Adversarial Autoencoder for Denoising and Signal Recovery in Quantum Gyroscopes

Quantum gyroscopes (QG) are a critical component of navigation systems in space applications. However, these devices are prone to noise and environmental factors that can degrade the quality of the data and compromise the accuracy of the measurements. This research proposes an effective Adversarial Autoencoders (AAEs) framework for denoising and signal recovery in QGs to improve the accuracy and reliability of navigation systems in space. By denoising signals, AAEs can improve the accuracy of measurements and can help reduce the risk of communication failures and increase the efficiency of cognitive communication systems. Overall, our method offers a promising solution for denoising and signal recovery in noisy QG schemes, demonstrating that it can accurately recover signals with low reconstruction error. This approach has the potential to improve the reliability and accuracy of QGs, leading to safer and more efficient communication systems.