Eastern Macedonia and Thrace Institute of Technology
Abstract
Airborne magnetometers are utilized for the small-range search, precise positioning, and identification of the
ferromagnetic properties of underwater targets. As an important performance parameter of sensors, the detection range of
airborne magnetometers is commonly set as a fixed value in references regardless of the influences of environment noise,
target magnetic properties, and platform features in a classical model to detect airborne magnetic anomalies. As a
consequence, deviation in detection ability analysis is observed. In this study, a novel detection range model is proposed
on the basis of classic detection range models of airborne magnetometers. In this model, probability distribution is
applied, and the magnetic properties of targets and the environment noise properties of a moving submarine are
considered. The detection range model is also constructed by considering the distribution of the moving submarine during
detection. A cell-averaging greatest-of-constant false alarm rate test method is also used to calculate the detection range
of the model at a desired false alarm rate. The detection range model is then used to establish typical submarine search
probabilistic models. Results show that the model can be used to evaluate not only the effects of ambient magnetic noise
but also the moving and geomagnetic features of the target and airborne detection platform. The model can also be
utilized to display the actual operating range of sensor systems
