The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a c...The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a certain model with certain regularity,the FH frequency is thus predictable.In this paper,we investigate the FH frequency reconnais-sance and prediction of a non-cooperative communi-cation network by effective FH signal detection,time-frequency(TF)analysis,wavelet detection and fre-quency estimation.With the intercepted massive FH signal data,long short-term memory(LSTM)neural network model is constructed for FH frequency pre-diction.Simulation results show that our parameter es-timation methods could estimate frequency accurately in the presence of certain noise.Moreover,the LSTM-based scheme can effectively predict FH frequency and frequency interval.展开更多
Frequency-hopping(FH) technique is widely used in high-secure communications by exploiting its capabilities of mitigating interference and confidentiality. However, electronic attacks in wireless systems become more a...Frequency-hopping(FH) technique is widely used in high-secure communications by exploiting its capabilities of mitigating interference and confidentiality. However, electronic attacks in wireless systems become more and more rigorous, which poses huge challenges to the use of the number theory based and chaos theory assisted sequences. The structure of the FH sequence directly affects the performance of FH communication systems. In this paper, the novel FH sequence generation scheme is proposed with the aid of the so-called Government Standard(GOST) algorithm, which achieves a promising balance between efficiency and security. Moreover, the security performance of the proposed algorithm is analyzed, which reveals that it is more resistant to impossible differential attacks than the widely-used Data Encryption Standard(DES) algorithm. The numerical results show that the FH sequences generated by the GOST algorithm significantly outperform the ones generated by the DES algorithm and chaotic theory in terms of the randomness and complexity.展开更多
An signal noise ratio( SNR) adaptive sorting algorithm using the time-frequency( TF)sparsity of frequency-hopping( FH) signal is proposed in this paper. Firstly,the Gabor transformation is used as TF transformation in...An signal noise ratio( SNR) adaptive sorting algorithm using the time-frequency( TF)sparsity of frequency-hopping( FH) signal is proposed in this paper. Firstly,the Gabor transformation is used as TF transformation in the system and a sorting model is established under undetermined condition; then the SNR adaptive pivot threshold setting method is used to find the TF single source. The mixed matrix is estimated according to the TF matrix of single source. Lastly,signal sorting is realized through improved subspace projection combined with relative power deviation of source. Theoretical analysis and simulation results showthat this algorithm has good effectiveness and performance.展开更多
文摘The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a certain model with certain regularity,the FH frequency is thus predictable.In this paper,we investigate the FH frequency reconnais-sance and prediction of a non-cooperative communi-cation network by effective FH signal detection,time-frequency(TF)analysis,wavelet detection and fre-quency estimation.With the intercepted massive FH signal data,long short-term memory(LSTM)neural network model is constructed for FH frequency pre-diction.Simulation results show that our parameter es-timation methods could estimate frequency accurately in the presence of certain noise.Moreover,the LSTM-based scheme can effectively predict FH frequency and frequency interval.
基金supported in part by the National Natural Science Foundation of China (No.61631015 and 61501354)
文摘Frequency-hopping(FH) technique is widely used in high-secure communications by exploiting its capabilities of mitigating interference and confidentiality. However, electronic attacks in wireless systems become more and more rigorous, which poses huge challenges to the use of the number theory based and chaos theory assisted sequences. The structure of the FH sequence directly affects the performance of FH communication systems. In this paper, the novel FH sequence generation scheme is proposed with the aid of the so-called Government Standard(GOST) algorithm, which achieves a promising balance between efficiency and security. Moreover, the security performance of the proposed algorithm is analyzed, which reveals that it is more resistant to impossible differential attacks than the widely-used Data Encryption Standard(DES) algorithm. The numerical results show that the FH sequences generated by the GOST algorithm significantly outperform the ones generated by the DES algorithm and chaotic theory in terms of the randomness and complexity.
基金Supported by the National Natural Science Foundation of China(64601500)
文摘An signal noise ratio( SNR) adaptive sorting algorithm using the time-frequency( TF)sparsity of frequency-hopping( FH) signal is proposed in this paper. Firstly,the Gabor transformation is used as TF transformation in the system and a sorting model is established under undetermined condition; then the SNR adaptive pivot threshold setting method is used to find the TF single source. The mixed matrix is estimated according to the TF matrix of single source. Lastly,signal sorting is realized through improved subspace projection combined with relative power deviation of source. Theoretical analysis and simulation results showthat this algorithm has good effectiveness and performance.
