Soft Computing Technique (PLE) for Target Tracking

Computer Engineering electronics Engineering Civil Engineering

The pseudo linear Kalman filter for target tracking concerns the estimation of target motion parameters i.e., range, bearing, course and speed of a moving target, from noisy corrupted data. In the ocean environment. two dimensional bearings-only target motion analysis is generally used. An observer monitors sonar bearings from radiating target in passive listening mode. An observer processes these measurements and finds out target motion parameters like, range, course, bearings and speed of the target. As range is not available and the bearing measurement is not linearly related to the target states, the whole process becomes nonlinear. Added to this, since bearing measurements are extracted from passive sonar, the process remains unobservable until observer executes a proper maneuver. The measurements are corrupted with noise, hence the process becomes the random process. The pseudo linear filter is projected in such a way that it does not require any initial estimate at all and at the same time offers all the features of the extended kalman filter based pseudo-linear filter; namely sequential processing, flexibility to adopt the variance of each measurement. The algorithm is tested in Monte Carlo simulations and results are presented for one typical scenario. Effect of random noise in the range ,course and speed distribution is presented. loading..