Underwater 3D Doppler-Angle Target Tracking with Signal Time Delay

Area of Science:

• Underwater acoustics
• Signal processing
• Estimation theory

Background:

• Traditional target tracking faces challenges in underwater passive acoustic scenarios.
• Incomplete observability and signal time delay significantly degrade tracking performance.
• Passive acoustic sensors lack accurate target range information.

Purpose of the Study:

• To develop an advanced filtering algorithm for robust underwater passive acoustic target tracking.
• To mitigate the negative impacts of signal time delay and system incomplete observability.
• To enhance tracking accuracy and stability in three-dimensional underwater environments.

Main Methods:

• Introduction of the Gauss-Helmert model to incorporate unknown signal emission time as a state variable.
• Expansion of the Gauss-Helmert model to handle implicit equations and previous/current states.
• Development of a Gauss-Helmert iterated Unscented Kalman filter for improved accuracy through second-stage iteration.

Main Results:

• The proposed Gauss-Helmert iterated Unscented Kalman filter demonstrates superior estimation accuracy.
• The new method exhibits more stable performance compared to existing filtering algorithms.
• Effective handling of signal time delay and improved system observability were achieved.

Conclusions:

• The Gauss-Helmert iterated Unscented Kalman filter provides a significant advancement for underwater passive acoustic target tracking.
• The proposed approach effectively addresses key challenges in underwater acoustic environments.
• This method offers a more reliable solution for estimating the state of moving targets underwater.