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Co-Authors
- Ch. Rajya Lakshmi
- B. Omkar Lakshmi Jagan
- S. Koteswara Rao
- S. K. B. Karishma
- A. Vijaya
- Sk. B. Karishma
- K. Lakshmiprasanna
- K. Lakshmi Prasanna
- SK. B. Karishma
- Rajya Lakshmi
- N. Priyanka
- M. Yamini
- K. Vijayaraj
- R. Anantharam
- M. Kumara Dhas
- S. Sasikanth
- G. Chinna Rao
- S. S. Kiran
- B. Ramana Babu
- G. Sailaja
- D. Lakshman
- Y. Murali Krishna
- V. Subrahmanya Aditya
Journals
- Indian Journal of Automation and Artificial Intelligence
- Indian Journal of Science and Technology
- Fuzzy Systems
- Digital Signal Processing
- Automation and Autonomous Systems
- Artificial Intelligent Systems and Machine Learning
- Asian Journal of Research in Chemistry
- Indian Journal of Innovations and Developments
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Jawahar, A.
- Feasible Course Trajectories for Undersea Sonar Target Tracking Systems
Abstract Views :309 |
PDF Views:173
Authors
Affiliations
1 Dept of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, A.P., IN
1 Dept of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, A.P., IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 3, No 1 (2016), Pagination: 1-5Abstract
Background/Objectives: In underwater sonar environment, the target motion parameters can be obtained only when observer maneuvers in some particular manner is satisfying certain requirements.
Methods/Statistical analysis: The algorithm is evaluated using Line of sight measurements which are obtained from intercept radar. Though the recommended maneuver may not be optimum, observability is ensured.
Findings: Recursive Maximum Likelihood Estimator with initial estimation from Recursive Pseudo Linear Estimator is used to evaluate the process.
Application/Improvements: For the purpose of analysis, the proposed observer maneuver is used for a typical scenario at low, medium and high target angles. Convergence time and the accuracy of the solution in Monte-Carlo simulation are presented in detail.
Keywords
Estimation, Sonar, Simulation, Target Motion Analysis, Maneuver, Line of Sight Measurements.Full Text
References
- J. A. Fawcett. Effect of course maneuvers on bearings-only range estimation. IEEE Transactions on Acoustics, Speech and Signal processing. 1988; ASSP -36(8), 1193-1199.
- A.G.Lindgren, K.F. Gong. Properties of a bearings only motion analysis estimator: An interesting case study in system observability. In: Proceedings 12th Asilomar Conference Circuits, Systems and Computers. 1978; 50-58.
- S.C.Nardone, V.J. Aidala. Observability criteria for bearings-only target motion analysis. IEEE transactions on aerospace and electronic systems. 1981; AES-17(2).
- D. T. Pham. Some quick and efficient methods for bearings-only target motion analysis. IEEE Transactions on Acoustics, Speech and Signal processing. 1993; ASSP -41(9), 2737-2751.
- A.Jawahar, S.Koteswara Rao. Modified Polar Extended Kalman Filter (MP-EKF) for Bearings - Only Target Tracking. Indian Journal of Science and Technology. 2016; 9(26), 1-5.
- A.Jawahar, S.Koteswara Rao. Recursive Multistage Estimator for Bearings only Passive Target Tracking in ESM EW Systems. Indian Journal of Science and Technology. 2015; 8(26), 1-5.
- A.Jawahar, S. Koteswara Rao, A. Sampath Dakshina Murthy, K.S. Srikanth, Rudra Pratap Das. Underwater Passive Target Tracking in Constrained Environment. Indian Journal of Science and Technology. 2015; 8(35), 1-4.
- Data Fusion of Towed Array and Hull Mounted Array Measurements for Passive Acoustic and Electromagnetic Underwater Localisation and Classification
Abstract Views :317 |
PDF Views:186
Authors
Affiliations
1 Dept of Electrical and Electronics Engg, Sanketika Institute of Technology and Management, Visakhapatnam, AP, IN
1 Dept of Electrical and Electronics Engg, Sanketika Institute of Technology and Management, Visakhapatnam, AP, IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 3, No 1 (2016), Pagination: 1-5Abstract
Background/Objectives: In our earlier work, data fusion with specific application to underwater tracking environment was explored. The target can be tracked using array bearings, while it is moving with constant velocity and maneuvering occasionally.
Methods/Statistical analysis: In this paper, it is shown that if data fusion is carried out using the bearing measurements available from Towed Array (TA) along with hull mounted array’s bearings, then tracking of a continuously moving target can be carried out easily.
Findings: This algorithm is independent of ownship maneuver for the observability of the process. Song and Speyer's modified gain algorithms are utilized with some modifications for estimation.
