Pulse interference method against PRI sorting

Hao, Nan; Peng, Shirui; Yu, Jia’ao; Wang, Xiaoyan

doi:10.1049/joe.2019.0398

Cited by 10 publications

(10 citation statements)

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“…The center values of the two radar signals are in the same order of magnitude Considering that the center values of the two radar signals are in the same order of magnitude, T 10 ≈ T 20 (19) Therefore, Equation ( 18) is transformed into:…”

Section: The Difference Between the Center Values Of Two Groups' Rada...mentioning

confidence: 99%

“…In the field of anti-sorting, jitter signal is also considered as one of the better antisorting signals [19]. This section takes PRI jitter signal as an example to compare its sorting resistance with that designed based on PRI estimation sorting failure principle.…”

Section: Comparison With Pri Jitter Signal Sorting Experimentsmentioning

confidence: 99%

“…Second, jitter is added to the PRI of the pulse signal, and each pulse has a different PRI. Thus, it is difficult for the enemy intercept receiver to sort radar signals [17,19,20]. Although the methods above have been effective, the stability of the anti-sorting performance of the designed signals needs to be further verified.…”

Section: Introductionmentioning

confidence: 99%

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Research on the Sequential Difference Histogram Failure Principle Applied to the Signal Design of Radio Frequency Stealth Radar

et al. 2022

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As electronic warfare becomes the core of modern warfare, radio frequency (RF) stealth radar is becoming the focus of modern electronic warfare. The anti-sorting strategy of RF stealth radar is a new effective method of the anti-enemy electronic reconnaissance system. Hence, research on the failure mechanism of sorting algorithms has become the cornerstone of anti-sorting technology. In this paper, the mechanism of algorithm failure is studied because the SDIF algorithm is widely used in engineering practice throughout the whole workflow of the sequential difference histogram (SDIF) algorithm, from the estimation of pulse repetition interval (PRI) destroyed by the algorithm and algorithm analysis to the staggered signal. Firstly, the working steps of the SDIF histogram sorting algorithm are considered. Key steps of signal sorting by the algorithm are analyzed, and the failure principle of the sorting algorithm is proposed. It is pointed out that if the PRI signal center value of the two groups of radars is within the tolerance range of the sorting algorithm, when the two signal center values are not of the same order of magnitude, the difference is more than 10 times, and the signal variation is less than 30% of the center value, the sorting error of the algorithm for the radar signal is at least 25%. The sorting algorithm fails to sort signals. At the same time, for the sorting failure of the staggered signal, the sub-PRI design formula of the staggered signal is proposed, and the staggered signal satisfying the design formula can make the sorting algorithm invalid. Finally, the correctness of the SDIF failure principle is further verified by formula derivation, signal design simulation and experiment. The principle of sorting failure provides theoretical support and foundation for the design of anti-sorting RF stealth signal. The principle of sorting failure makes up for the shortcomings of random signal design and improves the design efficiency of RF stealth signal.

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Section: The Difference Between the Center Values Of Two Groups' Rada...mentioning

confidence: 99%

Section: Comparison With Pri Jitter Signal Sorting Experimentsmentioning

confidence: 99%

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Research on the Sequential Difference Histogram Failure Principle Applied to the Signal Design of Radio Frequency Stealth Radar

et al. 2022

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“…As a result, the deinterleaving of pulse trains has become an increasingly challenging task [1]. In addition, artificial signal distortion, such as the jamming pulse in [2], is also being employed for anti-electronic warfare.…”

Section: Introductionmentioning

confidence: 99%

A Unified Method for Deinterleaving and PRI Modulation Recognition of Radar Pulses Based on Deep Neural Networks

Han

Park

2021

IEEE Access

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In the modern electronic warfare signal environment, multiple radar signals of high density are mixed and received, and separating them into signals for each emitter is an essential step for emitter identification. Each radar has its own pulse repetition interval (PRI), which is a key parameter for deinterleaving pulse trains. The PRI is modulated in various forms depending on the purpose of the radar operation, and analyzing the mean PRI and the modulation type of PRI is the core of electronic warfare signal processing. Many existing papers have tried separate independent approaches for deinterleaving and for PRI modulation recognition. However, many distortions are unintentionally generated in the process of extracting the pulse train using the PRI estimated through deinterleaving for the PRI modulation recognition. This degrades the the modulation recognition performance. In this paper, we propose a unified method for the deinterleaving and PRI modulation recognition of radar pulses using deep learning-based multitasking learning. The simulation results demonstrate the good performance of the proposed method for deinterleaving and modulation recognition, compared to the conventional method, and prove that the proposed method is robust in noisy radar signal environments.

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“…With the continuous development of electronic countermeasures, the signal density in the electromagnetic environment has reached a level of 10 million per second. The signal forms adopted by military radars are increasingly complex [2]. The waveforms change simultaneously in both the time and frequency domains, such as frequency‐agile radar, the agility of pulse parameters can be utilised to destroy the similarity between the parameters of the same detector used in deinterleaving.…”

Section: Introductionmentioning

confidence: 99%