{'fraction_non_alphanumeric': 0.020939086294416244, 'fraction_numerical': 0.005076142131979695, 'mean_word_length': 5.598326359832636, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Specific Emitter Identification Using IMF-DNA with a Joint Feature Selection Algorithm

Specific emitter identification (SEI) is a technique to distinguish among different emitters of the same type using weak individual characteristics instead of conventional modulation parameters. The biggest challenge in SEI is to not only distinguish the different emitters with close modulation parameters but also to identify a specific emitter when its modulation parameters change significantly. For this paper, individual differences in pulse envelopes were investigated and four types of pulse envelopes were modeled. To exploit the individual features along with the pulse envelope for the identification of a specific emitter, an intrinsic mode function distinct native attribute (IMF-DNA) feature extraction algorithm and a joint feature selection (JFS) algorithm were proposed, which together constitute the final proposed SEI technique. Compared with four other feature selection methods, the proposed feature selection algorithm performed better for finding the most useful features for classification, which greatly helps in the reduction of feature dimension. Compared with radio frequency DNA (RF-DNA), IMF-DNA had a far superior correct emitter identification rate under similar conditions. A real data verification method was developed to verify the performance of IMF-DNA for specific emitter identification. The method achieved a correct identification rate of 85.3% at a sampling rate of 200 MHz and had an estimated signal-to-noise ratio (SNR) of approximately 10 dB.