scholarly journals Sparse Frequency Waveform Design for Radar-Embedded Communication

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Chaoyun Mai ◽  
Jinping Sun ◽  
Rui Zhou ◽  
Guohua Wang
Keyword(s):  
Waveform Design ◽  
Eigenvalue Decomposition ◽  
Covert Communication ◽  
Communication Signals ◽  
Power Spectral ◽  
Signal Error ◽  
Density Fitting ◽  
Low Probability ◽  
Simulation Results ◽  
Quasi Newton

According to the Tag application with function of covert communication, a method for sparse frequency waveform design based on radar-embedded communication is proposed. Firstly, sparse frequency waveforms are designed based on power spectral density fitting and quasi-Newton method. Secondly, the eigenvalue decomposition of the sparse frequency waveform sequence is used to get the dominant space. Finally the communication waveforms are designed through the projection of orthogonal pseudorandom vectors in the vertical subspace. Compared with the linear frequency modulation waveform, the sparse frequency waveform can further improve the bandwidth occupation of communication signals, thus achieving higher communication rate. A certain correlation exists between the reciprocally orthogonal communication signals samples and the sparse frequency waveform, which guarantees the low SER (signal error rate) and LPI (low probability of intercept). The simulation results verify the effectiveness of this method.

scholarly journals Orthogonal Waveform Design for Radar-Embedded Communications

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1107
Author(s):  
Jianqiu Xu ◽  
Baoguo Li ◽  
Zhitao Huang ◽  
Jing Lei
Keyword(s):  
Computational Complexity ◽  
Theoretical Analysis ◽  
Waveform Design ◽  
Covert Communication ◽  
Spectrum Utilization ◽  
Response Delay ◽  
Communication Reliability ◽  
Low Probability ◽  
Simulation Results ◽  
Low Probability Of Intercept

This paper focuses on the waveform design for a radar-embedded communication (REC) system which can achieve covert communication while improving the spectrum utilization. In order to solve the problem that the conventional embedded communication waveforms are not orthogonal, this paper proposes the orthogonal weighted-combining (OWC) strategy and the orthogonal dominant-projection (ODP) strategy. Furthermore, the OWC strategy can be broken into two strategies: constrained weighted-combining (CWC) strategy and improved weighted-combining (IWC) strategy. Theoretical analysis and simulation results have shown that these three strategies can dramatically improve communication reliability. Moreover, the performance of the strategies mentioned above has been assessed by the low probability of intercept (LPI) metric. Comparing to the traditional strategies, the IWC strategy shows better LPI performance while the CWC strategy and ODP strategy remain unchanged. Additionally, the ODP strategy can also reduce computational complexity and response delay, which is rather important in the REC system. Any of the three strategies can be selected in accordance with the needs of the application scenario.

scholarly journals Adaptive Radar Waveform Design Based on Weighted MI and the Difference of Two Mutual Information Metrics

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fengming Xin ◽  
Bin Wang ◽  
Shumin Li ◽  
Xin Song ◽  
Chi-Hsu Wang
Keyword(s):  
Mutual Information ◽  
Impulse Response ◽  
Waveform Design ◽  
Adaptive Radar ◽  
Trade Offs ◽  
Power Spectral ◽  
Simulation Results ◽  
The Difference ◽  
Transmitted Waveform ◽  
Information Metrics

This study deals with the problem of radar waveform design based on the weighted mutual information (MI) and the difference of two mutual information metrics (DMI) in signal-dependent interference. Since the target and clutter information are included in the received signal at the beginning of the design, DMI-based waveform is designed according to the following criterion: maximizing the MI between the received signal and target impulse response while minimizing the MI between the received signal and the clutter impulse response. This criterion is equivalent to maximizing the difference between the first MI and the second MI. Then maximizing the difference of two types of MI is used as the objective function, and the optimization model with the transmitted waveform energy constraint is established. In order to solve it, we resort to maximum marginal allocation (MMA) method to find the DMI-based waveform. Since DMI-based waveform does not allocate energy to the frequency band where the clutter power spectral density (PSD) is greater than the target PSD, we propose to weight the MI-based waveform and DMI-based waveform to synthesize the final optimal waveform. It could provide different trade-offs between two types of MI. Simulation results show the proposed algorithm is valid.

scholarly journals A New Shaped Waveform Design Scheme for Radar Embedded Communication

2018 ◽  
Vol 173 ◽  
pp. 02039 ◽  
Author(s):  
Shan He ◽  
Baoguo Li ◽  
Jing Lei ◽  
Hua Yan
Keyword(s):  
Theoretical Analysis ◽  
Waveform Design ◽  
Correlation Filter ◽  
Eigenvalue Decomposition ◽  
Feature Vectors ◽  
Design Scheme

In order to improve the covertness of radar embedded communication based on the eigenvalue decomposition radar embedded communication waveform design scheme, a new waveform design scheme that combines the idea of shaped design is constructed. In this paper, the background and concept of radar embedded communication are introduced in detail. Three existing waveform design schemes are analyzed. Using de-correlation filter receivers, a weighted waveform design scheme for shaped non-dominant subspace feature vectors is constructed and analyzed. The communication covertness and reliability is illustrated. Both the theoretical analysis and the simulation show that this scheme improves the covertness of communication.

scholarly journals Generalized Givens Rotations Applied to Complex Joint Eigenvalue Decomposition

2021 ◽  
Vol 1 (1) ◽  
pp. 58-62
Author(s):  
Ammar Mesloub
Keyword(s):  
Complex Case ◽  
Eigenvalue Decomposition ◽  
Real Case ◽  
Joint Diagonalization ◽  
The Real ◽  
Givens Rotation ◽  
Givens Rotations ◽  
Simulation Results ◽  
Complex Joint

This paper shows the different ways of using generalized Givens rotations in complex joint eigenvaluedecomposition (JEVD) problem. It presents the different schemes of generalized Givens rotation, justifies the introducedapproximations and focuses on the process of extending an algorithm developed for real JEVD to the complex JEVD.Several Joint Diagonalization problem use generalized Givens rotations to achieve the solution, many algorithmsdeveloped in the real case exist in the literature and are not generalized to the complex case. Hence, we show herein asimple and not trivial way to get the complex case from the real one. Simulation results are provided to highlight theeffectiveness and behaviour of the proposed techniques for different scenarios.

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