Application/Improvements: Monte Carlo simulation is performed and results are shown for various typical geometries which revealed that this algorithm is useful naval based applications.
Keywords
Estimation, Sonar, Tracking, Data Fusion, Kalman Filter, Observability, Maneuver.Full Text
References
- V. J. Aidala. Kalman Filter behavior in bearings only tracking applications. IEEE Transactions and Aerospace Electronic Systems. 1979, AES-15(1), 29-39.
- V.J.Aidala, S.C. Nardone. Biased Estimation Properties of the pseudo linear estimator, IEEE Transactions and Aerospace Electronic Systems. 1982, AES-18,(4), 432-441.
- A.G.Lindgren, K.F.Gong. Position and Velocity Estimation via Bearing Observations, IEEE Transactions on Aerospace and Electronic Systems. 1978, AES-14, 564-577.
- V.J. Aidala, S.E.Hammel, Utilization of Modified Polar Coordinates for bearings only tracking. IEEE Transactions Automatic Control. 1983, Ac-28(3), 283-294.
- S.C Nardone, A.G. Lindgren and K.F.Gong. Fundamental properties and performance of conventional bearings only target motion analysis, IEEE Transaction Automatic Control. 1984, Ac -29(9), 775-787.
- S. Koteswara Rao. Pseudo linear estimator for Bearings only Passive target tracking. IEE Proceedings Radar, Sonar and Navigation., 2001, 148(1), 16-22.
- T.L. Song, J.L. Speyer. A stochastic Analysis of a modified gain extended Kalman filter with applications to estimation with bearing only measurements, IEEE Transactions Automatic Control. 1985, Ac -30(10), 940-949.
- P.J. Galkowski, M.A. Islam. An Alternative Derivation of the Modified Gain Function of Song and Speyer. IEEE Transactions Automatic Control. 1991, Ac-36(11), 1323-1326.
- S. Koteswara Rao. Algorithm for detection of maneuvering Targets in Bearings only Passive target Tracking. IEE Proceedings Radar, Sonar and Navigation., 1999, 146(3), 141-146.
- S. Koteswara Rao. Modified gain extended Kalman filter with application to bearings-only passive maneuvering target tracking, IEE Proc., Radar, Sonar and Navigation., 2005, 152(4), 239-244.
- A.Jawahar, S.Koteswara Rao, Modified Polar Extended Kalman Filter (MP-EKF) for Bearings - Only Target Tracking, Indian Journal of Science and Technology, 2016, 9(26),1-5.
- A.Jawahar, S.Koteswara Rao Recursive Multistage Estimator for Bearings only Passive Target Tracking in ESM EW Systems, Indian Journal of Science and Technology, 2015, 8(26), 1-5.
- A.Jawahar,S. Koteswara Rao, A.Sampath Dakshina Murthy, K.S.Srikanth, Rudra Pratap Das Advanced Submarine Integrated Weapon Control System, Indian Journal of Science and Technology, December 2015, 8(35), 1-3.
- A.Jawahar, S. Koteswara Rao, A.Sampath Dakshina Murthy, K.S. Srikanth, Rudra Pratap Das. Multi-sensor Submarine Surveillance System using MGBEKF, Indian Journal of Science and Technology, 2015 8(35),1-5 .
- A.Jawahar, S. Koteswara Rao, A. Sampath Dakshina Murthy, K.S. Srikanth, Rudra Pratap Das Underwater Passive Target Tracking in Constrained Environment, Indian Journal of Science and Technology, 2015, 8(35), 1-4.
- Application of Particle Filter using TA Bearing Measurements
Abstract Views :209 |
PDF Views:0
Authors
Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andra Pradesh, IN
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 7 (2016), Pagination:Abstract
Background/Objectives: An Algorithm, the Particle filter, is proposed for implementing the bearings only Torpedo Motion Analysis (TMA). The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm. The method is not restricted by assumptions of linearity or Gaussian noise. Methods/Statistical analysis: The particle filter is combined with Modified Gain Bearings Only Extended Kalman Filter and the results are compared with that of Extended Kalman Filter or Unscented Kalman Filters. Findings: Almost similar performance is obtained. The algorithm is applied to track a torpedo using measurements available from towed array. Application/Improvements: The results in simulation mode and with sea trial data are presented.Keywords
Algorithm, Estimation, Gaussianity, Kalman Filter, Linearity, Simulation, Towed ArrayFull Text
- Characterization Studies of Non-Linear Sonar Signal Estimation Scheme for Underwater Tracking and Surveillance for Naval Applications
Abstract Views :215 |
PDF Views:2
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Fuzzy Systems, Vol 8, No 9 (2016), Pagination: 243-248Abstract
Altered Gain Extended Kalman Filter (MGEKF) created by Song and Speyer [1] was ended up being reasonable calculation for edges just uninvolved target following applications in air. As of late, roughly changed increases are exhibited, which are numerically steady and precise [2]. In this paper, this enhanced MGEKF calculation is investigated for submerged applications with a few adjustments. In submerged, the clamor in the estimations is high, turning rate of the stages is low and speed of the stages is additionally low when contrasted and the rockets in air. These attributes of the stage are considered in detail and the calculation is changed appropriately to track applications in submerged. Monte-Carlo mimicked comes about for two regular situations are exhibited with the end goal of clarification. From the outcomes it is watched that this calculation is particularly reasonable for this nonlinear edges just latent target following.
