Target Tracking in Clutter with Extremum Seeking Control for Adaptive Detection Thresholding.

Area of Science:

• Signal Processing
• Control Systems Engineering
• Sonar Technology

Background:

• Target tracking performance in sonar systems is critically dependent on the detection threshold.
• Existing methods for threshold adjustment often require prior knowledge of clutter signal probability density functions, which is unrealistic in many environments.
• Uncertainty in clutter distribution negatively impacts both target detection probability and overall tracking accuracy.

Purpose of the Study:

• To propose a robust detection threshold control method for sonar target tracking in environments with unknown clutter signal distributions.
• To develop a novel extremum seeking control structure adaptable to the nonlinear characteristics of detection processes.
• To enhance target tracking performance by dynamically optimizing the detection threshold.

Main Methods:

• Implementation of an extremum seeking control (ESC) strategy tailored for detection processes.
• Development of a new ESC structure designed to handle nonlinear system characteristics.
• Adjustment of the received signal amplitude's detection threshold to align estimated clutter density with a desired density.

Main Results:

• The proposed ESC method effectively controls the detection threshold in realistic, unknown clutter environments.
• Simulation studies confirm the method's ability to improve target tracking performance.
• The approach demonstrated convergence of estimated clutter measurement density to a designed density, optimizing performance.

Conclusions:

• The developed extremum seeking control method offers a viable solution for adaptive detection thresholding in sonar target tracking.
• This technique significantly enhances tracking performance, particularly in scenarios with unknown clutter characteristics.
• The proposed structure provides a robust framework for optimizing detection processes in complex, nonlinear systems.