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Constrained state estimation for underwater target tracking problem
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DOI：10.1016/j.dsp.2025.105394.png)
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Abstract
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• A constrained estimation method is proposed to improve tracking accuracy using known range and velocity limits of the target. • Range limits are estimated using bearing angle, Doppler-shifted frequency, and target sound intensity measurements. • Supervised machine learning classifiers are used for range classification to determine the range limits. • Velocity limits are estimated from the target's Doppler-shifted frequency. • The Lagrange multiplier method solves the constrained optimization problem and provides the final estimated target state.
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