Digital Control Circuit of Accelerometer in Gravity Gradiometer Based on Particle Swarm Optimization Algorithm

This study presents a Digital Control Circuit for Accelerometer Noise Reduction in Gravity Gradiometers Using Enhanced Particle Swarm Optimization algorithm. In the realm of geophysics and space exploration, gravity gradiometers are crucial for precise measurements, yet accelerometer noise and interference have long hindered performance enhancement. Our enhanced PSO algorithm, inspired by the natural foraging behaviors of avian species, mimics how birds utilize collective and individual experiences to search for food, translating this concept into the algorithm's particle movement and parameter update rules for exploring the solution space to effectively reduce high-frequency noise by 30% and improve the signal-to-noise ratio by 25% compared to traditional methods. The designed digital control circuit, with the PSO algorithm integrated into its hardware framework based on a digital signal processor, enables real-time signal processing. Simulation results confirm the circuit's proficiency in noise reduction and enhancement of the collected data's signal-to-noise ratio, thereby validating our approach's effectiveness in improving accelerometer performance within gravity gradiometer systems