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Measure of nonlinearity for underwater target tracking using hull-mounted sensor
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作者 B.Omkar Lakshmi Jagan S.Koteswara Rao 《International Journal of Intelligent Computing and Cybernetics》 EI 2022年第3期333-344,共12页
Purpose-Doppler-Bearing Tracking(DBT)is commonly used in target tracking applications for the underwater environment using the Hull-Mounted Sensor(HMS).It is an important and challenging problem in an underwater envir... Purpose-Doppler-Bearing Tracking(DBT)is commonly used in target tracking applications for the underwater environment using the Hull-Mounted Sensor(HMS).It is an important and challenging problem in an underwater environment.Design/methodology/approach-The system nonlinearity in an underwater environment increases due to several reasons such as the type of measurements taken,the speeds of target and observer,environmental conditions,number of sensors considered for measurements and so on.Degrees of nonlinearity(DoNL)for these problems are analyzed using a proposed measure of nonlinearity(MoNL)for state estimation.Findings-In this research,the authors analyzed MoNL for state estimation and computed the conditional MoNL(normalized)using different filtering algorithms where measurements are obtained from a single sensor array(i.e.HMS).MoNL is implemented to find out the system nonlinearity for different filtering algorithms and identified how much nonlinear the system is,that is,to measure nonlinearity of a problem.Originality/value-Algorithms are evaluated for various scenarios with different angles on the target bow(ATB)in Monte-Carlo simulation.Computation of root mean squared(RMS)errors in position and velocity is carried out to assess the state estimation accuracy using MATLAB. 展开更多
关键词 Nonlinear filtering Statistical signal processing Underwater target tracking Estimation theory hull-mounted sensor
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