DOAJ Open Access 2025

A modified adaptive Kalman filter algorithm for the distributed underwater multi-target passive tracking system

Xuefei Ma Jiaxin Ma Zexu Ma Rahim Khan Hengliang Wu +2 lainnya

Lihat Sumber DOI

Abstrak

A modified adaptive Kalman filter (AKF) algorithm is proposed to make underwater multi-target tracking with uncertain measurement noise reliable. By utilizing the proposed AKF algorithm with three core points, including an adaptive fading factor, measurement noise covariance adjustment, and an adaptive weighting factor, the unknown measurement noise and state vector can be estimated with good accuracy and robustness. The practical trial data verify this algorithm, and it has proven superior to all traditional algorithms in this Letter based on the results that it reduces the estimated position RMSEs by at least 10.29% while estimated velocity RMSEs by at least 52.57%.

Topik & Kata Kunci

Acoustics. Sound

Penulis (7)

Xuefei Ma

Jiaxin Ma

Zexu Ma

Rahim Khan

Hengliang Wu

Tingting Wang

Zhongwei Shen

Format Sitasi

APA MLA BibTeX

Ma, X., Ma, J., Ma, Z., Khan, R., Wu, H., Wang, T. et al. (2025). A modified adaptive Kalman filter algorithm for the distributed underwater multi-target passive tracking system. https://doi.org/10.1121/10.0034764

Akses Cepat

Lihat di Sumber doi.org/10.1121/10.0034764

Informasi Jurnal

Tahun Terbit: 2025
Sumber Database: DOAJ
DOI: 10.1121/10.0034764
Akses: Open Access ✓