Probability Of Intercept Research Articles

FPGA-Based Wigner–Hough Transform System for Detection and Parameter Extraction of LPI Radar LFMCW Signals

Low probability of intercept (LPI) radars using linear frequency-modulated continuous waveforms (LFMCWs) is rapidly proliferating in the military domain and posing a serious challenge to conventional electronic support receivers (ESRs). In this article, we provide a practical approach that can be used in digital ESR systems for real-time LFMCW radar signal detection and parameter extraction under challenging SNR levels. We proposed a modified version of the Wigner–Ville distribution (WVD), namely, short-time Wigner distribution (STWD), postprocessing steps, e.g., column-based thresholding of STWD combined with the Hough transform (HT), and a field-programmable gate array (FPGA) design as an embedded solution with low computational complexity. The performance of the proposed system is tested with MATLAB and hardware simulations using a signal database generated with different signal-to-noise ratio (SNR) levels. The system is then embedded into a Virtex-7 FPGA where the performance evaluations showed satisfactory detection results down to −6-dB SNR level, and parameter extraction results down to −8-dB SNR level.

LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion

Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models’ performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features extracted by the networks are insufficient under noise jamming. In this paper, we propose a multi-resolution deep feature fusion method for LPI radar waveform recognition. First, we apply the enhanced Fourier-based Synchrosqueezing Transform (FSST), which shows good performance at low SNRs, to convert radar signals into time-frequency images. Then, we construct a multi-resolution deep convolutional network to extract more deep features from each resolution channel. Next, we explore an interactive feature fusion strategy for deep feature fusion. By some down-sampling or up-sampling blocks, different resolution features are fused to generate new features. Finally, we apply a fusion algorithm to the fully connected layer to achieve classification fusion for better performance. Simulation experiments on twelve kinds of LPI radar waveforms show that the overall recognition accuracy of our method can reach 95.2% at the SNR of −8 dB. It is proved that our approach does indeed improve the recognition accuracy effectively at low SNRs.

Numerical simulation of multi output radar orthogonal waveform based on chaos optimization algorithm

Aiming at the problems of low probability of interception and poor anti-jamming performance of multi output radar, the numerical simulation of orthogonal waveform of multi output radar based on chaos optimization algorithm is proposed. Firstly, chaotic frequency coding is applied to multi output radar signal, and different frequency modulation is applied to different sub pulse. At the same time, in view of the low efficiency of numerical simulation algorithm in large space and high dimension optimization, GASA algorithm is used to increase the diversity of chaotic optimization algorithm process. According to the specific working mode, the initial phase of each cycle of multi output radar orthogonal waveform is obtained, and the number of numerical simulation of multi output radar orthogonal waveform is established Model. The experimental results show that the proposed method can improve the radar energy utilization and the signal-to-noise ratio of the echo signal, allocate the transmitting energy reasonably, and keep the structural stability of LFM signal frequency changing continuously with time.

A novel algorithm for implementing time-frequency transform with low computation.

In this paper, a novel algorithm called two-dimensional sliding fast Fourier transform (2D SFFT) algorithm is proposed. This algorithm organizes one-dimensional data in two dimensions and calculates the spectrum of current data by using the existing spectrum and new collected data. The algorithm formula and accurate simulation results show the following: first, the computation required by the proposed 2D SFFT algorithm is lower than that required by the traditional sliding discrete Fourier transform algorithm when the sliding rate is larger than or equal to 4/M, where M is the sequence length. Moreover, the computation required by the proposed 2D SFFT algorithm is lower than that required by the fast Fourier transform (FFT) algorithm when the sliding rate is less than or equal to 6.25%. Finally, the error between the spectrum calculated by the 2D SFFT and FFT algorithms is less than 10-10. The 2D SFFT algorithm is used to increase the power of the ultra-short pulse, which is initially invisible in the frequency-domain window of the mixed-domain oscilloscope. Therefore, the 100% probability of intercept of the mixed-domain oscilloscope is lower.

