On-Board Parameter Optimization for Space-Based Infrared Air Vehicle Detection Based on ADS-B Data

Abstract

Frequent aviation safety accidents of civil aircraft misses and crashes lead to an urgent need for flight safety assurance. Due to long-time flights over different backgrounds, accompanied by the changes in flight altitude and speed, it is difficult for a conventional space-based infrared detection system to use a set of fixed parameters to meet the stable detection requirement. To enhance the awareness of civil aircraft surveillance, a real-time parameter optimization method based on Automatic Dependent Surveillance-Broadcast (ADS-B) data is proposed. According to the background spectral characteristics and the real-time flight data, the most reasonable spectral band is analyzed, using the joint signal-to-noise/clutter ratio (JSNCR) as the evaluation criteria. Then, an automatic parameter adjustment is used to maximize the integration time and switch the integration capacitor gear. Numerical simulation results show that the JSNCR increased by 1.16 to 1.31 times, and the corresponding noise equivalent target radiant intensity (NET) reduced from 2.4 W/Sr to 1.2 W/Sr compared with a conventional fixed-parameter detection system. This study lays a solid theoretical foundation for the spectral band analysis of space-based AVD system design. Meanwhile, the proposed method can be used as a standard procedure to improve on-board performance.