Journal articles: 'Low probability of intercept radar'

1

Stove, A. G., A. L. Hume, and C. J. Baker. "Low probability of intercept radar strategies." IEE Proceedings - Radar, Sonar and Navigation 151, no. 5 (2004): 249. http://dx.doi.org/10.1049/ip-rsn:20041056.

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Savci, Kubilay, Gaspare Galati, and Gabriele Pavan. "Low-PAPR Waveforms with Shaped Spectrum for Enhanced Low Probability of Intercept Noise Radars." Remote Sensing 13, no. 12 (June 17, 2021): 2372. http://dx.doi.org/10.3390/rs13122372.

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Noise radars employ random waveforms in their transmission as compared to traditional radars. Considered as enhanced Low Probability of Intercept (LPI) radars, they are resilient to interference and jamming and less vulnerable to adversarial exploitation than conventional radars. At its simplest, using a random waveform such as bandpass Gaussian noise as a probing signal provides limited radar performance. After a concise review of a particular noise radar architecture and related correlation processing, this paper justifies the rationale for having synthetic (tailored) noise waveforms and proposes the Combined Spectral Shaping and Peak-to-Average Power Reduction (COSPAR) algorithm, which can be utilized for synthesizing noise-like sequences with a Taylor-shaped spectrum under correlation sidelobe level constraints and assigned Peak-to-Average-Power-Ratio (PAPR). Additionally, the Spectral Kurtosis measure is proposed to evaluate the LPI property of waveforms, and experimental results from field trials are reported.

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Shi, Chenguang, Wei Qiu, Fei Wang, Sana Salous, and Jianjiang Zhou. "Stackelberg Game-Theoretic Low Probability of Intercept Performance Optimization for Multistatic Radar System." Electronics 8, no. 4 (April 2, 2019): 397. http://dx.doi.org/10.3390/electronics8040397.

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In this paper, the problem of Stackelberg game-theoretic low probability of intercept (LPI) performance optimization in multistatic radar system is investigated. The goal of the proposed LPI optimization strategy is to minimize the transmitted power of each radar while satisfying a predetermined signal-to-interference-plus-noise ratio (SINR) requirement for target detection. Firstly, a single-leader multi-follower Stackelberg game is adopted to formulate the LPI optimization problem of multistatic radar system. In the considered game model, the hostile intercept receiver plays a role of leader, who decides the prices of power resource first through the maximization of its own utility function. The multiple radars are followers to compete with each other in a non-cooperative game according to the imposed prices from the intercept receiver subsequently. Then, the Nash equilibrium (NE) for the considered game model is derived, and the existence and uniqueness of the NE are analytically proved. Furthermore, a pricing-based distributed iterative power control algorithm is proposed. Finally, some simulation examples are provided to demonstrate that the proposed scheme has remarkable potential to enhance the LPI performance of the multistatic radar system.

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Devi, M. Rajani. "Low Probability of Intercept (LPI) Radar Signal Identification Techniques." Bioscience Biotechnology Research Communications 14, no. 5 (June 15, 2021): 365–73. http://dx.doi.org/10.21786/bbrc/14.5/63.

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Basit, Abdul, Ijaz Mansoor Qureshi, Wasim Khan, Ihsan Ulhaq, and Shafqat Ullah Khan. "Hybridization of Cognitive Radar and Phased Array Radar Having Low Probability of Intercept Transmit Beamforming." International Journal of Antennas and Propagation 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/129172.

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A novel design of a cognitive radar (CR) hybridized with a phased array radar (PAR) having a low probability of intercept (LPI) transmit beam forming is proposed. PAR directed high gain property reveals its position to interceptors. Hence, the PAR high gain scanned beam patterns, over the entire surveillance region, are spoiled to get the series of low gain basis patterns. For unaffected array detection performance, these basis patterns are linearly combined to synthesize the high gain beam pattern in the desired direction using the set of weight. Genetic algorithm (GA) based evolutionary computing technique finds these weights offline and stores to memory. The emerging CR technology, having distinct properties (i.e., information feedback, memory, and processing at receiver and transmitter), is hybridized with PAR having LPI property. The proposed radar receiver estimates the interceptor range and the direction of arrival (DOA), using the extended Kalman filter (EKF) and the GA, respectively, and sends as feedback to transmitter. Selector block in transmitter gets appropriate weights from memory to synthesize the high gain beam pattern in accordance with the interceptor range and the direction. Simulations and the results validate the ability of the proposed radar.

