Application of three-dimensional filtering to moving target detection

To detect a stationary target immersed in an optically observed scene, the standard approach is to use integration to separate the target energy from the background clutter. It is pointed out that when the target is nonstationary and moves with a fixed velocity relative to the clutter, the procedure for integrating the target signal is no longer obvious. It is shown here that the problem of tracking a target having a fixed velocity can be generalized and treated in accordance with three-dimensional filter theory. The target detection problem thus reduces to one of finding optimal three-dimensional filters in the three-dimensional transform domain and processing the observed scene via this filtering. The design of these filters is described, with allowance made for the target, clutter, and optical detection models. The performance is computed for a basic clutter model, demonstrating the effective increase in detectability as a function of the target velocity.