Keywords
Estimation, Sonar, Kalman Filter, Simulation, Modified Gain, Angles-Only Target Tracking.
- An Innovate Approach to Sonar Signal Based Undersea Non Maneuvering Target Localisation
Abstract Views :169 |
PDF Views:1
Authors
Affiliations
1 Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Digital Signal Processing, Vol 8, No 10 (2016), Pagination: 258-262Abstract
The passive target tracking using bearings-only measurements is studied for several underwater applications This research effort is to track the target even though the range measurements are not available. As range measurement is not available and the bearing measurement is not linearly related to the target states, the whole process becomes nonlinear. But many times it is difficult to carry out maneuver by own ship due to tactical reasons. Unscented Angles-only Kalman Filter (UAKF) is used for bearing and elevation target tracking. The mathematical modeling and simulation have been carried out. It is shown that UAKF algorithm effectively tracks the target in underwater environment.
Keywords
Stochastic Theory, Statistical Signal Processing, Applied Statistics, Estimation Theory, Sonar, Range, Bearing Measurements, Sigma Points, Elevation, Kalman Filter.- Undersea Target Localization and Detection using Advanced Positioning System and Non-Linear Estimation Techniques
Abstract Views :155 |
PDF Views:2
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Digital Signal Processing, Vol 8, No 9 (2016), Pagination: 242-246Abstract
Tracking underwater targets is a focused application area in modern underwater defence systems. The passive target tracking using bearings-only measurements is studied for several underwater applications In under water environment, Sonobuoy receives target information in the form of acoustic energy and processes the data to get range and bearing measurements. As range measurement is not available and the bearing measurement is not linearly related to the target states, the whole process becomes non linear. But many times it is difficult to carry out maneuver by own ship due to tactical reasons. Extended Kalman filter is used to process these noise corrupted measurements. This information about target motion parameters are communicated to the airplane by means of an UHF link and airplane releases the weapon on to the target. Results obtained in simulation are presented.
Keywords
GPS, Sonobuoy, Target Motion Analysis, Stochastic Processing, Statistical Stochastic Processing.- Linear Quadratic Recursive Estimation Scheme Using Bayesian Inference for Navigation Systems
Abstract Views :183 |
PDF Views:1
Authors
Affiliations
1 Sanketika Institute of Technology and Management, IN
1 Sanketika Institute of Technology and Management, IN
Source
Digital Signal Processing, Vol 8, No 10 (2016), Pagination: 263-269Abstract
In the ocean environment, two dimensional Range & Bearings Target Motion Analysis (TMA) is generally used. In the underwater scenario, the active sonar, positioned on a observer, is capable of sensing the sound waves reflected from the target in water. The sonar sensors in the water pick up the target reflected signal in the active mode. The observer is assumed to be moving in straight line and the target is assumed to be moving mostly in straight line with maneuver occasionally. The observer processes the measurements and estimates the target motion parameters, viz., Range, Bearing, Course and Speed of the target. It also generates the validity of each of these parameters. Here we try to apply Kalman Filter for the sea scenario using the input estimation technique to detect target maneuver, estimate target acceleration and correct the target state vector accordingly. There are mainly two versions of Kalman Filter – a Linearised Kalman Filter (LKF) in which polar measurements are converted into Cartesian coordinates and the well-known Extended Kalman Filter (EKF). Recently S. T. Pork and L. E. Lee presented a detailed theoretical comparative study of the above two methods and stated that both the methods perform well. Here, EKF is used throughout.
