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

Jun Su¹, Yaan Li¹, Wasiq Ali¹

¹School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.

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|July 16, 2020

Summary

This study introduces a novel Gauss-Helmert iterated Unscented Kalman filter for underwater passive acoustic target tracking. The enhanced method improves tracking accuracy by addressing signal time delay and incomplete observability.

Keywords:

Doppler-angle tracking Gauss–Helmert model signal time delay three-dimensional underwater tracking

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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.