scholarly journals A Nonlinear Fingerprint-Level Radar Simulation Modeling Method for Specific Emitter Identification

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1030
Author(s):  
Peng Man ◽  
Chibiao Ding ◽  
Wenjuan Ren ◽  
Guangluan Xu
Keyword(s):  
Simulation Modeling ◽  
Modeling Method ◽  
Fingerprint Identification ◽  
Radar Signal ◽  
Mechanism Analysis ◽  
Experimental Conditions ◽  
Electronic Warfare ◽  
Emitter System ◽  
Military Systems ◽  
Working Parameters

With the development of information technology for modern military confrontations, radar emitter fingerprint identification has become a hot and difficult topic in the field of electronic warfare, especially in the field of electronic reconnaissance. Owing to the confidentiality of military systems, most of the existing studies use simulation data for radar emitter fingerprint identification experiments and analysis. However, most of the existing modeling methods focus on the mechanism analysis of the nonlinear fingerprint characteristics of a single independent component. Its main disadvantage is that it can only represent the nonlinear fingerprint characteristics of some components in the radar emitter system but cannot fully reflect the nonlinear fingerprint characteristics of the whole radar emitter system. In this paper, a nonlinear fingerprint-level radar simulation modeling method is proposed. In contrast to the previous single component modeling method, the systematic nonlinear characteristic modeling method of this model can provide individual radar signal data under different modulation modes and working parameters, and provide experimental conditions for data support and theoretical analysis of radar emitter fingerprint identification.

scholarly journals Estimating the Instantaneous Frequency of Linear and Nonlinear Frequency Modulated Radar Signals—A Comparative Study

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2840
Author(s):  
Hubert Milczarek ◽  
Czesław Leśnik ◽  
Igor Djurović ◽  
Adam Kawalec
Keyword(s):  
Instantaneous Frequency ◽  
Early Warning Systems ◽  
Vital Role ◽  
Estimation Methods ◽  
Radar Signal ◽  
Nonlinear Frequency ◽  
Modulation Recognition ◽  
Electronic Warfare ◽  
Time Frequency ◽  
Radar Signals

Automatic modulation recognition plays a vital role in electronic warfare. Modern electronic intelligence and electronic support measures systems are able to automatically distinguish the modulation type of an intercepted radar signal by means of real-time intra-pulse analysis. This extra information can facilitate deinterleaving process as well as be utilized in early warning systems or give better insight into the performance of hostile radars. Existing modulation recognition algorithms usually extract signal features from one of the rudimentary waveform characteristics, namely instantaneous frequency (IF). Currently, there are a small number of studies concerning IF estimation methods, specifically for radar signals, whereas estimator accuracy may adversely affect the performance of the whole classification process. In this paper, five popular methods of evaluating the IF–law of frequency modulated radar signals are compared. The considered algorithms incorporate the two most prevalent estimation techniques, i.e., phase finite differences and time-frequency representations. The novel approach based on the generalized quasi-maximum likelihood (QML) method is also proposed. The results of simulation experiments show that the proposed QML estimator is significantly more accurate than the other considered techniques. Furthermore, for the first time in the publicly available literature, multipath influence on IF estimates has been investigated.

scholarly journals Computer Network Simulation Modeling Based on Object Oriented Petri Net

2016 ◽  
Vol 12 (02) ◽  
pp. 25
Author(s):  
Xinhua Chen ◽  
Ya-ni Sun
Keyword(s):  
Petri Net ◽  
Simulation Modeling ◽  
Computer Network ◽  
Network Simulation ◽  
Object Oriented ◽  
Modeling Method ◽  
Model Based ◽  
Valid Method

This paper first briefly introduces the Petri net, and then studied in detail according to the selected object-oriented Petri net modeling method. This paper improve the object-oriented Petri net modeling method, and study the modeling and operation steps in details. Finally this paper build a computer network TCP/IP protocol model based on the object oriented Petri net. The model prove to be a good simulation to the computer network and the improved modeling method is also a valid method for further object oriented Petri net modeling.

scholarly journals Simulation on Cooperative Changeover of Production Team Using Hybrid Modeling Method

Algorithms ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 204
Author(s):  
Xiaodong Zhang ◽  
Yiqi Wang ◽  
Bingcun Xu
Keyword(s):  
Simulation Modeling ◽  
Simulation Method ◽  
Modeling Method ◽  
Hybrid Modeling ◽  
Test Results ◽  
Multi Agent Systems ◽  
Discrete Events ◽  
Cooperative Strategies ◽  
Multi Agent ◽  
Production Cell

