Feature extraction algorithm of precession target based on image length and Doppler broadening

Area of Science:

• Space Defense Technology
• Radar and Lidar Imaging
• Target Recognition and Tracking

Background:

• Distinguishing real targets from decoys in space defense relies on micromotion features.
• Microwave radar's Inverse Synthetic Aperture Radar (ISAR) faces challenges imaging high-speed precession targets due to isolated scattering centers.
• Laser's short wavelength enables continuous Inverse Synthetic Aperture Ladar (ISAL) imaging, capturing crucial precession-induced variations.

Purpose of the Study:

• To develop a practical algorithm for inverse motion parameter estimation of precessing space targets.
• To leverage ISAL image sequences for extracting target precession characteristics.
• To improve the accuracy and applicability of target identification in space defense scenarios.

Main Methods:

• Established an observation model for precessing targets.
• Processed ISAL image sequences over time to obtain image length and Doppler width variations.
• Applied ellipse fitting to these sequences for calculating precession parameters.

Main Results:

• Successfully extracted image length and Doppler width sequences from ISAL data.
• The ellipse fitting method accurately determined target precession parameters.
• Experimental validation confirmed the algorithm's effectiveness with errors within 2%.

Conclusions:

• The proposed ISAL-based method effectively estimates space target precession parameters.
• The algorithm's independence from prior motion information enhances its practical utility.
• This technique offers a robust solution for target discrimination in space defense.