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The structure design and switching regulation of pulse groups in multi‐function radars (MFRs) are closely related to the work mode. The sequential extraction and recognition of MFR pulse group structure is a fundamental task to analysing and interpreting the work modes and behaviour intentions of an MFR. In this study, the temporal structure of MFR pulse group is expressed hierarchically, which is intensively modelled based on regular grammar. Besides, a corresponding hierarchical automaton is established to sequentially extract and recognise the MFR pulse group structure in pulse train. The hierarchical automaton used for pulse group recognition has a two‐layer structure. The bottom layer of the hierarchical automaton realises the sequential input of pulses and recognition of pulse subgroups, and the sequential input of pulse subgroups and recognition of pulse groups are realised at the top layer. The simulation results demonstrate that the proposed method performs satisfyingly in recognising the pulse group structure and is robust to not only pulse noises but also to the emitter number and pulse group scale. [ABSTRACT FROM AUTHOR]

Signals of radars with fixed, stagger and other conventional pulse repetition intervals (PRI) occupy a large proportion in most radar reconnaissance datasets. Automatic and accurate reconstruction of the PRI patterns of these radars is an important task in realizing intelligent processing of radar reconnaissance data. In order to address this problem, this article proposes an automatic method based on the extraction and extension of frequent differential time‐of‐arrival (DTOA) items, which can be combined with other pulse parameters such as pulse width. The values and ordering of the frequent items are determined to reconstruct a complete PRI cycle, and the radar pulses are deinterleaved at the same time as a by‐product. Compared with the commonly used one‐dimensional radar reconnaissance parameters such as framework PRI or typical PRI set, the reconstructed PRI pattern contains more information about radar operational modes and can be applied to realize online and parallel pulse deinterleaving and more accurate radar type classification. [ABSTRACT FROM AUTHOR]