In the multi-variety and small-quantity manufacturing environment, changeover operation occurs frequently, and cooperative changeover method is often used as a way to shorten the changeover time and balance the workload. However, more workers and tasks will be affected by cooperative changeover. As such, the effectiveness of the cooperative changeover is dependent on other factors, such as the scope of cooperation and the proportion of newly introduced products. For this reason, this paper proposes a hybrid modeling method to support the simulation study of the production team's cooperative changeover strategies under various environments. Firstly, a hybrid simulation modeling method consisting of multi-agent systems and discrete events is introduced. Secondly, according to the scope of cooperation, this paper puts forward four kinds of cooperative changeover strategies. This paper also describes the cooperative line-changing behavior of operators. Finally, based on the changeover strategies, the proposed simulation method is applied to a production cell. Four production scenarios are considered according to the proportion of newly introduced part. The performance of various cooperative strategies in different production scenarios is simulated, and the statistical test results show that the optimal or satisfactory strategy can be determined in each production scenario. Additionally, the effectiveness and practicability of the proposed modeling method are verified.

scholarly journals LPI Radar Waveform Recognition Based on CNN and TPOT

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 725 ◽  
Author(s):  
Jian Wan ◽  
Xin Yu ◽  
Qiang Guo
Keyword(s):  
Signal To Noise Ratio ◽  
Recognition Rate ◽  
Recognition System ◽  
Radar Signal ◽  
Automatic Identification ◽  
Identification System ◽  
Electronic Warfare ◽  
Time Frequency ◽  
Barker Codes ◽  
Intelligence Support

The electronic reconnaissance system is the operational guarantee and premise of electronic warfare. It is an important tool for intercepting radar signals and providing intelligence support for sensing the battlefield situation. In this paper, a radar waveform automatic identification system for detecting, tracking and locating low probability interception (LPI) radar is studied. The recognition system can recognize 12 different radar waveform: binary phase shift keying (Barker codes modulation), linear frequency modulation (LFM), Costas codes, polytime codes (T1, T2, T3, and T4), and polyphase codes (comprising Frank, P1, P2, P3 and P4). First, the system performs time–frequency transform on the LPI radar signal to obtain a two-dimensional time–frequency image. Then, the time–frequency image is preprocessed (binarization and size conversion). The preprocessed time–frequency image is then sent to the convolutional neural network (CNN) for training. After the training is completed, the features of the fully connected layer are extracted. Finally, the feature is sent to the tree structure-based machine learning process optimization (TPOT) classifier to realize offline training and online recognition. The experimental results show that the overall recognition rate of the system reaches 94.42% when the signal-to-noise ratio (SNR) is −4 dB.

Discrete Electronic Warfare Signal Processing using Compressed Sensing Based on Random Modulator Pre-Integrator

2015 ◽  
Vol 65 (6) ◽  
pp. 472 ◽  
Author(s):  
M. Sreenivasa Rao ◽  
Chandan C. Mishra ◽  
K. Krishna Naik ◽  
K. Maheshwara Reddy
Keyword(s):  
Signal Processing ◽  
Input Signal ◽  
High Speed ◽  
Traditional Approach ◽  
Ultra Wideband ◽  
Radar Signal ◽  
Electromagnetic Spectrum ◽  
Electronic Warfare ◽  
High Speed Adc ◽  
Detection Of Signals

Electronic warfare receiver works in the wide electromagnetic spectrum in dense radar signal environment. Current trends in radar systems are ultra wideband and low probability of intercept radar technology. Detection of signals from various radar stations is a concern. Performance and probability of intercept are mainly dependent on high speed ADC technology. The sampling and reconstruction functions have to be optimized to capture incoming signals at the receiver to extract characteristics of the radar signal. The compressive sampling of the input signal with orthonormal base vectors, projecting the basis in the union of subspaces and recovery through convex optimisation techniques is the current traditional approach. Modern trends in signal processing suggest the random modulator pre-integrator (RMPI), which sample the input signal at information rate non-adaptively and recovery by the processing of discrete and finite vectors. Analysis of RMPI theory, application to EW receiver, simulation and recovery of EW receiver signals are discussed.

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