Modelling Of The Underwater Targets Tracking With The Aid Of Pseudomeasurements Kalman Filter

Target motion analysis of the underwater target tracking by the UUV (Unmanned underwater vehicle) usually based on the bearing-only observations including azimuth and elevation angles. However, low angular resolution of hydro acoustic sonars is not enough for the good quality of tracking. Moreover, angular observations lead to nonlinear filtering such as Extended Kalman Filtering (EKF) which usually produces estimations with unknown bias and quadratic errors. As it was mentioned long ago in a case of bearing-only observations target unobservability may take place, therefore, some special observer’s motion become necessary. Other filters like the particle or unscented ones need the additional computer resources and also may produce the tracking loss. At the same time the pseudomeasurements Kalman filtering (PKF) method which transforms the estimation problem to the linear one and gives the current coordinates estimation with almost same accuracy could be modified to evaluate the moving target coordinates and velocities without bias. Since PKF gives unbiased estimate for the motion and the quadratic error it provides the good means for integration of various measurements methods such as passive (bearing-only) and active (range) metering. Using this filtering approach the good quality of target motion analysis (TMA) for randomly moving target may be achieved.