Optimal Geometry and Motion Coordination for Multisensor Target Tracking with Bearings-Only Measurements

Area of Science:

• Robotics and Control Systems
• Sensor Networks
• Estimation Theory

Background:

• Mobile sensor networks are crucial for target tracking.
• Bearings-only sensors present unique challenges due to limited measurement types.
• Optimizing sensor geometry and motion is key to improving tracking performance.

Purpose of the Study:

• To derive the optimal geometry for multiple mobile bearings-only sensors.
• To develop a motion coordination strategy for sensors to achieve optimal formations.
• To enhance target tracking performance through optimal sensor configuration.

Main Methods:

• Derivation of general optimal sensor-target geometry using D-optimality for n sensors.
• Development of a motion coordination method to achieve a circular radius orbit (CRO) and circular formation.
• Optimization of sensor motion under constraints to minimize travel distance.

Main Results:

• A general optimal sensor-target geometry is established based on partitioning the number of sensors.
• A method is presented to guide sensors into a CRO and then into optimal geometric subsets.
• The proposed approach effectively steers sensors to achieve desired formations for improved tracking.

Conclusions:

• The derived optimal geometry and motion coordination method enhance target tracking performance for bearings-only sensors.
• The approach is effective in guiding sensors to form optimal circular formations.
• This work provides a valuable framework for designing coordinated mobile sensor systems.