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Eskelinen, P. "Detecting and Classifying Low Probability of Intercept Radar [Book Review]." IEEE Aerospace and Electronic Systems Magazine 19, no. 5 (May 2004): 42–44. http://dx.doi.org/10.1109/maes.2004.1301226.

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Key, E. L. "Detecting and classifying low probability of intercept radar [Book Review]." IEEE Aerospace and Electronic Systems Magazine 19, no. 6 (June 2004): 39–41. http://dx.doi.org/10.1109/maes.2004.1308837.

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Galati, Gaspare, Gabriele Pavan, Kubilay Savci, and Christoph Wasserzier. "Counter-Interception and Counter-Exploitation Features of Noise Radar Technology." Remote Sensing 13, no. 22 (November 9, 2021): 4509. http://dx.doi.org/10.3390/rs13224509.

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In defense applications, the main features of radars are the Low Probability of Intercept (LPI) and the Low Probability of Exploitation (LPE). The counterpart uses more and more capable intercept receivers and signal processors thanks to the ongoing technological progress. Noise Radar Technology (NRT) is probably a very effective answer to the increasing demand for operational LPI/LPE radars. The design and selection of the radiated waveforms, while respecting the prescribed spectrum occupancy, has to comply with the contrasting requirements of LPI/LPE and of a favorable shape of the ambiguity function. Information theory seems to be a “technologically agnostic” tool to attempt to quantify the LPI/LPE capability of noise waveforms with little, or absent, a priori knowledge of the means and the strategies used by the counterpart. An information theoretical analysis can lead to practical results in the design and selection of NRT waveforms.

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Song, Yuxiao, Yu Wang, Jingyang Xie, Yiming Yang, Biao Tian, and Shiyou Xu. "Ultra-Low Sidelobe Waveforms Design for LPI Radar Based on Joint Complementary Phase-Coding and Optimized Discrete Frequency-Coding." Remote Sensing 14, no. 11 (May 28, 2022): 2592. http://dx.doi.org/10.3390/rs14112592.

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In this paper, in order to reduce the probability of the radar waveform intercepted by the passive detection system, the time-bandwidth product of the radar waveform is increased, and the detection probability of the radar waveform to the target is improved. This paper tackles the holographic RF stealth radar and proposes a joint coding waveform based on the linear frequency modulation (LFM) waveform. Joint coding uses complementary codes to perform phase-coding, and combines the codewords optimized by genetic algorithm in order to perform discrete frequency-coding waveform. The joint coding waveform model is theoretically analyzed, and the ambiguity function, pulse compression and target detection probability of the joint coding waveform are obtained by numerical simulation. In addition, the complexity of the algorithm and the low probability of intercept (LPI) characteristic of the joint coding waveform are analyzed. The results show that the joint coding waveform has an approximate “pushpin” ambiguity function, ultra-low sidelobe characteristics, better RF stealth and target detection performance. Finally, it has good application prospects in the current battlefield environment.

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Stevens, Daniel L., and Stephanie A. Schuckers. "Analysis of Low Probability of Intercept Radar Signals Using the Reassignment Method." American Journal of Engineering and Applied Sciences 8, no. 1 (January 1, 2015): 26–47. http://dx.doi.org/10.3844/ajeassp.2015.26.47.

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Zhang, Zhenkai, Bing Zhang, Zhibin Xie, and Yi Yang. "Radar Selection Method Based on an Improved Information Filter in the LPI Radar Network." International Journal of Antennas and Propagation 2018 (December 17, 2018): 1–6. http://dx.doi.org/10.1155/2018/6104849.

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In order to save the radar resources and obtain the better low probability intercept ability in the network, a novel radar selection method for target tracking based on improved interacting multiple model information filtering (IMM-IF) is presented. Firstly, the relationship model between radar resource and tracking accuracy is built, and the IMM-IF method is presented. Then, the information gain of every radar is predicted according to the IMM-IF, and the radars with larger information gain are selected to track target. Finally, the weight parameters for the tracking fusion are designed after the error covariance prediction of every working radar, in order to improve the IMM-IF. Simulation results show that the proposed algorithm not only saves much more radar resources than other methods but also has excellent tracking accuracy.

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Rao, M. Sreenivasa, Chandan C. Mishra, K. Krishna Naik, and K. Maheshwara Reddy. "Discrete Electronic Warfare Signal Processing using Compressed Sensing Based on Random Modulator Pre-Integrator." Defence Science Journal 65, no. 6 (November 10, 2015): 472. http://dx.doi.org/10.14429/dsj.65.8414.

