Low sidelobe robust imaging in random frequency-hopping wideband radar based on compressed sensing

High resolution range imaging with correlation processing suffers from high sidelobe pedestal in random frequency-hopping wideband radar. After the factors which affect the sidelobe pedestal being analyzed, a compressed sensing based algorithm for high resolution range imaging and a new minimized ll-norm criterion for motion compensation are proposed. The random hopping of the transmitted carrier frequency is converted to restricted isometry property of the observing matrix. Then practical problems of imaging model solution and signal parameter design are resolved. Due to the particularity of the proposed algorithm, two new indicators of range profile, i.e., average signal to sidelobe ratio and local similarity, are defined. The chamber measured data are adopted to testify the validity of the proposed algorithm, and simulations are performed to analyze the precision of velocity measurement as well as the performance of motion compensation. The simulation results show that the proposed algorithm has such advantages as high precision velocity measurement, low sidelobe and short period imaging, which ensure robust imaging for moving targets when signal-to-noise ratio is above 10 dB.

Frequency-Hopping Frequency Reconnaissance and Prediction for Non-cooperative Communication Network

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.

A NEW METHOD OF FREQUENCY-HOPPING(FH) SIGNAL DETECTION

A new Frequency-Hopping(FH) signal detection method is proposed.Different from pre-vious methods which need to monitor the total band,it can monitor part of the band and decrease the range of the bandwidth.According to this method,a new detection model is set and the computation formulas of the detection probability and false-alarm probability are given.The parameters of a VHF radio are used to prove the validity of the method.Simulation results show that this method can de-crease the range of the bandwidth and detect the FH signal with some penalty on the SNR and signal loss.

New sets of low-hit-zone frequency-hopping sequence with optimal maximum periodic partial Hamming correlation

Recently, Chung et al. gave a general method to construct frequency-hopping sequence set(FHS set) with low-hit-zone(LHZ FHS set) by the Cartesian product. In their paper, Theorems 5 and 8 claim that k FHS sets whose maximum periodic Hamming correlation is 0 at the origin result in an LHZ FHS set based on the Cartesian product, and Proposition 4 presented an upper bound of the maximum periodic Hamming correlation of FHSs. However, their statements are imperfect or incorrect. In this paper, we give counterexamples and make corrections to them. Furthermore, based on the Cartesian product, we construct two classes of LHZ FHS sets with optimal maximum periodic partial Hamming correlation property. It is shown that new FHS sets are optimal by the maximum periodic partial Hamming correlation bound of LHZ FHS set.

Frequency-hopping transmitter fingerprint feature recognition with kernel projection and joint representation

Frequency-hopping(FH)is one of the commonly used spread spectrum techniques that finds wide applications in communications and radar systems because of its inherent capability of low interception,good confidentiality,and strong antiinterference.However,non-cooperation FH transmitter classification is a significant and challenging issue for FH transmitter fingerprint feature recognition,since it not only is sensitive to noise but also has non-linear,non-Gaussian,and non-stability characteristics,which make it difficult to guarantee the classification in the original signal space.Some existing classifiers,such as the sparse representation classifier(SRC),generally use an individual representation rather than all the samples to classify the test data,which over-emphasizes sparsity but ignores the collaborative relationship among the given set of samples.To address these problems,we propose a novel classifier,called the kernel joint representation classifier(KJRC),for FH transmitter fingerprint feature recognition,by integrating kernel projection,collaborative feature representation,and classifier learning into a joint framework.Extensive experiments on real-world FH signals demonstrate the effectiveness of the proposed method in comparison with several state-of-the-art recognition methods.

Interference analysis and improvement of capacity reduction for FHSS networks in WPAN application environment

The coexistence between Bluetooth system and IEEE 802.11 frequency hoppingspread spectrum (FHSS) equipment is analyzed. Based on the capacity formulae and system simulation,the inter-affection between these networks is compared. A fragment adaptive solution of packetpayload length is presented, which can be used to improve the capacity reduction of IEEE 802.11 FHSSnetwork. Analysis results show that the IEEE 802.11 WLAN standard with its inherent mechanismsupports this fragment length adaptive algorithm. With the increasing of Bluetooth interferingnetworks, this adaptive solution can effectively relieve capacity decreasing of IEEE 802.11 FHSSnetwork. The capacity analysis method and adaptive algorithm adopted in this paper can also begeneralized into other FHSS networks.

L_x频段高速跳频频率合成器

Ｌ_ｘ频段高速跳频频率合成器主研人员：李少谦冯晓东程国辉洪福明杨毅生葛运坤舒力林精波达到的战术指标！ｏｉ＄：１３３８～１５７５Ｍｉｌｋ；③脚濒点间隔：３－－；频率切换时间：＜ｓｗ；相位噪声：＜一９０ｄＢｃ／ｌ（ｌｌ处；ｎｇ：＜一６０ｄＢ，－－－－－ｘ...

High Secure Sequence Design in Frequency Hopping Communications

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.

Network Sorting Algorithm of Multi-Frequency Signal with Adaptive SNR

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.