Performance analysis of an ISAR contrast-based autofocusing algorithm using real data

The ISAR imaging technique is a well consolidated method for target image reconstruction. One of the main critical steps for ISAR is image focusing. This operation consists of removing from the received signal a nonlinear phase term due to the motion of the target. As the target motion is not a priori known, motion parameters are typically estimated from the received data by means of autofocusing techniques. The novel contrast based autofocusing technique (CBAT) has already been proposed by the authors. The paper describes tests of CBAT on real data and compares it to a classic autofocusing technique, namely the "hot-spot" or prominent point processing (PPP) technique. In order to test also the flexibility of the technique, two types of targets with different motion characteristics have been selected, specifically, a "bulk loader" ship and a Boeing 737 airplane. The CBAT performance has been evaluated by comparing the ISAR images reconstructed by means of a simple range-Doppler technique to the images obtained by means of the PPP technique.