Keywords
Estimator, Fire Control System, Helicopter, Initial Turn Angle, Weapon Control Algorithm, Kalman Filter, Splash Point Algorithm.- Optimal Recursive Data Processing Algorithm for Underwater Vehicle Localisation and Ranging
Abstract Views :255 |
PDF Views:2
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Automation and Autonomous Systems, Vol 8, No 10 (2016), Pagination: 275-282Abstract
Range and bearing measurements of underwater vehicle is obtained by helicopter which uses dunking sonar. Considering range and bearing measurements the target position is identified and target motion parameters are available to guide the weapon on the target vehicle. Target motion parameters are finally found by using Extended Kalman filter. Present weapon parameters are initial turning angle, straight run distance and many other which are obtained using the known parameters like speed, course of the helicopter and the target motion parameters. Results of Monte Carlo simulation are shown which gives the better performances of the algorithm for typical scenarios using Matlab.Keywords
Estimation, Stochastic, Bearing, Line of Sight, Kalman Filter, Sonar, Weapon.- Target Localization and Mathematical Modelling for Maritime Based Sonar Applications Using Kalman Filter
Abstract Views :273 |
PDF Views:2
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Automation and Autonomous Systems, Vol 8, No 10 (2016), Pagination: 287-298Abstract
Tracking underwater targets is a focused application area in modern underwater defense systems. The passive target tracking using bearings-only measurements is studied for several underwater applications. Surveillance is the most important feature of maritime warfare and is undertaken by active as well as passive sensors. Active methods of surveillance require acoustic transmissions to be made by the surveillance platform and hence susceptible to interception by others. Hence, in certain situations it becomes necessary to maintain silence on active mode. In the ocean environment, two dimensional bearings-only Target Motion Analysis (TMA) is generally used. In this paper, three-dimensional target motion analysis tracking an air target is implemented using Kalman filter. This is an extension of TMA tracking from a two-dimensional to three-dimensional scenario.
Keywords
Estimation, Tracking, Radar, Simulation, Active Mode, Maneuver, Range, Bearing Measurement.- More Reliable and Automated Target Localisation when Tracking Low Signature Targets in Areas with Heavy Shipping
Abstract Views :199 |
PDF Views:1
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 8, No 9 (2016), Pagination: 299-303Abstract
In maritime environment, the surveillance plays a major role. Tracking underwater targets is a focused application area in modern underwater defence systems. The passive target tracking using bearings-only measurements is studied for several underwater applications. Many estimation algorithms have been formulated in recent years for accurate and reliable target estimation and localization using passive acoustic noisy measurements .The aim of this paper is to track the target even though the range measurements are not available. Modified gain angles-only extended Kalman filter (MGAEKF) is used for bearing and elevation target tracking. The mathematical modeling and simulation have been carried out. It is shown that MGAEKF algorithm effectively tracks the target in underwater environment.
Keywords
Stochastic Theory, Sonar, Kalman Filter, Localization, Lone of Sight Measurements, Statistical Signal Processing, Applied Statistics, Estimation Theory.- Passive Target Tracking using Intercept Sonar Measurements
Abstract Views :185 |
PDF Views:0
Authors
Affiliations
1 KarishmaSchool of Electrical Sciences, KL University, Vaddeswaram – 522502, Andhra Pradesh, IN
1 KarishmaSchool of Electrical Sciences, KL University, Vaddeswaram – 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 12 (2016), Pagination:Abstract
Intercept sonar of ownship is used to track a target, which is assumed to be doing active transmission for detecting a target in underwater. The ownship intercepts the active transmissions and generates bearing measurements of the target. The measurement interval between generated bearings in intercept mode is not constant and so closed loop estimators like Kalman filter is not useful to find out target motion parameters. So, sub-optimal estimator like Pseudo Linear Estimator (PLE) is used. Recursive PLE developed by S. K. Rao is modified to suit this application. The algorithm is tested in Monte-Carlo simulation and its results are presented for two typical scenarios.
