The generalized Kalman filter approach to adaptive underwater target tracking
Abstract
The generalized Kalman filtering (GKF) method is applied to underwater target tracking. The proposed GKF is based on the formulation developed by J.C. Lagarias and F. Aminzadeh (1983) establishing a tradeoff between the cost associated with estimation error and the cost related to the lateral discontinuity of the estimates. By assigning proper weights for accuracy and stability in the objective function, the desired balance between accuracy of estimates and lateral continuity is achieved. Computational results illustrate the performance of the technique. Conclusions as to the effects of the accuracy and stability weights are drawn.>
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References 17 · Cited by 22
- Authors
- El-Hawary, F., Aminzadeh, F., & Mbamalu, G. A. N.
- Affiliations
- Technical University of Nova Scotia (CA)
- ORCID
- Aminzadeh, F.
- Venue
- IEEE Journal of Oceanic Engineering
- Published
- 1992
- Volume
- 17
- Issue
- 1
- Pages
- 129-137
- ISSN
- 0364-9059 (ISSN-L)
- OpenAlex
- W2148178564
- Cited by
- 22
- References
- 17
- Citations by year
- 2026: 1 · 2025: 1 · 2021: 1 · 2019: 3 · 2016: 1 · 2015: 1
- FWCI
- 2.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Oceanic Engineering (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- generalized Kalman filter, underwater target tracking, adaptive filtering, cost function weighting
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