Cubature Kalman Filter

Research Update: Hohai University Team Achieves Latest Progress in Multi-Sensor Fusion for Autonomous Localization and 3D Mapping

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Research Update: Hohai University Team Achieves Latest Progress in Multi-Sensor Fusion for Autonomous Localization and 3D Mapping

Recently, Professor He Xiufeng’s research group from the School of Earth Sciences and Engineering at Hohai University, along with collaborators, published a research paper titled “DALI-SLAM: Degeneracy-Aware LiDAR-inertial SLAM with novel distortion correction and accurate multi-constraint pose graph optimization” in the ISPRS Journal of Photogrammetry and Remote Sensing. LiDAR-Inertial Simultaneous Localization and Mapping (LI-SLAM) plays … Read more

Estimation of SOC for Lithium-Ion Batteries and Circuit Implementation

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Estimation of SOC for Lithium-Ion Batteries and Circuit Implementation

Definition of SOC for Lithium-Ion Batteries SOC, as a key technical indicator managed by the Battery Management System (BMS), is obtained through estimation methods and parameter correspondence. The main function of SOC in the power batteries of new energy vehicles is to provide an intuitive display of the remaining energy in the vehicle, similar to … Read more

Common Algorithms in Embedded Development: Least Squares Estimation

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Common Algorithms in Embedded Development: Least Squares Estimation

Linear regression is the foundation of the classic least squares method, Kalman filter, and Wiener filter. It was the first algorithm I encountered during my graduate studies, and I first used it while working on a project for my advisor. After entering the workforce, I found that these algorithms are ubiquitous in engineering. Unfortunately, many … Read more

Federated Kalman Filtering for Radar and Sensor Trajectory Estimation

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Federated Kalman Filtering for Radar and Sensor Trajectory Estimation

💥💥💞💞Welcome to this blog❤️❤️💥💥 🏆Author’s Advantage: 🌞🌞🌞The blog content aims to be logically coherent and clear for the convenience of readers. ⛳️Motto: A journey of a hundred miles begins with a single step. ⛳️Gift to Readers 👨💻Conducting research involves a profound system of thought, requiring researchers to be logical and diligent, but effort alone is … Read more

MATLAB Routine for Integrated Navigation: CKF Filtering on a 2D Plane, Fusing IMU and GNSS Data, Simulation with Observations on X and Y Axes

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MATLAB Routine for Integrated Navigation: CKF Filtering on a 2D Plane, Fusing IMU and GNSS Data, Simulation with Observations on X and Y Axes

Using an 8-dimensional state model, it comprehensively describes position, velocity, attitude, and sensor biases in planar motion. The Cubature Kalman Filter is employed to handle nonlinear problems, offering better numerical stability and accuracy compared to traditional EKF, effectively fusing IMU and GNSS data to fully leverage the complementary advantages of both sensors. Table of Contents … Read more

Overview of SOC Estimation Methods

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Overview of SOC Estimation Methods

Welcome to the Battery Perspective! Previously, we introduced various electrode materials, battery manufacturing processes, and battery analysis content, mainly focusing on material manufacturers and cell manufacturers, with little introduction to battery applications. This section mainly discusses issues such as SOC and SOH in battery applications. The state of charge (SOC) of lithium-ion batteries is very … Read more

3D State Combination Navigation Based on CKF: Integrating GNSS and IMU with Observations of Three-Axis Position and Velocity, 15-Dimensional State Variables, Code Download Link

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3D State Combination Navigation Based on CKF: Integrating GNSS and IMU with Observations of Three-Axis Position and Velocity, 15-Dimensional State Variables, Code Download Link

The simulation of 3D state combination navigation uses the Cubature Kalman Filter (CKF) for nonlinear filtering. The state model consists of 15-dimensional error states, and the observation model includes 6-dimensional GNSS observations (position + velocity). Article Directory Program Introduction Running Results MATLAB Source Code Program Introduction This program implements a 3D state combination navigation simulation, … Read more

UKF-Based Combined Navigation with 8-Dimensional State and XY Coordinate Observations in MATLAB

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UKF-Based Combined Navigation with 8-Dimensional State and XY Coordinate Observations in MATLAB

The code implements a two-dimensional combined navigation system based on the Unscented Kalman Filter (UKF), integrating data from the Inertial Measurement Unit (IMU) and the Global Navigation Satellite System (GNSS). This system employs an 8-dimensional error state model to estimate the carrier’s position, velocity, attitude, and sensor biases in real-time. Program Overview System Overview IMU … Read more

MATLAB Example: CKF (Cubature Kalman Filter) Filtering Routine for Two-Dimensional Nonlinear Systems with Nonlinear States and Observations, Code Download Link Included

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MATLAB Example: CKF (Cubature Kalman Filter) Filtering Routine for Two-Dimensional Nonlinear Systems with Nonlinear States and Observations, Code Download Link Included

The state equation and observation equation are both two-dimensional and nonlinear. There are Chinese comments, and you can modify the code as needed.<span>After subscribing to the column, you can directly view the source code, paste it into a MATLAB empty script, and run it to obtain results.</span> Article Directory Program Introduction Running Results MATLAB Source … Read more