Explore MATLAB source code curated for "目标定位" with clean implementations, documentation, and examples.
An adaptive Kalman filter algorithm for target localization through multi-sensor information fusion, featuring automated covariance matrix adjustments based on sensor data inputs
Using MATLAB to compute the Geometric Dilution of Precision (GDOP) values for target localization in radar networks, with implementation of error covariance matrix analysis and positioning accuracy evaluation algorithms.
Application of particle filter in target localization and tracking, suitable for nonlinear filtering algorithm research with implementation insights using sequential Monte Carlo methods.
Single-sensor target localization and tracking, featuring Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) algorithms based on Constant Acceleration (CA) and Interacting Multiple Model (IMM) frameworks, with code implementation insights.
Orthogonal correlation object detection employs orthogonal correlation methods to identify target positions in images. Suitable for various computer vision applications including video object detection, visual object detection, object localization, visual object tracking, video object tracking, image matching, and image registration. Implementation typically involves calculating correlation matrices between target templates and image regions using orthogonal basis functions.
A MATLAB program for target localization employing the classical centroid localization technique. Highly valuable for understanding algorithm implementation, with all parameters pre-configured for immediate execution upon download. Includes detailed code structure descriptions.
A passive radar localization system employing direction finding methodology for target positioning, with comprehensive analysis of localization accuracy through algorithmic implementation.
This resource presents several fundamental target localization algorithms including Centroid Algorithm, RSSI Algorithm, TOA Algorithm, and AOA Algorithm. All programs have been thoroughly debugged and validated through successful simulation results with detailed implementation code.
MATLAB-based multi-faceted image processing workflow: starting with histogram equalization for contrast enhancement, followed by integral projection analysis (including horizontal and vertical projections), and concluding with precise target localization algorithms.
Implementing D-S evidence theory for data fusion in wireless sensor network target localization and decision-level fusion, featuring probability mass functions and combination rules