Complex system radar signal grade correlating, clustering and sorting method

Abstract

The invention relates to a complex system radar signal grade correlating, clustering and sorting method. The method comprises the following steps: through the study and analysis on the characteristics of the radiation source signal of the existing complex radar system, firstly, using a pulse width domain and frequency domain hierarchical clustering method to classify the different radar signals; secondly, using the PRI algorithm of the small box width adaptive pulse flow density to extract the repetition period parameters; pre-estimating the pulse flow density of the post-clustered signal; using the small box width of the adaptive pulse flow density to detect the signal; performing PRI transform and suppressing harmonic waves; and extracting the repetition period's characteristic parameters from the detection result. This method takes into account the detection capability for radar signal and the identification ability for repetition period, and improves the accuracy of clustering. It also has a good detection and characteristic parameter extraction performance for complex system radar signals such as multi-staggered radar signals and large-scale jitter radar signals.

Description

technical field [0001] The invention is applied in the field of signal sorting, and in particular relates to a level-associated clustering sorting method for complex system radar signals. Background technique [0002] The characteristics of the modern electronic countermeasure signal environment are high signal density, complex and changeable waveforms, wide operating frequency bands and partial overlaps, dense signals in the time domain and increasingly serious overlaps, and the signals arriving at the input of the radar reconnaissance system are random pulse streams . In addition, there is a lot of noise in the transmission and reception of the radar emitter signal, and the SNR changes greatly, which greatly increases the difficulty of sorting and processing. The above characteristics greatly destroy the regularity of signals used in signal sorting and identification, which greatly affects the interception probability of radar reconnaissance systems. The time-domain modu...

AI Technical Summary

Problems solved by technology

Clustering traditional radar emitter signal sorting model parameters in the pulse width domain and frequency domain does not fully refer to the working principle and parameter distribution of active radar. Concentrated convergence and other characteristics, which may lead to mistakenly clustering several different radiation sources into one category or misclassifying a radiation source into several categories, which affects the subsequent time-domain clustering input; traditional PRI in time-domain clustering Sorting uses a small box with a fixed width. For high-repetition frequency signals, when the stagger interval is smaller than the width of the small box, it is impossible to distinguish sub-periods; Statistics of the staggered value; for the jitter and slip signals, the detection probability is very low due to the large distribution range of the repetition period

Only relying on adjusting the width of the small box and the detection threshold can no longer adapt to the current complex system radar signal

Images