Keywords
Bearings-Only Measurements, Estimation, Intercept Measurements, Kalman Filter, Target TrackingFull Text
- Application of Parameterized Modified Gain Bearings-Only Extended Kalman Filter for Undersea Tracking
Abstract Views :216 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Communication Engineering, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
2 Department of Electronics and Communication Engineering, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh
1 Department of Electronics and Communication Engineering, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
2 Department of Electronics and Communication Engineering, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh
Source
Indian Journal of Science and Technology, Vol 9, No 13 (2016), Pagination:Abstract
Background/Objectives: This paper presents parameterized Modified Gain Bearings Only Extended Kalman Filter to track a torpedo using bearings-only measurements. Methods/Statistical Analysis: The parameterization is included to obtain fast convergence in estimated torpedo motion parameters. Findings: Observer uses estimated target kinematics to determine proper observer manuever calculates. Monte-Carlo simulation is carried out and the results are presented. Application/Improvements: It is noted that parameterization reduces the time of convergence and the results are satisfactory.Keywords
Kalman Filter, Sonar, TorpedoFull Text
- Ownship Strategies during Hostile Torpedo Attack
Abstract Views :191 |
PDF Views:0
Authors
Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram – 522502, Andhra Pradesh, IN
1 School of Electrical Sciences, KL University, Vaddeswaram – 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 16 (2016), Pagination:Abstract
Background/Objectives: The necessity of ownship stratagies is essential during the attack of enemy torpedo. Methods/Statistical Analysis: Torpedo tacking using advanced particle filter is proposed in bearings-only tracking environment for underwater applications. The observer platform has to perform evasive maneuver as well as perform target motion analysis to track the incoming hostile torpedo. Particle Filter (PF) combined with Modified Gain Bearings-Only Extended Kalman Filter (MGBEKF) is proposed technique. Findings: Monte-Carlo simulation is carried out for performance evaluation of the algorithm and the obtained results are presented which agree that PF-MGBEKF is most suitable as a part of ownship strategy.Keywords
Bearing Measurements, Estimation, Simulation, Sonar, Torpedo, TrackingFull Text
- Application of Pseudo Linear Estimator for Target Tracking
Abstract Views :192 |
PDF Views:0
Authors
Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, IN
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 16 (2016), Pagination: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 TrackingFull Text
- Application of Cubature Kalman Filter for Bearingsonly Target Tracking
Abstract Views :216 |
PDF Views:0
Authors
Affiliations
1 Koneru Lakshmaiah University, Guntur – 522502, Andhra Pradesh, IN
1 Koneru Lakshmaiah University, Guntur – 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 17 (2016), Pagination:Abstract
Background/Objectives: The objective of this paper is to develop a novel estimation algorithm based target tracking simulator for underwater target tracking applications. Methods/Statistical Analysis: An own ship observes corrupted sonar bearings from a radiating target and finds out Target Motion Parameters (TMP) - viz., range, course, bearing and speed of the target. The issue is inherently nonlinear as the bearing measurement is non-linearly related to the target state. CKF is a new nonlinear filter for state estimation. The modeling of target state and measurement vectors is carried out. CKF is integrated into the model to result in evolution of simulator. Extensive performance evaluation of CKF with respect to bearings-only target tracking problem in Monte-Carlo simulation is carried out and the results are presented. Findings: CKF depends on spherical-radial cubature rule that makes it potential to numerically figure variable moment integrals encountered within the nonlinear filter. The underwater passive target tracking following Cubature Kalman filter is explored in this paper. Application/Improvements: The results obtained are satisfactory and UKF can be used in futuristic submarines in Indian Navy owing to its advantages as envisaged in this paper.Keywords
Cubature Kalman (CKF) Filter, Estimation, Kalman Filter, Simulation, Sonar, Underwater Target Tracking.Full Text
- Unscented Kalman Filter with Application to Bearings-only Passive Target Tracking
Abstract Views :211 |
PDF Views:0
Authors
Affiliations
1 Koneru Lakshmaiah University, Vaddeswaram - 522502, Andhra Pradesh, IN
1 Koneru Lakshmaiah University, Vaddeswaram - 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 19 (2016), Pagination:Abstract
Background/Objectives: Target tracking is an age old problem which demands robust statistical estimators which can effectively track the target within the acceptable limits of errors in target motion parameters. The objective of this paper is to develop a novel estimation algorithm based target tracking simulator for underwater target tracking applications. Methods/Statistical Analysis: The unscented transformation developed by Julier, et al., is applied to the body of Kalman filter to synthesize Unscented Kalman filter. The modeling of target state and measurement vectors is carried out. Unscented Kalman filter is integrated into the model to result in evolution of simulator. Extensive performance evaluation of UKF with respect to bearings-only target tracking problem in Monte-Carlo simulation is carried out and the results are presented. Findings: UKF algorithms effectively track the target with encouraging convergence time which is proved from the results obtained in single run and Monte-Carlo simulation. It is observed that UKF is suitable algorithm for bearings-only target tracking problem. Application/Improvements: The results obtained are satisfactory and UKF can be used in futuristic submarines in Indian Navy owing to its advantages as envisaged in this paper.Keywords
Estimation Theory, Kalman Filter, Simulation, Sonar, Target Tracking.Full Text
- Application of Bar-Shalom and Fortmann’s Input Estimation for Underwater Target Tracking
Abstract Views :142 |
PDF Views:0
Authors
Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
