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Srikanth, K. S.
- Advanced Submarine Integrated Weapon Control System
Abstract Views :179 |
PDF Views:0
Authors
Jawahar Annabattula
1,
S. Koteswara Rao
1,
A. Sampath Dakshina Murthy
2,
K. S. Srikanth
1,
Rudra Pratap Das
2
Affiliations
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 8, No 35 (2015), Pagination:Abstract
Background/Objectives: In underwater, a single submarine processes noisy sonar bearings from a radiating target (ship/submarine/torpedo) in passive listening mode. Methods/Statistical Analysis: The target is assumed to be at constant velocity or maneuvering in its course/speed/course and speed. An adaptive Kalman filter estimates target motion parameters. Findings: Data fusion and data association in multi target and multi sensor scenario are carried out, using Chi-squared innovation process. Applications/Improvements: Finally improved torpedo intercept guidance algorithm with homing capabilities is developed for attacking the target.Keywords
Data Fusion, Doppler, Fire Control System, Towed Array- Multi-Sensor Submarine Surveillance System using MGBEKF
Abstract Views :162 |
PDF Views:0
Authors
Jawahar Annabattula
1,
S. Koteswara Rao
1,
A. Sampath Dakshina Murthy
2,
K. S. Srikanth
1,
Rudra Pratap Das
2
Affiliations
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 8, No 35 (2015), Pagination:Abstract
Background/Objectives: The modern submarines use mutlitple sensors for tracking multiple targets in sea environment. In general, multiple sensor data can be handled in two ways: measurement fusion and state vector fusion. Methods/ Statistical Analysis: Measurement fusion is not practical for implementation due to various reasons and hence state vector fusion is proposed. Target trackingusing Modified Gain Bearings only Extended Kalman Filter in generic two-dimensional platform is carried out in each channel. Findings: In this approach, a state vector and its corresponding covariance matrix are extracted from the sensor measurements by an estimator equipped on each sensor. The output of each channel is transported via a data link in to order to be reach the fusion center. Applications/Improvements: A composite target state vector is obtained by performing track-to-track correlation and fusion at the fusion center.Monte-Carlo simulation is carried outand the results are presented for a typical scenario.Keywords
Estimation, Fusion, Kalman Filter, Simulation, Tracking- Underwater Passive Target Tracking in Constrained Environment
Abstract Views :158 |
PDF Views:0
Authors
Jawahar Annabattula
1,
S. Koteswara Rao
1,
A. Sampath Dakshina Murthy
2,
K. S. Srikanth
1,
Rudra Pratap Das
2
Affiliations
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 8, No 35 (2015), Pagination:Abstract
In underwater scenario, observer manoeuvre is required to find out target motion parameters in bearings only passive target tracking. Sometimes, due to tactical constraints, observer is not able to carry out manoeuvre. In this paper, it is shown that target motion parameters can be obtained in such situation, if the knowledge of any one of the target motion parameters is available. There are other practical problems like spurious bearings are generated by sonar, etc. In addition, auto tracking fails often and some bearings will be missed. Pseudo Linear Kalman Filter is made flexible to address these practical problems.Keywords
Constrained Environment, Direction of Arrival Estimation, Kalman Filtering, Monte Carlo Simulation, Passive Target Tracking, Target Detection- Power Management Strategy for Hybrid Microgrid System under Islanded Condition using Adaptive Droop Control
Abstract Views :122 |
PDF Views:0
Authors
Affiliations
1 Electrical and Electronics Engineering, KL University Greenfields, Vaddeswaram, Guntur District - 522502, Andhra Pradesh, IN
1 Electrical and Electronics Engineering, KL University Greenfields, Vaddeswaram, Guntur District - 522502, Andhra Pradesh, IN