Indian Journal of Science and Technology

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Application of Pseudo Linear Estimator for Target Tracking


Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, India
 

Background/Objectives: Pseudo Linear Estimator (PLE) is developed for active sonar applications. Methods/Statistical analysis: The PLE offers features of Extended Kalman Filter (EKF). Findings: The results of PLE are compared with that of EKF. The results of MC simulation are presented for typical scenarios. Application/Improvements: In PLE, there is no need to initialize target state vector and its covariance matrix with prior (approximate) knowledge and hence its performance is found to be better than that of EKF.

Keywords

Estimation, Kalman Filter, Pseudo Linear Estimator, Simulation, Target Tracking
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  • Application of Pseudo Linear Estimator for Target Tracking

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Authors

K. Lakshmiprasanna
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, India
S. Koteswara Rao
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, India
A. Jawahar
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, India
Sk. B. Karishma
School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, India

Abstract


Background/Objectives: Pseudo Linear Estimator (PLE) is developed for active sonar applications. Methods/Statistical analysis: The PLE offers features of Extended Kalman Filter (EKF). Findings: The results of PLE are compared with that of EKF. The results of MC simulation are presented for typical scenarios. Application/Improvements: In PLE, there is no need to initialize target state vector and its covariance matrix with prior (approximate) knowledge and hence its performance is found to be better than that of EKF.

Keywords


Estimation, Kalman Filter, Pseudo Linear Estimator, Simulation, Target Tracking



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i16%2F132659