1 School of Electrical Sciences, KL University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 21 (2016), Pagination:Abstract
Background/Objectives: The Extended Kalman Filter (EKF) using range and bearing measurements is analyzed for undersea target tracking. The Input estimation technique, developed by Bar-Shalom and Fortmann for radar applications is implemented for sonar applications. Methods/Statistical Analysis: Input estimation is used to estimate the target acceleration whenever the target makes a maneuver. Findings: The algorithm estimates target kinematics using zero mean chi-square distributed random sequence residual. Upon detection of target maneuver, this algorithm corrects the velocity and position components using acceleration components. Application/Improvements: Finally, the performance of this algorithm is evaluated in Monte-Carlo simulations and results conform the effectiveness of input estimation technique.Keywords
Bearing Measurements, Estimation, Maneuvering, Range, Target Tracking.Full Text
- Modified Polar Extended Kalman Filter (MP-EKF) for Bearings - Only Target Tracking
Abstract Views :224 |
PDF Views:0
Authors
Affiliations
1 School of Electrical Sciences, KL University, Vaddeswaram - 522502, IN
1 School of Electrical Sciences, KL University, Vaddeswaram - 522502, IN
Source
Indian Journal of Science and Technology, Vol 9, No 26 (2016), Pagination:Abstract
Background/Objectives: Surveillance is most crucial part of maritime environment. The target needs to be tracked within shortest possible time with low complexity and computational cost. Methods/Statistical Analysis: Modified Polar Extended Kalman Filter is well suited for bearing only target tracking. In this paper a mathematical modelling and Monte Carlo simulation has been carried out. Findings: It is found out that MPEKF effectively tracks the underwater target. Therefore, it is suitable estimation algorithm for bearings-only underwater passive target tracking.Keywords
Bearing, Estimation, Kalman Filter, Manuever, Simulation, Target Tracking.Full Text
- An Innovative Approach to More Reliable and Automated Target Characterisation Studies for Underwater Maritime Survelliance
Abstract Views :164 |
PDF Views:2
Authors
A. Jawahar
1,
Rajya Lakshmi
1
Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Fuzzy Systems, Vol 9, No 4 (2017), Pagination: 61-66Abstract
Target Motion Analysis (TMA) using conventional passive bearing together with frequency measurements is explored. This approach offers one tactical advantage over the classical bearings-only TMA. It makes the ownship maneuver superfluous. In this paper, TMA is carried out using Unscented Kalman Filter (UKF). Inclusion of range, course and speed parameterization is proposed in UKF target state vector to obtain the convergence of the solution fast. Finally the results of various scenarios in Monte-Carlo simulation are presented. This method can be easily adopted for underwater passive target tracking application.
Keywords
Sonar, Estimation, Target Tracking, Ownship, Range, Course, Speed.- Modified Gain Bearing-only Extended Kalman Filter for Underwater Target Tracking
Abstract Views :172 |
PDF Views:0
Authors
Affiliations
1 Department of ECE, KL University, Greenfields, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
1 Department of ECE, KL University, Greenfields, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 10, No 8 (2017), Pagination:Abstract
Objectives: This paper proposes the own ship manoeuvring strategy to estimate the proper target state in the bearings only tracking. Methods/Statistical Analysis: The modified gain bearings-only extended Kalman filter is used for analysis, where the gain is modifiable. In the context of Target Motion Analysis, the target state is monitored through nonlinear estimations. The own ship exact manoeuvre is to increase the range observability. Findings: The proposed target estimation algorithm is effective in maritime tracking based sonar applications. Application/Improvements: The methodology proposed here is very useful for tracking underwater targets and finds immense usage for Indian Navy.Keywords
Estimation, Manoeuvre, Own Ship, Simulation, Sonar, Underwater TrackingFull Text
- Single Crystal EPR and X-Ray Studies of Exchange Interactions in Hexaaquocopper (II) Picrylsulphonate Tetrahydrate
Abstract Views :199 |
PDF Views:2
Authors
Affiliations
1 Department of Chemistry, NMSSVN College, Nagamalai, Madurai-625019, Tamilnadu, IN
2 Department of Chemistry, ANJA College, Sivakasi, Tamilnadu, IN
3 Department of Physics, Mahendra Arts and Science College, Kalippatti, Namakkal-637501, Tamilnadu, IN
1 Department of Chemistry, NMSSVN College, Nagamalai, Madurai-625019, Tamilnadu, IN
2 Department of Chemistry, ANJA College, Sivakasi, Tamilnadu, IN
3 Department of Physics, Mahendra Arts and Science College, Kalippatti, Namakkal-637501, Tamilnadu, IN
Source
Asian Journal of Research in Chemistry, Vol 10, No 2 (2017), Pagination: 85-94Abstract
Single crystals of hexaaquocopper(II) picrylsulphonate tetrahydrate, [Cu(H2O)6(picsul)2.4H2O and the corresponding copper(II) doped zinc and cadmium analogues have been prepared and subjected to EPR studies. X-ray diffraction studies of the pure complex reveal the structure to be triclinic and z=1, with a two dimensional Cu-picsul-Cu-picsul-chain running along b-axis, super exchange interactions are taking place through the chains, linked by H-bonds from uncoordinated water. The line width and line shape analysis indicate the system to be a quasi two dimensional one. A probe into the study of the metal ligand bonding has also been made.Keywords
Electron Paramagnetic Resonance, Metal Ligand, Line Width, Line Shape.- Comparative Investigation of Advanced Non-Linear Control Algorithms for Undersea Sonar-Based Tracing Applications
Abstract Views :252 |
PDF Views:3
Authors
Affiliations
1 NSTL, Visakhapatnam, Andhra Pradesh, IN
1 NSTL, Visakhapatnam, Andhra Pradesh, IN
Source
Automation and Autonomous Systems, Vol 9, No 7 (2017), Pagination: 129-142Abstract
Unscented Kalman Filter (UKF) and Cubature Kalman Filter (CKF) use Gaussian assumed density approximations. SimoSarkka has shown that UKF is a generalized one of CKF. Extensive performance evaluation of UKF and CKF with respect to bearings-only target tracking problem in Monte-Carlo simulation is carried out and the results are presented. It is observed that UKF is better than that of CKF for bearings-only target tracking problem.
