A New Coarse Gating Strategy Driven Multidimensional Assignment for Two-Stage MHT of Bearings-Only...

Area of Science:

• Signal Processing
• Estimation Theory
• Robotics

Background:

• Multisensor-multitarget tracking with bearings-only data presents significant computational challenges.
• Multidimensional assignment (MDA) is essential for data association but computationally intensive.

Purpose of the Study:

• To develop a computationally efficient strategy for multidimensional assignment in bearings-only tracking.
• To reduce the complexity of data association in multisensor-multitarget tracking scenarios.

Main Methods:

• A novel coarse gating strategy is proposed, utilizing Mahalanobis distance for early elimination of infeasible associations.
• The strategy involves an iterative process for maximum likelihood estimation with an early exit condition.
• The coarse gating strategy is integrated into a two-stage multiple hypothesis tracking framework.

Main Results:

• The proposed coarse gating strategy significantly reduces computational complexity in MDA.
• Early termination of iterations based on Mahalanobis distance prevents excessive computation for invalid associations.
• Numerical experiments demonstrate the effectiveness of the proposed strategy in bearings-only multisensor-multitarget tracking.

Conclusions:

• The developed coarse gating strategy offers an effective solution for reducing computational load in bearings-only multisensor-multitarget tracking.
• This approach enhances the efficiency of data association within multiple hypothesis tracking frameworks.