Jamming Detection in Broadband Frequency Hopping Systems Based on Multi-Segment Signals Spectrum Clustering

In order to solve the problem of low detection rate of frequency hopping (FH) signal under low SNR, an FH signal detection technology based on deep neural network (vgg16 network) is proposed. Firstly, this paper introduces the principle of FH signal. Then, this paper presents the SSD deep neural network detection framework, and uses this framework to detect FH signal and estimate its parameters. Time-frequency distribution maps of FH signals are used as the input of deep neural network model to carry out tag learning and training, and then the trained model is used to realise FH signal detection. At the same time, aiming at the noise problem of time-frequency distribution map, the time-frequency graph correction method of K-means clustering algorithm is proposed. After modification, it is more tolerant to noise. The simulation results show that when the SNR is –4 dB, the detection rate of FH signal can reach more than 88%. Finally, the performance of parameter estimation of FH signal is analysed.

Frequency hopping systems have been widely used in military communications to prevent hostile jamming, interception and detection. In traditional frequency hopping (FH) systems, the transmitter hops in a pseudo-random manner among available frequencies according to a pre- specified algorithm, and the receiver operates accordingly in exact synchronization with the transmitter's hopping pattern. In multiple access systems, a collision may happen when more than one users transmit in the same frequency band simultaneously. Two major limitations with the conventional frequency hopping systems are: strict requirement on frequency acquisition/synchronization, and very low spectral efficiency due to inefficient utilization of the available bandwidth. In this paper, we introduce a new concept collision-free frequency hopping (CFFH). Based on the OFDM framework and the secure subcarrier assignment algorithm, the proposed CFFH system can achieve high information capacity through collision-free multiple access, and can successfully resolve the strict synchronization limitation. At the same time, as each user still transmits through a pseudo-random frequency hopping scheme, CFFH can maintain the inherent anti-jamming, anti-interception security features of the conventional FH system. The proposed CFFH scheme can be used for both civilian and military applications where secure high speed information transmission is needed.

In differential frequency hopping (FH) wireless systems, data are expressed by frequency hopping pattern, and frequency detection involving the Fourier transform and widebands requires large numbers of Nyquist samples, which makes them difficult to implement. Due to the sparseness of FH signals in the frequency domain, compressive sampling (CS) techniques have been explored for the sampling and reconstruction of such signals. In CS, the number of measurements must satisfy $$M\ge {C}\cdot {\mu }^2(\varvec{\varPhi },\varvec{\varPsi })\cdot {K}\cdot {}log(N)$$M?C·μ2(?,?)·K·log(N), where $$C$$C and $$\mu (\varvec{\varPhi },\varvec{\varPsi })$$μ(?,?) are the constants, $$K$$K is the sparsity level, and $$N$$N is the dimension of the original signal. Because of the large number of channels in the operation band, many of these channels are often occupied by diverse frequency-fixed (FF) signals. For this reason, the band compression rate (BCR $$=N/M$$=N/M) may be greatly reduced. However, the FH signals only occupy a single frequency at a time. This means that $$K=1$$K=1, and the number of measurements can be far smaller than the number to restore the mixture of FH and FF signals. In this paper, a CS method that is not subject to the influence is presented, and the BCR can reach 1,000:6 when the FH signal is mixed with 50 interferences. The proposed algorithm covers the generation of the sampling matrix and signal reconstruction. Specifically, it maximizes the signal-to-noise ratio of the compressed signal with a white noise background. The new reconstruction algorithm was found to be 5 times faster than the OMP algorithm in the case of that $$K=4$$K=4, and it is not limited by the inequality given above.

Unmanned aircraft vehicle frequency hopping (UAV-FH) systems face multiple types of jamming, and one anti-jamming method cannot cope with all types of jamming. Therefore, the jamming signals of the environment where the UAV-FH system is located must be identified and classified; moreover, anti-jamming measures must be selected in accordance with different jamming types. First, the algorithm extracts the Sevcik fractal dimension from the frequency domain (SFDF) and the degree of energy concentration from the fractional Fourier domain of various types of jamming. Then, these parameters are combined into a two-dimensional feature vector and used as a feature parameter for classification and recognition. Lastly, a binary tree-based support vector machine (BT-SVM) multi-classifier is used to classify the jamming signal. Simulation results show that the feature parameters extracted by the proposed method have good separation and strong stability. Compared with the existing box-dimensional recognition algorithm, the new algorithm not only can quickly and accurately identify the type of jamming signal but also has more advantages when the jamming-to-noise ratio (JNR) is low.

