Multi-function radar emitter identification based on stochastic syntax-directed translation schema

Abstract

To cope with the problem of emitter identification caused by the radar words’ uncertainty of measured multi-function radar emitters, this paper proposes a new identification method based on stochastic syntax-directed translation schema (SSDTS). This method, which is deduced from the syntactic modeling of multi-function radars, considers the probabilities of radar phrases appearance in different radar modes as well as the probabilities of radar word errors occurrence in different radar phrases. It concludes that the proposed method can not only correct the defective radar words by using the stochastic translation schema, but also identify the real radar phrases and working modes of measured emitters concurrently. Furthermore, a number of simulations are presented to demonstrate the identification capability and adaptability of the SSDTS algorithm. The results show that even under the condition of the defective radar words distorted by noise, the proposed algorithm can infer the phrases, work modes and types of measured emitters correctly.