Keywords
Estimation Theory, Sonar, Kalman Filter, Target Tracking, Simulation.References
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- Advanced Statistically Robust Estimation Algorithm for Underwater Vehicle Localization and Ranging for Sonar Applications
Abstract Views :383 |
PDF Views:162
Authors
Affiliations
1 Department of Basic Sciences and Humanities, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
2 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
3 Department of Electronics and Communication Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
1 Department of Basic Sciences and Humanities, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
2 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
3 Department of Electronics and Communication Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh-530041, IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 4, No 1 (2017), Pagination: 1-14Abstract
Objectives: Range and bearing measurements of underwater vehicle is obtained by helicopter which uses dunking sonar. Considering range and bearing measurements the target position is identified and target motion parameters are available to guide the weapon on the target vehicle.
Methods/Statistical analysis: Target motion parameters are finally found by using Extended Kalman filter. Present weapon parameters are initial turning angle, straight run distance and many other which are obtained using the known parameters like speed, course of the helicopter and the target motion parameters.
Findings: Results of Monte Carlo simulation are shown which gives the better performances of the algorithm for typical scenarios using Matlab.
Application/Improvements: The proposed algorithm can be used for undersea sonar based applications.
Keywords
Estimation, Stochastic, Bearing, Line of Sight, Kalman Filter, Sonar, Weapon.Full Text
References
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- B.O.L. Jagan, S. K. Rao, A. Jawahar, S.K.B. Karishma. Application of bar-shalom and fortmann’s input estimation for underwater target tracking. Indian Journal of Science and Technology. 2016; 9(21), 1-5.
- B.L. Kumari, S.R. Rao, K.P. Raju. Simplified target location estimation for underwater vehicles. Ocean Electronics (SYMPOL). 2013, 1-9.
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- Statistically Efficient Control Scheme for Undersea Surveillance for Sonar Ranging and Detection
Abstract Views :320 |
PDF Views:164
Authors
B. Ramana Babu
1,
A. Jawahar
1
Affiliations
1 Department of Computer Science and Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Computer Science and Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
Source
Indian Journal of Automation and Artificial Intelligence, Vol 4, No 1 (2017), Pagination: 1-9Abstract
Background/Objectives: Altered Gain Extended Kalman Filter (MGEKF) created by Song and Speyer was ended up being reasonable calculation for edges of just uninvolved target following applications in air. As of late, roughly changed increases are exhibited, which are numerically steady and precise. In this paper, this enhanced MGEKF calculation is investigated for submerged applications with a few adjustments.
Methods/Statistical Analysis: In submerged, the clamor in the estimations is high, turning rate of the stages is low and speed of the stages is additionally low when contrasted and the rockets in air.
Findings: These attributes of the stage are considered in detail and the calculation is changed appropriately to track applications in submerged. Monte-Carlo mimicked comes about for two regular situations are exhibited with the end goal of clarification.
Application/Improvements: From the outcomes it is watched that this calculation is particularly reasonable for this nonlinear edges just latent target following.
Keywords
Estimation, Sonar, Kalman Filter, Simulation, Modified Gain, Angles-Only Target Tracking.Full Text
References
- P.J. Golkoki, M.A. Islam. An alternative derivation of the modified gain function of song and speyer. IEEE Transactions on Automatic Control. 1999, 36(11), 1223-1326.
- M. Longbin, L. Qi, Z. Yiyu, S. Zhongkang. Utilization of the universal linearization in target tracking. IEEE Transactions on Aerospace and Electronic Systems.1997, 2, 941-945.
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- Jawahar, S.K. Rao. Modified polar extended kalman filter (MP-EKF) for bearings only target tracking. Indian Journal of Science and Technology. 2016, 9(26), 0974-5645.
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- A. Jawahar, S. Koteswara Rao. Modified Polar Extended Kalman Filter (MP-EKF) for bearings only target tracking. Indian Journal of Science and Technology. 2016, 9 (26), 1-5.
