Interacting Multiple Model Joint Aircraft Guidance Mode and Control Set-Point Estimation
Year: 2026
Type: article
Abstract: To safely accommodate significantly higher air traffic demands, the future air traffic management (ATM) concept will make use of trajectory-based operations (TBOs) in combination with reduced separation criteria, where the intended flight trajectories will be better communicated to the air traffic control system on the ground, and an improved ground capability for monitoring the realization of or deviation from the communicated flight plan will be available. Current ATM makes use of ground target tracking systems that account for basic mode switching between level flight, climb, and descent. However, future ATM is in need of a ground system that also considers onboard flight guidance modes. In a prior contribution, we developed an interacting multiple model (IMM) filter that takes onboard flight guidance modes into account and demonstrated that such an approach performs well under nominal conditions. But the IMM was developed under the unrealistic assumption that, for each guidance mode, the actual control set point is known. The objective of the current contribution is to extend our earlier work by dropping such an unrealistic assumption. In nonlinear filtering, a simultaneous switching of a guidance mode and a jump in the control set point is referred to as a hybrid jump. To cope with such hybrid jumps, the standard IMM has been extended to a generalized IMM (GIMM). The current article develops this GIMM approach, considering ADS-B and enhanced mode S surveillance data, for the joint estimation of simultaneous jumps in aircraft guidance modes and control set points and shows its performance on both simulated and real flight data.
DOI: 10.2514/1.g009123
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: SESAR Joint Undertaking
OpenAlex ID: W7161554101