Abstract
We propose an algorithm based on the knowledge of training sequences to obtain an asymptotically unbiased estimator of the Radio Frequency (RF) front-end nonlinearity to perform Specific Emitter Identification (SEI). In most SEI literature Inter Symbol Interference (ISI) is seldom considered; however, it is a major limiting factor in SEI systems and should be suppressed to achieve reliable identification. In this paper we develop a nonlinearity estimator that can overcome ISI and provide reliable estimation. The method is shown to achieve nonlinearity estimation and radio emitter identification over an empirical indoor channel model using an Orthogonal Frequency Division Multiplexing (OFDM) system.
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