Radar emitter recognition based on cyclostationary signatures and sequential iterative least-square estimation

Radar emitter recognition plays an important role in electronic warfare (EW). Specific radar emitter recognition is the state-of-art technology of emitter recognition, which can recognize the different radar devices of the same type. It is a composite task that involves radar signal interception, modulation recognition, features extraction and classification. In this paper, first we study the unintentional modulation on pulse (UMOP) features of radar emitter. Then the iterative least-square method is introduced for estimation of the UMOP features. Because of the discriminatory capability and abundant information of cyclostationary signatures, the zero frequency slice of cyclic spectrum is used for specific radar emitter recognition. Based on these, the sequential iterative least-square (SILS) algorithm is proposed for the online recognition of radar emitters. Finally experiments on three simulation radars and eight actual intercepted radars with the same type verify the correctness and validity of the proposed method.

Research highlights
► The import principle, basis and development of SEI.
► Cyclostationary signatures analysis for radar UMOP.
► Online recognition based on sequential iterative least-square algorithm.