The Magnetic Positioning System Based on Genetic Algorithm-optimized BP Natural Network

This article details a magnetic positioning system using a genetic algorithm-optimized BPNN. The hardware includes a control module with an Arduino Mega 2560, a data collection module using Honeywell HMC5883L magnetometers for XYZ magnetic data, and a communication module integrating I2C via TCA9548A for sensor connections. The BPNN and genetic algorithm principles are combined in MATLAB to optimize weights and biases. Results show the system converges faster, predicts coordinates closer to actual values, and improves accuracy and robustness across environments, enhancing overall system performance and stability.