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Keywords = jamming general formula

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26 pages, 3614 KB  
Review
Overview of Radar Jamming Waveform Design
by Yu Pan, Didi Xie, Yurui Zhao, Xiang Wang and Zhitao Huang
Remote Sens. 2025, 17(7), 1218; https://doi.org/10.3390/rs17071218 - 29 Mar 2025
Cited by 10 | Viewed by 6985
Abstract
Radar jamming waveform design is a vital part of radar jamming. Over seven to eight decades of evolution, the field has transitioned from noise signal design to coherent jamming signal design, resulting in a multitude of complex jamming styles capable of achieving deceptive [...] Read more.
Radar jamming waveform design is a vital part of radar jamming. Over seven to eight decades of evolution, the field has transitioned from noise signal design to coherent jamming signal design, resulting in a multitude of complex jamming styles capable of achieving deceptive jamming, suppressive jamming, and smart noise jamming, which combines both deception and suppression. For the first time, this article establishes a general formula for unifying jamming waveform design. Building upon this foundation, we systematically categorize jamming techniques, and provide an in-depth summary of the corresponding principles and conduct comparative analysis of their effectiveness against different targets. Finally, we look forward in terms of future research directions in jamming waveform design, including quantifiable jamming effect evaluation indicators, combined jamming styles, and intelligent jamming waveform generation methods to address the continuous advancement of radar technology and the complexity and variability of the electromagnetic environment. In order to fill the gap in the literature by summarizing the current state of the field and highlighting key challenges and opportunities, this review provides a comprehensive overview of radar jamming waveform design, categorizes and compares different jamming techniques, and identifies future research directions. Full article
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22 pages, 4989 KB  
Article
Electro-Hydraulic Servo-Pumped Active Disturbance Rejection Control in Wind Turbines for Enhanced Safety and Accuracy
by Tiangui Zhang, Haohui Yu, Bo Yu, Chao Ai, Xiaoxiang Lou, Pengjie Xiang, Ruilin Li and Jianchen Li
Processes 2024, 12(5), 908; https://doi.org/10.3390/pr12050908 - 29 Apr 2024
Cited by 4 | Viewed by 2108
Abstract
Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to [...] Read more.
Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b0 (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b0 is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. Full article
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21 pages, 6451 KB  
Article
Online Sequential Extreme Learning Machine-Based Active Interference Activity Prediction for Cognitive Radar
by Shanshan Wang, Zheng Liu, Rong Xie and Lei Ran
Remote Sens. 2022, 14(12), 2737; https://doi.org/10.3390/rs14122737 - 7 Jun 2022
Cited by 1 | Viewed by 2892
Abstract
For anti-active-interference-oriented cognitive radar systems, the mismatch between the acquired and actual interference information may result in serious degradation of cognitive anti-active-interference performance. To yield more effective knowledge of the electromagnetic environment and eliminate the mismatch effect, the electromagnetic activity prediction technique, which [...] Read more.
For anti-active-interference-oriented cognitive radar systems, the mismatch between the acquired and actual interference information may result in serious degradation of cognitive anti-active-interference performance. To yield more effective knowledge of the electromagnetic environment and eliminate the mismatch effect, the electromagnetic activity prediction technique, which deduces future electromagnetic behaviors based on current observations, has received increasing attention. However, high computational complexities limit the application of conventional electromagnetic activity prediction methods in dynamic active interference prediction with high real-time requirements. In this paper, the online sequential extreme learning machine (OS-ELM)-based method, which is dedicated to high-efficiency active interference activity prediction, is proposed. The advancement includes two aspects. First, benefiting from the single-hidden-layer network structure and recursive-formula-based output weight updating, the proposed OS-ELM-based frequency prediction (OS-ELM-FP) and OS-ELM-based angle prediction (OS-ELM-AP) models can predict the interference state and update the prediction model parameters with much higher computational efficiency. Second, the better generalization performance enables the proposed method to achieve smaller interference activity prediction errors compared with conventional methods. Numerical examples and prediction results based on measured jamming data demonstrate the advantages of the proposed method. Full article
(This article belongs to the Special Issue Radar High-Speed Target Detection, Tracking, Imaging and Recognition)
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