Multistatic target recognition in real operational scenarios

The ability to recognize quickly and reliably non cooperative targets is a primary issue in modern radar systems. The use of a multistatic radar has already been demonstrated to improve sensibly the recognition capacity of a radar system, through the exploitation of its inherent spatial diversity, given by the presence of multiple observation channels. In this paper, we evaluate the performance of a multistatic radar, which uses a correlation based classification algorithm for each channel of the multistatic system and a suitable fusion rule that combines the decisions coming from different channels. This fusion rule, referred as SELX (SELection of tX and rX), takes into account that each channel decision is influenced by a number of parameters, including the relative positions between target, transmitter and receiver. As a consequence, a suitable selection is made to favour the channels which show better performance with respect to the other ones. The performance evaluation of the SELX rule is carried out and compared with a straight method that takes into account only the SNR. In both the cases the performance are carried out by considering complex targets, each of them modelled as a set of independent scatterers, according to type, form and structure of the target. Four different types of targets are modelled, which emulate real targets. The evaluation demonstrates the ability to classify the targets by means of our methods and algorithms, with a very high probability of correct classification.