Improved Student’s t-Based Unscented Filter and its Application to Trajectory Estimation for Maneuvering Target
Source abstract
Abstract
To estimate the systems with one-step randomly delayed measurement and time-correlated heavy-tailed measurement noises, on the basis of robust Student’s t based unscented filter (RSTUF), an improved Student’s t based unscented filter (ISTUF) is proposed. Referring to the measurement differencing method, a reformed measurement model was built. Then, by augmenting the system state vector, the conditional probability distribution of the measurement noise with respect to delayed measurement was taken into consideration. Based on the reformed measurement model and the augment state vector, a novel estimator was designed to solve the one-step randomly delayed problem. Maneuvering target tracking systems were used for simulation. Compared with unscented Kalman filter (UKF) or RSTUF, ISTUF had higher accuracy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Target Tracking and Data Fusion in Sensor Networks · Inertial Sensor and Navigation · Advanced Measurement and Detection Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Control and Simulation Centre, Harbin Institute of Technology, Harbin 150001, China
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