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Electronic warfare receiver works in the wide electromagnetic spectrum in dense radar signal environment. Current trends in radar systems are ultra wideband and low probability of intercept radar technology. Detection of signals from various radar stations is a concern. Performance and probability of intercept are mainly dependent on high speed ADC technology. The sampling and reconstruction functions have to be optimized to capture incoming signals at the receiver to extract characteristics of the radar signal. The compressive sampling of the input signal with orthonormal base vectors, projecting the basis in the union of subspaces and recovery through convex optimisation techniques is the current traditional approach. Modern trends in signal processing suggest the random modulator pre-integrator (RMPI), which sample the input signal at information rate non-adaptively and recovery by the processing of discrete and finite vectors. Analysis of RMPI theory, application to EW receiver, simulation and recovery of EW receiver signals are discussed.

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Fu, Lian Qing, Li Sheng Yang, Ya Ning Ma, and Tao Wang. "Anti-Jamming and LPI Radar with Spread Spectrum Technology." Advanced Materials Research 219-220 (March 2011): 57–60. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.57.

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In order to enhance the capability of anti-jamming and Low Probability of Intercept (LPI) of radar system, spread spectrum signals are designed for modern radar system. Emission signal is coded with PN codes at the transmitting terminal. Spectrum of signal is spreaded and multi-signal mixed together, so it is not easy to intercept. At the receiving terminal, undesired signals are spreaded when dispreading desired signal. Signal to noise ratio (SNR) of the received signals is raised after despreading, so the detection range broadens. Computer simulations verify the good performance of the proposed approach.

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Palo, Francesco De, Gaspare Galati, Gabriele Pavan, Christoph Wasserzier, and Kubilay Savci. "Introduction to Noise Radar and Its Waveforms." Sensors 20, no. 18 (September 11, 2020): 5187. http://dx.doi.org/10.3390/s20185187.

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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.

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Shi, Chenguang, Fei Wang, Mathini Sellathurai, and Jianjiang Zhou. "Low probability of intercept based multicarrier radar jamming power allocation for joint radar and wireless communications systems." IET Radar, Sonar & Navigation 11, no. 5 (May 2017): 802–11. http://dx.doi.org/10.1049/iet-rsn.2016.0362.

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Tian, Gao, Yan Yang, and Wang Qi. "Research of Radar Waveform Based on Pulse Position Jitter and Relative LPI Performance Analysis." Applied Mechanics and Materials 457-458 (October 2013): 1338–43. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1338.

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The low probability of intercept (LPI) radar waveform is reflected in a lower pulse power and complex structure of the pulse series. The previous one ensures that it avoids being intercepted by the electronic measures system (ESM) carried by the goal; the latter makes it difficult for ESM to separate and identify. As for pulse position jitter pulse array, because of pulse position's random jitter in a specific pulse interval of the pulse repetition interval (PRI), the spectrum broadens and spectral density reduces, making it hard for the ESM to intercept. Meanwhile, because the waveform doesn't have a fixed PRI, it's also difficult to be sorted or identified Therefore pulse position jitter waveform is a rational LPI waveform. Combined with a design about the LPI radar signal waveform, this paper carries out a research on PRI jitter waveform, and provides a waveform generating and echo signal processing method; then the paper simulates the LPI characteristics and comes to a conclusion which has an important applying value .

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Ghadimi, G., Y. Norouzi, R. Bayderkhani, M. M. Nayebi, and S. M. Karbasi. "Deep Learning-Based Approach for Low Probability of Intercept Radar Signal Detection and Classification." Journal of Communications Technology and Electronics 65, no. 10 (October 2020): 1179–91. http://dx.doi.org/10.1134/s1064226920100034.

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Baher Safa Hanbali, Samer. "A review of radar signals in terms of Doppler tolerance, time-sidelobe level, and immunity against jamming." International Journal of Microwave and Wireless Technologies 10, no. 10 (August 8, 2018): 1134–42. http://dx.doi.org/10.1017/s1759078718001174.

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AbstractPulse compression technique allows a radar to achieve the resolution of a short pulse and the energy of a long pulse simultaneously, without the requirement of high-power transmission. Therefore, pulse compression radars have a low probability of intercept capability. The common types of pulse compression signals are frequency modulated waveforms and phase-coded waveforms, which have different properties. The optimum radar signal should have good immunity against deceptive jamming, good Doppler tolerance to detect high-speed targets, and low time-sidelobe level to detect weak targets nearby the strong ones. This paper reviews the current research in the commonly used radar signals, and presents their pros and cons, and compares between them in terms of Doppler tolerance, time-sidelobe level, as well as immunity against jamming in order to provide a reference for the researchers in the field of radar systems and electronic warfare.

