Function Extension Based Real-Time Wavelet De-Noising Method for Projectile Attitude Measurement.

Area of Science:

• Aerospace Engineering
• Signal Processing
• Guidance Systems

Background:

• Real-time projectile attitude measurement is crucial for guidance systems.
• Gyro signal de-noising accuracy and real-time performance are critical due to high dynamic projectile motion.
• Conventional extension methods for wavelet de-noising suffer from nonlinear discontinuity.

Purpose of the Study:

• To propose a novel function extension real-time wavelet de-noising method for gyro signals.
• To address the limitations of traditional extension methods in real-time de-noising applications.
• To enhance the accuracy and real-time performance of projectile attitude measurement.

Main Methods:

• Established a gyro signal prediction model based on the Roggla formula.
• Implemented a sliding window fitting approach for signal prediction.
• Utilized the predicted signal to achieve right boundary extension for wavelet de-noising.

Main Results:

• The proposed method significantly increased the signal-to-noise ratio (SNR) and signal smoothness.
• Attitude Mean Absolute Error (AMAE) and Attitude Root Mean Square Error (ARMSE) were effectively reduced.
• The time delay associated with signal de-noising was minimized, ensuring real-time performance.

Conclusions:

• The function extension real-time wavelet de-noising method offers superior performance compared to traditional techniques.
• This approach enhances the accuracy and reliability of projectile attitude measurement.
• The method effectively overcomes the challenges of real-time de-noising in dynamic environments.