Robust Radar Signal Sorting via Augmented Planar Transform

Radar signal sorting (RSS) is a key technology in electronic support measures systems. However, existing sorting methods utilizing pulse repetition interval (PRI) exhibit insufficient fault tolerance in complex electromagnetic environments with missing pulses, false alarm pulses, and coexisting multiple PRI modulation modes, thereby limiting their practical applications. This letter proposes a robust PRI-based sorting method via augmented planar transform. The method maps time-of-arrival (TOA) sequences to a two-dimensional feature plane, exploiting distribution characteristics of different PRI modulation modes in the planar domain. Information entropy theory and local extremum detection are employed to determine the PRI candidate set, while a supplementary identification mechanism handles jittered modulations. A suppression strategy is designed to eliminate subharmonic interference. The PRI sequence extraction and modulation mode identification are achieved through planar feature analysis. Experimental results demonstrate that the proposed method correctly identifies radar emitter modulation modes under non-ideal conditions, maintaining a sorting accuracy above 97% under missing pulse rate ranging from 5% to 40% with a 10% false alarm pulse rate, providing an effective approach for RSS in complex environments.