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Jawahar, A.
- An Innovate Approach to Sonar Signal Based Undersea Non Maneuvering Target Localisation
Authors
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
Authors
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
Authors
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.