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Shi, Chenguang, Fei Wang, Mathini Sellathurai, and Jianjiang Zhou. "LPI Optimization Framework for Target Tracking in Radar Network Architectures Using Information-Theoretic Criteria." International Journal of Antennas and Propagation 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/654561.

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Widely distributed radar network architectures can provide significant performance improvement for target detection and localization. For a fixed radar network, the achievable target detection performance may go beyond a predetermined threshold with full transmitted power allocation, which is extremely vulnerable in modern electronic warfare. In this paper, we study the problem of low probability of intercept (LPI) design for radar network and propose two novel LPI optimization schemes based on information-theoretic criteria. For a predefined threshold of target detection, Schleher intercept factor is minimized by optimizing transmission power allocation among netted radars in the network. Due to the lack of analytical closed-form expression for receiver operation characteristics (ROC), we employ two information-theoretic criteria, namely, Bhattacharyya distance and J-divergence as the metrics for target detection performance. The resulting nonconvex and nonlinear LPI optimization problems associated with different information-theoretic criteria are cast under a unified framework, and the nonlinear programming based genetic algorithm (NPGA) is used to tackle the optimization problems in the framework. Numerical simulations demonstrate that our proposed LPI strategies are effective in enhancing the LPI performance for radar network.

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Kamble, Jayshree, I. A Pasha, and M. Madhavilatha. "Poly-phase signal generation and optimizationof LPI Radar: A new approach." International Journal of Engineering & Technology 7, no. 2.6 (March 11, 2018): 147. http://dx.doi.org/10.14419/ijet.v7i2.6.10141.

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Low Probability of Intercept (LPI) Radar own certain positive characteristics make them nearly undetectable by Intercept Receivers. In a battle field, this present a considerable strategic problem. New digital receivers required complex signal processing techniques to detect these types of Radar. This paper address the problem of constructing a new hybrid waveform design using Poly-Phase modulation technique to optimize the detection performance of LPI Radar. Phase coded Pulse compression waveforms using Frequency Hopping Spread Spectrum (FHSS) are designed to evaluate the detection performance of LPI radar in terms of Discrimination factor (DF).The difference in DF of the Poly-phase coded and Binary phase coded signals is increasing with the increase in the phase values.The effect of noise on Hybrid Poly-Phase waveforms examined using the signal to noise ratios of -10dB,-15dB and -20dB and extract the parameter necessary for the LPI Radar system.

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Ding, Lintao, Chenguang Shi, Wei Qiu, and Jianjiang Zhou. "Joint Dwell Time and Bandwidth Optimization for Multi-Target Tracking in Radar Network Based on Low Probability of Intercept." Sensors 20, no. 5 (February 26, 2020): 1269. http://dx.doi.org/10.3390/s20051269.

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Radar network systems have been demonstrated to offer numerous advantages for target tracking. In this paper, a low probability of intercept (LPI)-based joint dwell time and bandwidth optimization strategy is proposed for multi-target tracking in a radar network. Since the Bayesian Cramer–Rao lower bound (BCRLB) provides a lower bound on parameter estimation, it can be utilized as the accuracy metric for target tracking. In this strategy, in order to improve the LPI performance of the radar network, the total dwell time consumption of the underlying system is minimized, while guaranteeing a predetermined tracking accuracy. There are two adaptable parameters in the optimization problem: one for dwell time, and the other for bandwidth allocation. Since the nonlinear programming-based genetic algorithm (NPGA) can solve the nonlinear problem well, we develop a method based upon NPGA to solve the resulting problem. The simulation results demonstrate that the proposed strategy has superiority over traditional algorithms, and can achieve a better LPI performance of this radar network.

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Wang, Xue Mei, Chun Yang Wang, Yu Chen, Yan Xin Yu, and Hong Yan Sun. "A Method for Designing Low Peak to Average Power Cognitive Radar Waveform." Applied Mechanics and Materials 716-717 (December 2014): 1055–59. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1055.

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In this paper, the basis function of TDCS system (Transform Domain Communication System) is used to design cognitive radar transmitter waveform. Based on the noise environment, the waveform can be adjusted adaptively. Then after clipping to reduce the PAPR (Peak to Average Power Ratio) of radar echo signal, the obtained signal is used as the next launch of the radar signal. The cognitive radar transmitter requires a nonlinear waveform to improve the efficiency of radar transmitter power amplifier, so reducing the PAPR of signal is essential. This paper presents the gray complementary sequence is applied to TDCS communication systems, and then it needs to reduce PAPR of signals by clipping. Proven, PAPR of the transmitted signal is maintained at about 3.25dB, and the signal has a low probability of intercept, high anti-interference ability and distant target detection range.

