Pulse sorting method based on isomorphic sequence

Abstract

The invention provides a pulse sorting method based on an isomorphic sequence, and aims to solve the problem in detection of pulse groups which are practically submersed into a large quantity of pulse streams. The method comprises the following steps S1, acquiring a pulse repetition time interval sequence through first-order backward difference of the arrival time sequence of pulse streams, and quantizing the value of each element of the pulse repetition time interval sequence; S2, sieving the repetition substrings of the pulse repetition time interval sequence by using a suffix array and a maximum public prefix; S3, deleting shorter sub-strings from sub-strings having inclusion relations, and combining and jointing sub-strings having overlapping relations; S4, constructing a pulse stream arrival time difference matrix specific to the remaining pulse streams; S5, extracting a positive real number sequence of each line of the difference matrix to construct a pile of arrays, and sequencing the arrays to obtain a plurality of subsets; S6, searching for the sum of the subsets and a maximum common subsequence, and determining the position of a target pulse; S7, performing harmonic wave verification and pulse loss verification.

Description

Technical field [0001] The invention relates to a pulse sorting method based on isomorphic sequences and belongs to the field of signal processing. Background technique [0002] With the increasing complexity of the electromagnetic environment, how to sort out the signals of interest from the highly dense pulsed signal environment and to dig out the laws has always been a research hotspot in the fields of radar and sonar. Extracting a regular pulse group sequence is an important method for pulse sorting. The classical method of early pulse sorting was to perform statistical histogram analysis of pulse parameters (PRI). The histogram method was mainly used to analyze conventional pulse signals, which could not eliminate the influence of harmonics, and could not adapt to modern complex and changeable pulse types. The PRI transformation algorithm uses the phase factor to achieve the effect of suppressing the harmonics, but this method is more sensitive to the initial parameter sett...

AI Technical Summary

Problems solved by technology

The difference histogram and PRI spectrum peaks of these few pulse groups are very low, and the state transition probability is also very low, which cannot be clearly distinguished from the interference pulse

If pulse loss occurs in these pulse groups, the detection performance of the above algorithm will be lower

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