Multi-hypothesis Filter for Passive Tracking of Surface and Sub- Surface Target Localization

摘要

A Multi-hypothesis Iterated-Extended Kalman Filter (MHEKF) for passive sonar tracking and localization of surface and submerged targets using elevation and bearing angle measurements is presented. The MHEKF operates in a multi-depth mode by creating a bank of independently operating range- parameterized Cartesian EKFs, each receiving the same measurement data. The multi-depth mode operation allows the EKF to determine a unique (x, y, z) position solution using elevation and bearing measurements. At the first available measurement, the multi-hypothesis filter logic calculates the number and positioning of the depth banks in the water column from the operational decision radius along with the sensor beam widths and water depth. The bank depths are set in a geometric progression that yields constant coefficient of variation in range calculated with respect to the operational decision region. The MHEKF uses the normalized likelihood from each EKF depth-mode output to recursively update the target track. Any velocity or Doppler information available will reduce track ambiguity that arises when the tracker is expected to distinguish fast moving targets on the surface from slow moving targets at depth.