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Xue, Chenyan, Ling Wang, and Daiyin Zhu. "Dwell Time Allocation Algorithm for Multiple Target Tracking in LPI Radar Network Based on Cooperative Game." Sensors 20, no. 20 (October 21, 2020): 5944. http://dx.doi.org/10.3390/s20205944.

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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.

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Shi, Chenguang, Fei Wang, Mathini Sellathurai, Jianjiang Zhou, and Huan Zhang. "Robust Transmission Waveform Design for Distributed Multiple-Radar Systems Based on Low Probability of Intercept." ETRI Journal 38, no. 1 (February 1, 2016): 70–80. http://dx.doi.org/10.4218/etrij.16.0114.1230.

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Hejazi Kookamari, Farzam, Yaser Norouzi, and Mohammad Mahdi Nayebi. "Using a moving aerial platform to detect and localise a low probability of intercept radar." IET Radar, Sonar & Navigation 11, no. 7 (May 18, 2017): 1062–69. http://dx.doi.org/10.1049/iet-rsn.2016.0295.

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Shi, C. G., F. Wang, S. Salous, and J. J. Zhou. "Adaptive Jamming Waveform Design for Distributed Multiple-Radar Architectures Based on Low Probability of Intercept." Radio Science 54, no. 1 (January 2019): 72–90. http://dx.doi.org/10.1029/2018rs006668.

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Neelakanta, Perambur, and Dolores De Groff. "Assessment of RCS-specific SNR and Loglikelihood Function in Detecting Low-observable Targets and Drones Illuminated by a Low Probability of Intercept Radar Operating in Littoral Regions." Transactions on Networks and Communications 9, no. 4 (July 30, 2021): 1–22. http://dx.doi.org/10.14738/tnc.94.10512.

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The objective of this study is to deduce signal-to-noise ratio (SNR) based loglikelihood function involved in detecting low-observable targets (LoTs) including drones Illuminated by a low probability of intercept (LPI) radar operating in littoral regions. Detecting obscure targets and drones and tracking them in near-shore ambient require ascertaining signal-related track-scores determined as a function of radar cross section (RCS) of the target. The stochastic aspects of the RCS depend on non-kinetic features of radar echoes due to target-specific (geometry and material) characteristics; as well as, the associated radar signals signify randomly-implied, kinetic signatures inasmuch as, the spatial aspects of the targets fluctuate significantly as a result of random aspect-angle variations caused by self-maneuvering and/or by remote manipulations (as in drones). Hence, the resulting mean RCS value would decide the SNR and loglikelihood ratio (LR) of radar signals gathered from the echoes and relevant track-scores decide the performance capabilities of the radar. A specific study proposed here thereof refers to developing computationally- tractable algorithm(s) towards detecting and tracking hostile LoTs and/or drones flying at low altitudes over the sea (at a given range, R) in littoral regions by an LPI radar. Estimation of relevant detection-theoretic parameters and decide track-scores in terms of maximum likelihood (ML) estimates are presented and discussed.

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Shi, Chenguang, Yijie Wang, Fei Wang, Sana Salous, and Jianjiang Zhou. "Low probability of intercept‐based OFDM radar waveform design for target time delay estimation in a cooperative radar‐communications system." IET Radar, Sonar & Navigation 13, no. 10 (October 2019): 1697–704. http://dx.doi.org/10.1049/iet-rsn.2019.0172.

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Zhang, Z., J. Zhu, and S. Salous. "A novel dwelling time design method for low probability of intercept in a complex radar network." International Journal of Design & Nature and Ecodynamics 10, no. 4 (December 31, 2015): 309–18. http://dx.doi.org/10.2495/dne-v10-n4-309-318.

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Zhang, Z., J. Zhu, and S. Salous. "A novel dwelling time design method for low probability of intercept in a complex radar network." International Journal of Design & Nature and Ecodynamics 10, no. 4 (December 31, 2015): 310–19. http://dx.doi.org/10.2495/dne-v10-n4-310-319.

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Shi, Chenguang, Jianjiang Zhou, and Fei Wang. "Adaptive resource management algorithm for target tracking in radar network based on low probability of intercept." Multidimensional Systems and Signal Processing 29, no. 4 (May 15, 2017): 1203–26. http://dx.doi.org/10.1007/s11045-017-0494-8.