LPI RADAR WAVEFORM CLASSIFICATION USING BINARY SVM AND MULTI-CLASS SVM BASED ON PRINCIPAL COMPONENTS OF TFI

Since cognition has become an important topic in Electronic Warfare (EW) systems, Electronic Support Measures (ESM) are used to monitor, intercept and analyse radar signals. Low Probability of Intercept (LPI) radars is preferred to be able to detect targets without being detected by ES systems. Because of their properties as low power, variable frequency, wide bandwidth, LPI Radar waveforms are difficult to intercept with ESM systems. In addition to intercepting, the determination of the waveform types used by the LPI Radars is also very important for applying counter-measures against these radars. In this study, a solution for the LPI Radar waveform recognition is proposed. The solution is based on the training of Support Vector Machine (SVM) after applying Principal Component Analysis (PCA) to the data obtained by Time-Frequency Images (TFI). TFIs are generated using Choi-Williams Distribution. High energy regions on these images are cropped automatically and then resized to obtain uniform data set. To obtain the best result in SVM, the SVM Hyper-Parameters are also optimized. Results are obtained by using one-against-all and one-against-one methods. Better classification performance than those given in the literature have been obtained especially for lower Signal to Noise Ratio (SNR) values. The cross-validated results obtained are compared with the best results in the literature.

Precise ranging for the multi regions of two complex-shape targets by using two chaotic polarization components in the optically pumped spin vertical cavity surface emitting laser with optical injection

<sec> The ranging based on the chaotic lidar (CLR) generated by using the nonlinear dynamic of semiconductor with optical feedback or optical injection exhibits many advantages over the ranging using pulse lasers and CW lasers, such as low probability of intercept, strong anti-interference ability and low cost. Moreover, it has high resolution, benefiting from the broad bandwidth of the optical chaos. Finally, it is easily be generated and controlled due to the sensitivity of chaotic radar to laser parameters. </sec><sec> The resolution of the correlated chaotic lidar (CLR) ranging which has been reported in many literatures is largely limited by the bandwidth of the chaotic laser. An ultra-fast chaotic laser with large modulation bandwidth is required to further improve the ranging resolution. The recently proposed optically pumped spin-VCSEL has attractive features such as flexible spin control of lasing output, fast dynamics with femtosecond magnitude and large modulation bandwidth. The ultra-fast chaos radar wave emitted from the optically pumped spin-VCSEL with optical injection or optical feedback is expected to be used for improving the resolution and accuracy of target ranging. In addition, since the multi beams of CLRs were utilized in the previous works, the number of ranging targets is limited to a small number of targets. The reported CLR ranging technology cannot completely detect the distance of different regions in the target, and it is not suitable for the accurate ranging of the whole area in the complex shape target. The detection waveform based on the correlation CLR has not been designed before the target ranging, which affects the further improvement of the resolution and accuracy of the target ranging. To overcome these problems, it is necessary to further explore the theoretical and physical mechanism of the CLR ranging for the multi-region in complex shape target, and explore the new scheme and method for its realization. Motivated by these, in this paper, based on the optically pumped spin vertical cavity surface emitting laser with optical injection, we present a novel scheme for the accurate ranging of the multi regions in two complex shape targets, using two chaotic polarization components modulated by the bipolar sinc waveform. Here, these two modulated chaotic polarization probe waveforms possess the attractive features of the uncorrelation in time and space, fast dynamic with femtosecond magnitude. Utilizing these features, the accurate ranging to the position vectors of the multi regions of two complex-shape targets can be achieved by correlating the multi beams of the time-delay reflected chaotic polarization probe waveforms with their corresponding reference waveforms. The further investigations show that the ranging to the multi-region small targets possesses the very low relative error that is less than 0.94%. If the bandwidths of the photodetectors are large enough, their range resolutions are achieved as high as 0.4 mm, and exhibit excellent strong anti-noise performance and strong stability. The multi area target ranging proposed in our scheme has the following attractive advantages: stable and high range resolution, strong anti-noise ability and very low relative error. These characteristics can meet the needs of the position vector ranging of the multi regions in complex shape targets.</sec>

Detection and recognition of LPI radar signals using visibility graphs

The detection and recognition of radar signals play a critical role in the maintenance of future electronic warfare (EW). So far, however, there are still problems with signal detection and recognition, especially in the low probability of intercept (LPI) radar. This paper explores the usefulness of such an algorithm in the scenario of LPI radar signal detection and recognition based on visibility graphs (VG). More network and feature information can be extracted in the VG two-dimensional space, this algorithm can solve the problem of signal recognition using the autocorrelation function. Wavelet denoising processing is introduced into the signal to be tested, and the denoised signal is converted to the VG domain. Then, the signal detection is performed by using the constant false alarm of the VG average degree. Next, weight the converted graph. Finally, perform feature extraction on the weighted image, and use the feature to complete the recognition. It is testified that the proposed algorithm offers significant improvements, such as robustness to noise, and the detection and recognition accuracy, over the recent researches.

