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An Anti-Intermittent Sampling Jamming Technique Utilizing the OTSU Algorithm of Random Orthogonal Sub-Pulses.

Authors :
Zhan, Haihong
Wang, Tao
Guo, Tai
Su, Xingde
Source :
Remote Sensing. Jun2023, Vol. 15 Issue 12, p3080. 25p.
Publication Year :
2023

Abstract

The utilization of intermittent sampling jamming can engender a lofty verisimilitude false target cluster that exhibits coherence with the transmitted signal. Such an assemblage bears the hallmarks of both suppression jamming and deceitful jamming, capable of inflicting substantial impairment upon the radar, potentially leading to its profound incapacitation. Henceforth, the precise discernment of the target and various forms of intermittent sampling jamming emerges as a novel endeavor. In response to this predicament, this paper posits a pulsed radar waveform featuring intra-pulse random orthogonal frequency modulation (FM) and inter-pulse phase coherence. This innovative approach not only presents formidable challenges for the jammer in acquiring radar waveform parameters, but also bolsters the radar's low probability of intercept (LPI), while maintaining the phase coherence of sub-pulses between pulses. Furthermore, based on this waveform, the characteristics of the intermittent sampling jamming signal and its differences from the target echo signal are analyzed in the time domain, frequency domain, time-frequency domain, and pulse compression domain. Building upon these findings, this paper proposes the sub-division algorithms for typical types of intermittent sampling jamming under this waveform: the full-pulses multi-level maximum inter-class variance and sub-pulses multi-level maximum inter-class variance anti-intermittent sampling jamming algorithms. Simulation analysis demonstrates that this waveform and the anti-jamming algorithms can accurately identify and effectively counteract different types of intermittent sampling jamming in typical scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
12
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
164702265
Full Text :
https://doi.org/10.3390/rs15123080