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Kumari Chilukuri, Raja, Hari Kishore Kakarla, and K. Subba Rao. "Radar Signal Recognition Based on Multilayer Perceptron Neural Network." International journal of electrical and computer engineering systems 14, no. 1 (January 26, 2023): 29–36. http://dx.doi.org/10.32985/ijeces.14.1.4.

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Low Probability of Intercept (LPI) radars are developed on an advanced architecture by making use of coded waveforms. Detection and classification of radar waveforms are important in many critical applications like electronic warfare, threat to radar and surveillance. Precise estimation of parameter and classification of the type of waveform will provide information about the threat to the radar and also helps to develop sophisticated intercept receiver. The present work is on classification of modulation waveforms of LPI radar using multilayer perceptron neural (MLPN) network. The classification approach is based on the following two steps. In the first step, the waveforms are analysed using cyclstationary technique which models the signal in bi-frequency (BF) plane. Using this algorithm, the BF images of the signals are obtained. In the second step, the BF images are fed to a feature extraction unit to get the salient features of the waveform and then to the multilayer perceptron neural (MLPN) network for classification. Nine types of noise free modulation waveforms (Frank, four polyphase codes and four poly time codes) are classified using the images obtained in the first step. The success rate achieved is 100 % for noise free signals. The experiment is repeated for various noise levels up to -12dB SNR. The noisy signals, before feeding to the MLPN network, are denoised using two types of denoising filters connected in cascade and the classification success rate achieved is 93.3% for signals up to -12dB SNR.

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Ma, Zhiyuan, Zhi Huang, Anni Lin, and Guangming Huang. "LPI Radar Waveform Recognition Based on Features from Multiple Images." Sensors 20, no. 2 (January 17, 2020): 526. http://dx.doi.org/10.3390/s20020526.

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Detecting and classifying the modulation type of the intercepted noisy LPI (low probability of intercept) radar signals in real-time is a necessary survival technique in the electronic intelligence systems. Most radar signals have been designed to have LPI properties; therefore, the LPI radar waveform recognition technique (LWRT) has recently gained increasing attention. In this paper, we propose a multiple feature images joint decision (MFIJD) model with two different feature extraction structures that fully extract the pixel feature to obtain the pre-classification results of each feature image for the non-stationary characteristics of most LPI radar signals. The core technology of this model is combining the short-time autocorrelation feature image, double short-time autocorrelation feature image and the original signal time-frequency image (TFI) simultaneously input into the hybrid model classifier, which is suitable for non-stationary signals, and it has higher universality. We demonstrate the performance of MFIJD by simulating 11 types of the signals defined in this paper and generating training sets and test sets. The comparison with the literature shows that the proposed methods not only has a high universality for LPI radar signals, but also better adapts to LPI radar waveform recognition at low SNR (signal to noise ratio) environment. The overall recognition rate of the method reaches 87.7% when the SNR is −6 dB.

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Richter, Renan Miranda, and Thiago de Souza Mansur Pereira. "Análise de desempenho de radares LPI (Low Probalility of Intercept) frente a sensores passivos aeroembarcados de guerra eletrônica." Aplicações Operacionais em Áreas de Defesa 21 (July 21, 2020): 33–39. http://dx.doi.org/10.55972/spectrum.v21i1.74.

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Este artigo traz um estudo acerca da mensuração dos riscos advindos dos radares LPI (Low Probability of Intercept) frente a sensores passivos aeroembarcados de Guerra Eletrônica. Atualmente, tais radares representam o “estado da arte” do combate eletromagnético e ensejam cada vez mais atenção por parte das equipagens oponentes. Estes equipamentos utilizam comumente técnicas de modulação intrapulso, as quais conseguem tornar suas transmissões deveras furtivas, com alcance e resolução radares bastante otimizados. O contraponto feito a sensores passivos justifica-se pelo fato de que a priori tais equipamentos possuem uma vantagem de detecção em distância se comparados ao radar em geral e por isso são bastante difundidos como plataformas stand-off. A análise teórica do artigo repousa sobre os conceitos de modulação intrapulso do tipo LFM (Linear Frequency Modulation) e das equações radar/sensor passivo. Conduziram-se também simulações direcionadas aos aspectos de perda de detecção em distância levando-se em conta alguns cenários de variação de parâmetros do radar e do sensor passivo. O resultado da análise permitiu confirmar o quão um radar LPI pode ser um equipamento de extremo valor em um teatro de operações e o quanto as Forças Armadas brasileiras devem estar atentas ao advento de tais dispositivos.