Multi-Resolution Fusion Convolutional Neural Networks for Intrapulse Modulation LPI Radar Waveforms Recognition

Low Probability of Intercept (LPI) radar waveform has complex and diverse modulation schemes, which cannot be easily identified by the traditional methods. The research on intrapulse modulation LPI radar waveform recognition has received increasing attention. In this paper, we propose an automatic LPI radar waveform recognition algorithm that uses a multi-resolution fusion convolutional neural network. First, signals embedded within the noise are processed using Choi-William Distribution (CWD) to obtain time-frequency feature images. Then, the images are resized by interpolation and sent to the proposed network for training and identification. The network takes a dual-channel CNN structure to obtain features at different resolutions and makes features fusion by using the concatenation and Inception module. Extensive simulations are carried out on twelve types of LPI radar waveforms, including BPSK, Costas, Frank, LFM, P1~P4, and T1~T4, corrupted with additive white Gaussian noise of SNR from 10dB to -8dB. The results show that the overall recognition rate of the proposed algorithm reaches 95.1% when the SNR is -6dB. We also try various sample selection methods related to the recognition task of the system. The conclusion is that reducing the samples with SNR above 2dB or below -8dB can effectively improve the training speed of the network while maintaining recognition accuracy.

Enhancement of reliability and security in spatial diversity FSO-CDMA wiretap channel

Abstract Due to atmospheric turbulence, the reliability and security of free space optical (FSO) communication will be affected seriously. In this paper, we propose a novel scheme of quasisynchronous spatial diversity free-space optical code division multiple access (FSO-CDMA) wiretap channel based on gamma-gamma distribution. Considering multiple access interference, shot noise, thermal noise and background noise, performances of bit error rate (BER) and physical-layer security are analyzed theoretically. The physical-layer security of quasisynchronous spatial diversity FSO-CDMA wiretap channel is evaluated by secrecy capacity and interception probability. Closed-form expression of interception probability is obtained. In order to compare the performances between conventional spatial diversity FSO-CDMA and the proposed scheme, Optisystem simulation is carried out. The results indicate that quasisynchronous spatial diversity FSO-CDMA scheme can improve the reliability and physical-layer security simultaneously.

Dwell Time Allocation Algorithm for Multiple Target Tracking in LPI Radar Network Based on Cooperative Game.

To solve the problem of dwell time management for multiple target tracking in Low Probability of Intercept (LPI) radar network, a Nash bargaining solution (NBS) dwell time allocation algorithm based on cooperative game theory is proposed. This algorithm can achieve the desired low interception performance by optimizing the allocation of the dwell time of each radar under the constraints of the given target detection performance, minimizing the total dwell time of radar network. By introducing two variables, dwell time and target allocation indicators, we decompose the dwell time and target allocation into two subproblems. Firstly, combining the Lagrange relaxation algorithm with the Newton iteration method, we derive the iterative formula for the dwell time of each radar. The dwell time allocation of the radars corresponding to each target is obtained. Secondly, we use the fixed Hungarian algorithm to determine the target allocation scheme based on the dwell time allocation results. Simulation results show that the proposed algorithm can effectively reduce the total dwell time of the radar network, and hence, improve the LPI performance.

Development of a secured optical code-division multiple access system by implementing hybrid 2D-modified Walsh code

We present the development of a multi-user cross-layer security network implemented on the optical code-division multiple access (OCDMA) with newly designed hybrid 2D-modified Walsh code (MWC) along with an algorithmic approach in cryptography domain. Minimum BER value is evaluated on the order of 10 − 50 using our designed MWC, which is comparatively lower than other existing codes. The security performance of the network was analyzed using the probability detection parameter, which was found to be superior apart from few other available existing codes. The enhancement of the quality and grade of security in this network eavesdropper can intercept the designed optical code of OCDMA in the physical layer. It compels one to break the security in the data-layer to access the original code. We also calculated the probability of successful data interception as a function of time complexity. Furthermore, we presented the simulation of the hybrid system using the OptiSystem simulator.

