Space-Based Focal Plane Ambiguous Measurement Ballistic Target MeMber Tracking

Area of Science:

• Aerospace Engineering
• Signal Processing
• Data Fusion

Background:

• Space-based passive detection and tracking of ballistic targets present unique challenges.
• Focal plane target tracking is crucial in distributed data processing for space surveillance.
• Pixel resolution is identified as a primary error source in focal plane measurements.

Purpose of the Study:

• To propose a novel multi-target multi-Bernoulli (MeMber) filtering algorithm for space-based passive detection.
• To develop an ambiguous measurement model addressing focal plane pixel resolution errors.
• To enhance the accuracy and applicability of target tracking algorithms in space.

Main Methods:

• Analysis of measurement error sources in space-based passive detection.
• Establishment of a focal plane ambiguous measurement model.
• Design of a generalized likelihood function.
• Modification of the MeMber filter incorporating the ambiguous measurement model and generalized likelihood function.

Main Results:

• Simulation experiments demonstrated superior performance of the MeMber filter using the ambiguous measurement model compared to the traditional model.
• The ambiguous measurement model more accurately reflects real-world conditions in space-based tracking.
• The modified MeMber filter achieved improved tracking accuracy and reliability.

Conclusions:

• The proposed focal plane ambiguous measurement model and modified MeMber filter offer significant advantages for space-based passive target tracking.
• Accurate modeling of measurement errors, particularly pixel resolution, is vital for effective space surveillance.
• The developed algorithm shows high application value for real-world space target detection and tracking systems.