Frequency hopping (FH) signal has been widely used in military and civilian fields because of its superior anti-jamming performance. Meanwhile, its natural characteristics, i.e., hopped carrier frequency, brings a great challenge to the reconnaissance of FH emitters. To locate a high-speed moving FH emitter, the estimation of range difference (RD) and range rate difference (RRD) is a key process in passive localization. This paper proposes a joint RD and RRD estimation algorithm with the consideration of range migration (RM) during observation time. In this method, a new operation named frequency reversing transform is first presented to remove the random phase of the FH signal. Then, RD and RRD can be coherently estimated after RM correction via the scaled Fourier transform. This method accomplishes the RD and RRD estimation without knowing the hopped carrier frequencies of received FH signals, and it can be fast implemented by complex multiplications, fast Fourier transform (FFT) and inverse FFT operations without any searching process. Numerical experiments indicate that compared with several representative methods, the proposed estimation method achieves a better anti-noise performance with lower computational cost.

Aiming at the problem that single‐network hopping signals have not fully utilised its frequency domain sparse characteristic in the parameter estimation, this study proposes a parameter estimation of frequency hopping (FH) signal based on multi‐measurement vector sparse Bayesian learning (MSBL) in modulation wideband converter (MWC). Since the FH signal is sparse in the frequency domain, the authors apply the MSBL method to estimate its parameters. After the signal is sampled by the MWC, the MSBL algorithm is used to reconstruct its support set. Then the time–frequency ridge method is used to estimate the signal's hop duration, time‐hopping, and carrier frequency based on the time–frequency map. Simulation experiments show that under the condition of low signal‐to‐noise ratio, the parameter estimation performance in the case can be improved by up to 65% and anti‐noise performance can be improved up to 6 db compared with the existing method. The result is very close to the Nyquist full sampling and can greatly improve the accuracy of the FH signal parameter estimation in the MWC system and relieve the pressure of the hardware.

Long-time coherent integration using frequency hopping signals is a challenging problem for passive bistatic radar due to its frequency hopping characteristics. Apart from range walk, range curve, and Doppler frequency migration, Doppler diffusion caused by frequency hopping characteristics occurs within the observation time, which also lowers the detection performance. To deal with this problem, a novel coherent integration method for frequency hopping signals based on passive bistatic radar is proposed in this paper. In this novel method, range curve and range walk are eliminated by applying generalized Keystone transform. Then, Doppler frequency migration caused by the target's acceleration is compensated for by a parameter search with a designed search scope. Finally, Doppler frequency migration caused by frequency hopping characteristics is compensated for by designing a new acceleration compensation function and a revised rotation factor for Fourier transform. Since migration effects caused by frequency hopping characteristics are considered and compensated for when using frequency hopping signals, the weak target echo can be better integrated in the observation time compared to when using the existing methods. The simulation results and performance analysis illustrate the effectiveness of the proposed method.

A jamming detection algorithm for surveillance radar is proposed. The algorithm applies the features of order statistics constant false alarm rate (OS-CFAR) to the power spectral density (PSD) of the received signal which is not done before. The proposed algorithm shows a better probability of jamming detection compared to other jamming detection algorithms. Furthermore, it can be performed in real time because it does not need to receive a large number of samples as in various traditional CFAR algorithms to detect the presence of jamming. The jamming detection performance of the proposed algorithm in the presence of different jamming techniques is presented using actual received data from two-dimensional (2-D) surveillance radar.

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert–Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert–Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

In this paper the bit error probability of the SFH/MFSK system in presence of wideband and tone interference in a fading environment is evaluated. Simultaneous license-free operation of tone-like applications, Frequency Hopping (FH), and Direct Sequence (DS) based LAN clusters is assumed to be the prime interference facing the subject FH wireless LAN (of the IEEE 802.11 standard). The wideband DS interference is considered to have a sinc2() shape Power Spectral Density (PSD) centered at the middle of FH signal band and tone interferers are assumed to be spread over the whole FH band of the intended signal. Assumptions of slow non-selective fading along with slow hopping justify a quasi-static treatment. Results shows that the FH system is more sensitive to tone interference and fading and less sensitive to wideband interference variations. The paper sheds light on the performance of wireless LAN operation in the unlicensed free band where many other LANs may exist.

The synchronization is one of the key techniques in frequency hopping communication system. In this paper, a new synchronization scheme for high-speed frequency hopping is analyzed after analyzing synchronization in conventional frequency hopping communication system. Based on the method combined synchronization-head with time of day (TOD), the synchronization information is carried by slow-hopped pattern, and the corresponding message is carried by fast-hopped pattern, which overcomes the difficulty of correlation code transmission in fast frequency hopping. This paper mainly studies the frame of synchronization head,the synchronization of FH pattern. The performance of synchronization is analyzed and the simulation is completed by using Matlab7.0. The performance of synchronization shows that the scheme has the advantages of short synchronization time, higher probability of capture and lower false probability.