Estimation of Modulation Parameters of LPI Radar Using Cyclostationary Method

Low Probability of intercept (LPI) radars work on the principle of low peak-power and wide bandwidth. To achieve this, the LPI radars use special type of modulated waveforms which are difficult to intercept. The main tasks of intercept receivers are to detect, estimate and classify LPI signals even in the presence of high noise. Accurate estimation of the modulation parameters also provides information about threat to radar so that necessary counter measures could be initiated against the enemy radars. In the present work, Cyclo-stationary (CS) method is used to estimate the parameters of Polytime coded LPI signals. CS method is efficient for the analysis of periodic waveforms like LPI signals and finds applications in many fields such as array signal processing, estimation of direction of arrival, signal detection. Cyclic auto correlation function and the spectral correlation density function (SCD) which are the basis for CS analysis are computed for all the four types of polytime codes. Generation of all the four types of Polytime codes and computation of SCD coefficients are carried out using MATLAB. From the contour plot of SCD function, the parameters carrier frequency, bandwidth and code rate are measured. It is assumed that the received signal is not corrupted with any noise. The simulation results are compared with the values available in the literature. The maximum error of estimation is well within ± 6% for all the codes in the proposed method whereas the maximum error reported in the literature is 25.7%. Hence the proposed method is better. Since CS method is sensitive to sampling frequency, the analysis is repeated for three different sampling frequencies and in all cases, the estimation error is less than 6%.

Joint Target Assignment and Resource Optimization Framework for Multitarget Tracking in Phased Array Radar Network

In this article, a joint target assignment and resource optimization (JTARO) strategy is proposed for the application of multitarget tracking in phased array radar network system. The key mechanism of our proposed JTARO strategy is to employ the optimization technique to jointly optimize the target-to-radar assignment, revisit time control, bandwidth, and dwell time allocation subject to several resource constraints, while achieving better tracking accuracies of multiple targets and low probability of intercept (LPI) performance of phased array radar network. The analytical expression for Bayesian Cramér-Rao lower bound with the aforementioned adaptable parameters is calculated and subsequently adopted as the performance metric for multitarget tracking. After problem partition and reformulation, an efficient three-stage solution methodology is developed to resolve the underlying mixed-integer, nonlinear, and nonconvex optimization problem. To be specific, in Step 1, the revisit time for each target is determined. In Step 2, we implement the joint signal bandwidth and dwell time allocation for fixed target-to-radar assignments, which combine the cyclic minimization algorithm and interior point method. In Step 3, the optimal target-to-radar assignments are obtained, which results in the minimization of both the tracking accuracy for multiple targets and the total dwell time consumption of the network system. Simulation results are provided to demonstrate the advantages of the presented JTARO strategy, in terms of the achievable multitarget tracking accuracy and LPI performance of phased array radar network.

Secrecy Analysis of Ambient Backscatter NOMA Systems Under I/Q Imbalance

We investigate the reliability and security of the ambient backscatter (AmBC) non-orthogonal multiple access (NOMA) systems, where the source aims to communication with two NOMA users in the presence of an eavesdropper. We consider a more practical case that nodes and backscatter device (BD) suffer from in-phase and quadrature-phase imbalance (IQI). More specifically, exact analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived in closedform. Moreover, the asymptotic behaviors and corresponding diversity orders for the OP are discussed. Numerical results show that: 1) Although IQI reduces the reliability, it can enhance the security. 2) Compared with the traditional orthogonal multiple access (OMA) system, the AmBC-NOMA system can obtain better reliability when the signal-to-noise (SNR) ratio is low; 3) There are error floors for the OP because of the reflection coefficient \b{eta} .

Intercept probability analysis in DF time switching full-duplex relaying network with impact of Co-channel interference at the eavesdropper

In this research, we propose and investigate intercept probability analysis in DF time switching relaying full-duplex with impact of Co-channel interference at the eavesdropper. In the beginning stage, we present the DF time switching relaying full-duplex with the Impact of Co-channel interference at the eavesdropper. Furthermore, the closed-form expression of the intercept probability (IP) is analyzed and derived in connection with the primary system parameters. Finally, the Monte Carlo simulation is performed for verifying the correctness of the analytical section. From the research results, a novel solution and some recommendations can be proposed for the communication network in the near future.

Deep Learning-Based Approach for Low Probability of Intercept Radar Signal Detection and Classification

Detection and classification of Low Probability of Interception (LPI) radar signals is one of the most important challenges in electronic warfare (EW), since there are limited methods for identifying these type of signals. In this paper, a radar waveform automatic identification system for detecting and classifying LPI radar is studied, and accordingly we propose a method based on deep learning networks to detect and classify LPI radar waveforms. To this end, the GoogLeNet architecture as one of the well-known convolutional neural networks (CNN) is utilized. We employ the Short Time Fourier Transform (STFT) for time-frequency analysis in order to construct the entry image for proposed method 1,2 (improved the GoogLeNet and AlexNet networks) to recognize offline training and online recognition. After the training procedure with the supervised data sets the proposed method 1,2 can detect and classify nine modulation types of LPI radar, including LFM, poly-phase (P1, P2, P3, P4) and poly-time (T1, T2, T3, T4) waveforms. The numerical results for proposed method 1, show considerable accuracies up to 98.7% at the SNR level of –15 dB, which outperforms the existing methods.

