Cued passive bearing estimation in distributed sensor data fusion

Active and passive sonar sensors provide complementary information about contacts. In addition to the physical characteristics of a passive array, the bearing resolution estimate can be limited by computational constraints given the necessity to survey the full azimuth for contacts. In a distributed field of sensors, however, it may be advantageous to divert the resources of a given sensor from a coarse resolution detection strategy to a fine resolution tracking of a contact of interest. In particular, the position estimate in the form of a probability density function can be used to cue a horizontal line array to switch from a full- azimuth (surveillance), robust adaptive beamforming (ABF) approach to a more sensitive ABF focused in the region of high contact probability. In this paper, we investigate the degree of bearing estimate refinement available through cued beamforming as a function of contact signal-to-noise ratio, uncertainty in contact position, and ABF sensitivity.