Differential frequency hopping communication system as a new concept of communication systems has become an important development direction of the current shortwave confidential communications. In this paper, on the DFH communication mechanism based on the establishment of a function, the function design m sequences designed based on HHT transform DFH signal detection design, experimental results show that this scheme can effectively achieve DFH Signal generation and detection of a communication system. KEYWORD: DFH; G function; HHT transform; detection International Conference on Social Science, Education Management and Sports Education (SSEMSE 2015) © 2015. The authors Published by Atlantis Press 710 unknown Research hopping signal detection method differential signal parameters under the conditions. 2 BASIC PRINCIPLE OF DFH The concept stems from a DFH enhanced 1995 Sandes company developed Spread Spectrum (Correlated Hopping Enhanced Spread Spectrum, called CHESS) system, CHESS radio with DFH (Differential Frequency Hopping, referred DFH) as the core technology to achieve high-speed frequency hopping, hopping speed up to 5000 hops / sec transfer rate up to 19.2kbit / s, and anti-jamming, strong anti-fading capability. DFH has two key technologies, namely signal detection technology design technology and the receiving end of a differential frequency hopping pattern. DFH system uses a new technology system, its design is based on the hopping pattern called a mathematical relationship of G function, at the sending end, the frequency value of the current time n f is by the frequency value 1 n f  and the current time data symbols n X decision. An implicit difference equation is expressed as [8]: ) , ( 1 n n n X f G f   (1) G(∙)indicates a function transform relations, referred to function. Its frequency, data transformation relationship can be expressed in the form of a diagram of transformation function in Figure 1. Fig.1 The G function transform Differential frequency hopping communication system, the receiver uses a variety of new technology to receive broadband, digital signal processing. At the receiving end, by the broadband receiving digitized, characterized by the FFT analysis of all signals within the bandwidth of the frequency hopping, 1 n f  and n f is determined. Restore the data transmitting side by the inverse transform function, namely: ) , ( 1 1 n n n f f G X    (2) Wherein G -1 denotes inverse transform function of G, which requires the function G must have reversible. Its inverse transform relationship can be expressed in the form of a diagram 2. Fig.2 The inverse G function transform 3 G FUNCTION ALGORITHM PRINCIPLE In the differential frequency hopping, G function is a specific frequency transfer function, can be seen as a directed graph, directed graph node represents a frequency point of each frequency set, each node separates 2 f  branches, BPH representative of the number of bits per hop transmission, also called the fan-out coefficients. Are marked on each bifurcation current information symbols to the set of frequencies containing frequencies of 64, for example, when each hop transmission 1bit, each node has two bifurcated (0,1). BPH transmission bit stream bits per symbols constituting a transmission symbol stream according to a given differential frequency hopping sequence with a frequency corresponding to the generated map. 3.1 1 bit G function design G function design approach are many, including those based on the theory of congruence G function design, based on the state of the shift register design function G, G function m-sequence-based design and so on. In this selection of designs based on G function m sequences. Algorithm is described as follows: Step1 First reads the data n X to be transmitted, the data is encoded, the encoded data n d is calculated.

A channel simulator that models accurately the physical channel statistics determined by the frequency separation between two carriers in frequency hopping (FH) systems is called a FH channel simulator. In this paper, a novel stochastic FH simulation model based on Rice's sum of sinusoids is proposed for wideband mobile fading channels. It is shown that a frequency hop is the physical channel model that corresponds to phase hops in the simulation model, while maintaining all other parameters unchanged. Furthermore, this simulator is capable of simulating both the fast FH and slow FH fading channel by only adjusting the phase hop rate. Due to the fact that closed-form expressions are given for all model parameters, we can study the correlation properties of the proposed simulation model from both the analytical and simulation point of view. A pretty good agreement between the correlation properties of the simulation model and those of the underlying reference model has been observed in all cases.

It is difficult to ensure stability and communication efficiency of traditional anti-jamming frequency hopping communication system in the frequency domain probabilistic jamming environment. Therefore, this paper proposes an adaptive frequency hopping communication scheme under probabilistic jamming. Based on the probabilistic jamming model, the practical frequency hopping (FH) strategy and average payoff is obtained using Q-Learning algorithm and is compared with the theoretical optimal average payoff obtained by the greedy algorithm. Simulation results show that our proposed algorithm is fast to converge, has fewer frequency hops compared with existing anti-jamming FH strategy, and the average payoff is close to the theoretical optimal frequency hopping strategy.

Information communication of frequency hopping is a kind of spread spectrum in communication, it has strong anti-jamming ability, good performance of confidentiality, resistance to intercept ability and multi-user random access etc. Frequency hopping signal's spectrum is a very broad bring to unequal interval random jump, frequency hopping communication is using discrete channel. Today, the spectrum resources is shortage, in order to improve the existing spectrum utilization, cognitive radio therefore put forward the solution. The combination of cognitive radio and frequency hopping, not only improve the utilization rate of spectrum, but also improve the communication quality. This article is based on the combination of cognitive and frequency hopping, and proposed a kind of channel Information cognitive radio network channel access with good SNR selected.