Introduction to Noise Radar and Its Waveforms.

In the system-level design for both conventional radars and noise radars, a fundamental element is the use of waveforms suited to the particular application. In the military arena, low probability of intercept (LPI) and of exploitation (LPE) by the enemy are required, while in the civil context, the spectrum occupancy is a more and more important requirement, because of the growing request by non-radar applications; hence, a plurality of nearby radars may be obliged to transmit in the same band. All these requirements are satisfied by noise radar technology. After an overview of the main noise radar features and design problems, this paper summarizes recent developments in “tailoring” pseudo-random sequences plus a novel tailoring method aiming for an increase of detection performance whilst enabling to produce a (virtually) unlimited number of noise-like waveforms usable in different applications.

I/Q Imbalance Aware Nonlinear Wireless-Powered Relaying of B5G Networks: Security and Reliability Analysis

Physical layer security is known as a promising paradigm to ensure secure performance for the future beyond 5G (B5G) networks. In light of this fact, this paper elaborates on a tractable analysis framework to evaluate the reliability and the security of wireless-powered decode-and-forward (DF) multi-relay networks. More practical, the nonlinear energy harvesters, in-phase and quadrature-phase imbalance (IQI) and channel estimation errors (CEEs) are taken into account. To further enhance the secure performance, two relay selection strategies are presented: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1) suboptimal relay selection (SRS); 2) optimal relay selection (ORS)</i> . Specifically, exact analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived in closed-form. For the IP, we consider that the eavesdropper can wiretap the signal from the source or the relay. In order to obtain more deep insights, we carry out the asymptotic analysis as well as the diversity orders for the OP in the high signal-to-noise ratio (SNR) regimes. Numerical results show that: 1) Although the mismatches of amplitude/phase of transmitter (TX)/receiver (RX) limit the OP performance, it can enhance IP performance; 2) Large number of relays yields better OP performance; 3) There are error floors for the OP due to the CEEs; 4) There is a trade-off for the OP and IP to obtain the balance between reliability and security.

Power resource allocation scheme for distributed MIMO dual-function radar-communication system based on low probability of intercept

Distributed multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) configuration, which is composed of multiple distributed dual-function transmitters, multiple radar receivers and multiple communication receivers, are capable of performing target state estimation and information transferring tasks simultaneously. In this article, the authors put forward a low probability of intercept (LPI)-based power resource allocation (PRA) scheme for the distributed MIMO-DFRC system. The key mechanism of the LPI-PRA scheme is to minimize the total power consumption of the overall system by optimizing the radiation power allocation of different dual-function transmitters subject to a predefined target parameter estimation accuracy for radar purpose and a certain wireless communication performance for communication purpose, leading to an improved LPI performance of the distributed MIMO-DFRC system. The closed-form expression for Cramér-Rao lower bound (CRLB) is derived to gauge the target position and velocity estimation performance, and the communication data rate (CDR) is adopted as the performance metric for data transmission. Subsequently, an efficient three-stage solution algorithm is put forward to tackle with the resulting constrained, non-linear, and non-convex optimization problem by exploiting the semi-definite programming (SDP) and Karush-Kuhn-Tuckers (KKT) necessary conditions. Simulation results demonstrate that the proposed LPI-PRA scheme is able to deliver superior LPI performance in terms of minimizing the total power consumption of the distributed MIMO-DFRC system, compared with other power resource allocation algorithms.

Physical security layer with friendly jammer in half-duplex relaying networks over rayleigh fading channel: Intercept probability analysis

In this research, thephysical security layer with a friendly jammerin half-duplex (HD) relaying networksover the Rayleigh fading channel is proposed and investigated. Firstly, we proposed the system model and the time switching,power splitting protocolsfor the system model. Then we conductedthe mathematical analysisfor deriving theexact analysis and asymptotic analysisintegral forms for intercept probability (IP). Finally, the analytical formulationis verified by the Monte Carlo Simulation with all main system parameters. From the results, we can show that the simulation and analytical values are the same values.