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Chen, Jun, Jie Wang, Yidong Zhang, Fei Wang, and Jianjiang Zhou. "Spatial Information-Theoretic Optimal LPI Radar Waveform Design." Entropy 24, no. 11 (October 24, 2022): 1515. http://dx.doi.org/10.3390/e24111515.

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In this paper, the design of low probability of intercept (LPI) radar waveforms considers not only the performance of passive interception systems (PISs), but also radar detection and resolution performance. Waveform design is an important considerations for the LPI ability of radar. Since information theory has a powerful performance-bound description ability from the perspective of information flow, LPI waveforms are designed in this paper within the constraints of the detection performance metrics of radar and PISs, both of which are measured by the Kullback–Leibler divergence, and the resolution performance metric, which is measured by joint entropy. The designed optimization model of LPI waveforms can be solved using the sequential quadratic programming (SQP) method. Simulation results verify that the designed LPI waveforms not only have satisfactory target-detecting and resolution performance, but also have a superior low interception performance against PISs.

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Shi, Chenguang, Fei Wang, Sana Salous, and Jianjiang Zhou. "Low Probability of Intercept-Based Radar Waveform Design for Spectral Coexistence of Distributed Multiple-Radar and Wireless Communication Systems in Clutter." Entropy 20, no. 3 (March 16, 2018): 197. http://dx.doi.org/10.3390/e20030197.

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Liu, Yiyuan, Baoguo Li, and Yizhou Yao. "Radar-Embedded Communication Waveform Design Based on Parameter Optimization." Journal of Physics: Conference Series 2404, no. 1 (December 1, 2022): 012032. http://dx.doi.org/10.1088/1742-6596/2404/1/012032.

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Abstract Radar-embedded communication (REC) is a low probability of intercept (LPI) communication method that enables radar and communication to share the spectrum. Covert communication is accomplished by embedding low-power communication waveforms in high-power radar backscatter echoes. This research, by optimizing the eigenvalue matrix power exponent a of the shaped dominant projection (SDP) waveform, proposes an SDP waveform with variable eigenvalue matrix power exponent, namely SDP-a waveform. Then, the reliability of waveform communication and LPI performance are theoretically analyzed by processing gain. Finally, the simulation experiments are carried out with SDP-0.25, SDP-0.5, and SDP-0.75 waveforms as examples. The experimental results are consistent with the theoretical analysis results, indicating that the optimization of the eigenvalue matrix power exponent can meet the performance requirements of different aspects.

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Shi, Chenguang, Fei Wang, Sana Salous, and Jianjiang Zhou. "Low Probability of Intercept-Based Optimal OFDM Waveform Design Strategy for an Integrated Radar and Communications System." IEEE Access 6 (2018): 57689–99. http://dx.doi.org/10.1109/access.2018.2874007.

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Shi, Chenguang, Fei Wang, Mathini Sellathurai, Jianjiang Zhou, and Sana Salous. "Low Probability of Intercept-Based Optimal Power Allocation Scheme for an Integrated Multistatic Radar and Communication System." IEEE Systems Journal 14, no. 1 (March 2020): 983–94. http://dx.doi.org/10.1109/jsyst.2019.2931754.

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Shi, Chenguang, Fei Wang, Mathini Sellathurai, and Jianjiang Zhou. "Non‐cooperative game‐theoretic distributed power control technique for radar network based on low probability of intercept." IET Signal Processing 12, no. 8 (October 2018): 983–91. http://dx.doi.org/10.1049/iet-spr.2017.0355.

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Huang, Ling, Kuandong Gao, Zhiming He, and Jingye Cai. "Cognitive MIMO Frequency Diverse Array Radar with High LPI Performance." International Journal of Antennas and Propagation 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/2623617.

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Frequency diverse array (FDA) has its unique advantage in realizing low probability of intercept (LPI) technology for its dependent beam pattern. In this paper, we proposed a cognitive radar based on the frequency diverse array multiple-input multiple-output (MIMO). To implement LPI of FDA MIMO transmit signals, a scheme for array weighting design is proposed, which is to minimize the energy of the target location and maximize the energy of the receiver. This is based on the range dependent characteristics of the frequency diverse array transmit beam pattern. To realize the objective problem, the algorithm is proposed as follows: the second-order nonconvex optimization problem is converted into a convex problem and solved by the bisection method and convex optimization. To get the information of target, the FDA MIMO radar is proposed to estimate the target parameters. Simulation results show that the proposed approach is effective in decreasing the detection probability of radar with lossless detection performance of the receive signal.

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Mai, Chaoyun, Jinping Sun, Rui Zhou, and Guohua Wang. "Sparse Frequency Waveform Design for Radar-Embedded Communication." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/7270301.