- Jawahar, S. Koteswara Rao, A.S.D. Murthy, K.S. Srikanth, R.P. Das. Advanced submarine integrated weapon control system. Indian Journal of Science and Technology. 2015, 8(35), 1-3.
- Jawahar, S. Koteswara Rao, A.S.D. Murthy, K.S. Srikanth, R.P. Das. Underwater passive target tracking in constrained environment. Indian Journal of Science and Technology. 2015, 8(35), 1-4.
- Jawahar, S. Koteswara Rao, S.K.B. Karishma. Target estimation analysis using data association and fusion. International Journal of Oceans and Oceanography. 2015, 9(2), 203-210.
- Jawahar, S. Koteswara Rao. Recursive multistage estimator for bearings only passive target tracking in ESM EW Systems. Indian Journal of Science and Technology. 2015, 8(26), 1-5.
- Jawahar. Feasible course trajectories for undersea sonar target tracking systems. Indian Journal of Automation and Artificial Intelligence. 2016, 3(1), 1-5.
- Jawahar, V.C. Chakravarthi. Improved Nonlinear Signal Estimation Technique For Undersea Sonar-Based Naval Applications. Innovare Journal of Engineering and Technology. 2016, 4(4), 20-25.
- Jawahar A, V.C. Chakravarthi. Comparative analysis of non linear estimation schemes used for undersea sonar applications. Innovare Journal of Engineering and Technology. 2016, 4 (4), 14-19.
- K.L. Prasanna, S. Koteswara Rao, B.O.L. Jagan, A. Jawahar, S.K.B. Karishma Data Fusion in Underwater Environment. International Journal of Engineering and Technology (IJET). 2016, 8(1), 225-234.
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- An Innovative Approach of Control and Simulation Based Analysis of Doubly Fed Electrical Machines for Harnessing Wind Energy
Abstract Views :267 |
PDF Views:0
Authors
Affiliations
1 Department of Electrical and Electronics Engineering, SANKETIKA Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
2 Department of Electrical and Electronics Engineering, PYDAH College of Engineering Kakinada - YANAM Road, East Godavari District Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, SANKETIKA Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
2 Department of Electrical and Electronics Engineering, PYDAH College of Engineering Kakinada - YANAM Road, East Godavari District Andhra Pradesh, IN
Source
Indian Journal of Innovations and Developments, Vol 6, No 1 (2017), Pagination: 1-9Abstract
Background/Objectives: Wind energy systems are need of the hour from electrical energy system point of view. Doubly fed electric machines are best suited for wind systems due to their ability to work under variable speed conditions.
Methods/Statistical Analysis: This paper proposes a new configuration of doubly fed induction generator (DFIG) called as single external feeding of DFIG (SEF-DFIG) which has significant merits over the former system.
Findings: The operating mode is presented with detailed analysis of the proposed system. Extensive simulation study is carried out by considering a hybrid energy system which consists of wind as well as other renewable energy sources.
Application/Improvements: The results obtained during the simulation case study demonstrate the usefulness of the proposed system.
Keywords
Doubly Fed Induction Generator, Hybrid Energy System, Green Energy, Simulation, Variable Speed Conditions.Full Text
References
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- Virtual Target Intercept Guidance Algorithm
Abstract Views :176 |
PDF Views:1
Authors
Affiliations
1 Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
2 Dilla University, ET
3 Naval Science Technological Laboratories, Visakhapatnam, IN
1 Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
2 Dilla University, ET
3 Naval Science Technological Laboratories, Visakhapatnam, IN
Source
Fuzzy Systems, Vol 10, No 2 (2018), Pagination: 34-39Abstract
The Contact Motion Analysis (CMA) estimates the target motion parameters of the target. Intercept guidance algorithm is used when all the estimated target motion parameters viz. Range, bearing, course and speed of the target are available. This method was used initially for non-homing weapons. These days, people are using for homing weapons with proximity fuse to destroy the target. The estimated target motion parameters are used to find out the initial turn angle (ita) and weapon straight run distance to hit the target. Once the weapon is fired, it turns as per the presetita and then moves in straight path to hit the target. The algorithm also finds out the weapon run time to hit the target. Sometimes hit may not be possible due to the limitations in speed, time and endurance of the weapon. This paper presents the guidance algorithm for undersea maritime target ranging and detection.Keywords
Estimation, Sonar, Target Ranging, Homing Range, Intercept Guidance, Virtual Target.References
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- Intelligent Extraction of Optimum Power from HRES Using MPPT Variants
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Authors
Affiliations
1 Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering, Andhra Pradesh, IN
2 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
3 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
1 Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering, Andhra Pradesh, IN
2 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN
3 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IN