery faces two coupled risks that are not fully addressed by existing methods. Existing federated object-detection studies mainly focus on distributed training, communication efficiency, an...
Continuous monitoring of fine particulate matter (PM2.5) is important to provide near-real-time air quality information for public health protection, especially when ambient levels are elevated. The Tapered Element Oscillating Microbalance (TEOM), op...
Given the challenges in recommendation effectiveness, communication costs, and privacy issues associated with federated learning, the current algorithm amalgamates locality sensitive hash (LSH) with three federated recommendation models: Generalized...
Depression relapse is a common issue during long-term care. We introduce a privacy-aware explainable personalized federated learning (PFL) framework that incorporates layer-wise relevance propagation and Shapley value analysis to provide patient-spec...
In cases where a client suffers from completely unlabeled data, unsupervised learning has difficulty achieving an accurate fault diagnosis. Semi-supervised federated learning with the ability for interaction between a labeled client and an unlabeled...
Aimed at improving upon the disadvantages of the single centralized Kalman filter for integrated navigation, including its fragile robustness and low solution accuracy, a nonlinear double model based on the improved decentralized federated extended K...
As an important component of autonomous intelligent systems, the research on autonomous positioning algorithms used by UAVs is of great significance. In order to resolve the problem whereby the GNSS signal is interrupted, and the visual sensor lacks...
In response to the susceptibility of federated learning, which is based on a distributed training structure, to byzantine poisoning attacks from malicious clients, resulting in issues such as slowed or disrupted model convergence and reduced model ac...
This paper investigates the joint state and fault estimation problem for a class of nonlinear systems subject to both measurement censoring (MC) and random missing measurements (MMs). Recognizing that state estimation for nonlinear systems in complex...
Future UAV (unmanned aerial vehicle) operations in urban environments demand a PNT (position, navigation, and timing) solution that is both robust and resilient. While a GNSS (global navigation satellite system) can provide an accurate position under...
Aimed at improving the low measurement accuracy of the binocular vision sensor along the optical axis in the process of target tracking, we proposed a method for auxiliary correction using a laser-ranging sensor in this paper. In the process of syste...
Accurate and robust navigation is fundamental to Unmanned Aerial Vehicle (UAV) remote sensing operations. However, the susceptibility of UAV navigation sensors to diverse interference and malicious attacks can severely degrade positioning accuracy an...
This study introduces Meta-FedGeo, a federated learning framework that integrates meta-learning and spatiotemporal transformers to address key challenges in urban GeoAI for smart cities. Data streams in smart city environments are inherently non-stat...
A state of charge (SOC) estimation method is proposed. An Adaptive Extended Kalman Particle filter (AEKPF) based on Particle Filter (PF) and Adaptive Kalman Filter (AKF) is used in order to decrease the error and reduce calculations. The second-order...
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