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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.

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Shi, Chenguang, Fei Wang, Sana Salous, and Jianjiang Zhou. "Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept." Sensors 17, no. 12 (November 25, 2017): 2731. http://dx.doi.org/10.3390/s17122731.

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Shi, C. G., F. Wang, S. Salous, and J. J. Zhou. "Joint Transmitter Selection and Resource Management Strategy Based on Low Probability of Intercept Optimization for Distributed Radar Networks." Radio Science 53, no. 9 (September 2018): 1108–34. http://dx.doi.org/10.1029/2018rs006584.

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Jenn, David C., Phillip E. Pace, and Ric A. Romero. "An Antenna for a Mast-Mounted Low Probability of Intercept Continuous Wave Radar: Improving Performance With Digital Architecture." IEEE Antennas and Propagation Magazine 61, no. 2 (April 2019): 63–70. http://dx.doi.org/10.1109/map.2019.2895666.

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Shi, Chenguang, Yijie Wang, Fei Wang, Sana Salous, and Jianjiang Zhou. "Power resource allocation scheme for distributed MIMO dual-function radar-communication system based on low probability of intercept." Digital Signal Processing 106 (November 2020): 102850. http://dx.doi.org/10.1016/j.dsp.2020.102850.

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Andreev, A. Yu. "Naval LPI radars: ways to detect their operation." Transactions of the Krylov State Research Centre 4, no. 402 (October 14, 2022): 115–19. http://dx.doi.org/10.24937/2542-2324-2022-4-402-115-119.

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Object and purpose of research. This paper presents analytical estimates for emission characteristics of foreign low-probability-of-intercept (LPI) radars. It also gives a quantitative assessment to the possibility of detecting the operation of these radars by standard naval EW tools. Subject matter and methods. This paper reviews the publications of leading foreign experts in order to analyse performance parameters of existing foreign LPI radars and ESM tools. Emission characteristics of these “stealthy” radars in marine conditions were calculated by means of the four-beam model of electromagnetic wave scattering over an underlying surface developed by Krylov State Research Centre researchers. Main results. The study yielded a quantitative estimate for the possibility to detect the emission of radar homing head for RBS-15 anti-ship missile by standard naval tools of radioelectronic surveillance. Conclusion. The study has shown that ESM tools currently available with foreign navies cannot reliably detect the operation of LPI radars.

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Quan, Daying, Zeyu Tang, Xiaofeng Wang, Wenchao Zhai, and Chongxiao Qu. "LPI Radar Signal Recognition Based on Dual-Channel CNN and Feature Fusion." Symmetry 14, no. 3 (March 14, 2022): 570. http://dx.doi.org/10.3390/sym14030570.

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The accuracy of low probability of intercept (LPI) radar waveform recognition is an important and challenging problem in electronic warfare. Aiming at the problem of the difficulty in feature extraction and the low recognition rates of the LPI radar signal under a low signal-to-noise ratio, and inspired by the symmetry theory, we propose a new approach for the LPI radar signal recognition method based on a dual-channel convolutional neural network (CNN) and feature fusion. Our new approach contains three main modules: the preprocessing module that converts the LPI radar waveforms into two-dimensional time-frequency images using the Choi–Williams distribution (CWD) transformation and performs image binarization, the feature extraction module that extracts different features obtained from the images, and the recognition module that utilizes a multi-layer perceptron (MLP) network to fuse these features and distinguish the type of LPI radar signals. In the feature extraction module, a two-channel CNN model is proposed that extracts Histogram of Oriented Gradients (HOG) features and deep features from time-frequency images, respectively. Finally, the recognition module recognizes the radar signals using a Softmax classifier based on the fused features from two channels. The experimental results from 12 types of LPI radar signals prove the superiority and robustness of the proposed model. Its overall recognition rate reaches 97% when the signal-to-noise ratio is −6 dB.

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Lee, Ki-Woong, and Woo-Kyung Lee. "The Low Probability of Intercept RADAR Waveform Based on Random Phase and Code Rate Transition for Doppler Tolerance Improvement." Journal of Korean Institute of Electromagnetic Engineering and Science 26, no. 11 (November 30, 2015): 999–1011. http://dx.doi.org/10.5515/kjkiees.2015.26.11.999.

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Shi, Chenguang, Sana Salous, Fei Wang, and Jianjiang Zhou. "Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy." Radio Science 52, no. 8 (August 2017): 1030–45. http://dx.doi.org/10.1002/2017rs006332.

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Journal articles on the topic 'Low probability of intercept radar'

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