Deep Multimodal Subspace Interactive Mutual Network for Specific Emitter Identification

Abstract

This paper investigates the problem of specific emitter identification (SEI), i.e. radar emitter fingerprint or individual emitter identification, which first measures the emitter-specific differences caused by radar's nonlinearities, e.g. mixer, power amplifiers, transmitter, and then makes a decision. In this paper, the SEI problem is considered in the single-modal, dual-modal and multi-modal scenarios, respectively. First, a multi-modal subspace interactive mutual unit is proposed to perform information interaction between radar signal and its multiple transformations. Based on this, a data-driven multi-modal subspace interactive mutual network (MSIMN) is then built to solve the SEI problem. Extensive experiment results demonstrate that the proposed algorithm achieves superior identification performance on the airplane measured data.