Design of Costas/PSK continuous wave LPI radar signal

Yang, Hongbing

doi:10.1080/00207217.2016.1218060

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…Interferometer-based radar can also deliver good distance accuracy however its unambiguity distance is limited to the carrier wavelength and complicated calibration is often required [6]. With a two-tone signal, the unambiguity distance can be extended [7] and AM-modulated radar is another approach of generating two tones [9]. Both works require the shifting of center frequency in order to avoid interference.…”

Section: Discussionmentioning

confidence: 99%

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Micrometer Accuracy Phase Modulated Radar for Distance Measurement and Monitoring

An¹,

He²,

Li³

et al. 2020

IEEE Sensors J.

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An enhanced accuracy random binary phase modulated radar is proposed. It can be used in high accuracy monitoring in manufacturing. Compared with the traditional high accuracy radar using frequency modulated continuous wave (FMCW), the proposed radar system can be used in a multiuser scenario without occupying more bandwidth. A two-step distance estimation method is introduced to estimate the distance. First, the distance estimation accuracy is narrowed down to a half carrier wavelength by analyzing the envelope of the phase modulated signal. Then the carrier phase information increases the distance accuracy to several micrometers. An equalization method is introduced to solve the I/Q imbalance problem. The proposed radar system is demonstrated at a carrier frequency of 80 GHz with a bandwidth of 2 GHz. The measured distance error was within ±7 μm. In addition, a high measurement repetition rate of 500 kHz was reached which is suitable for real-time monitoring in automatic manufacturing.

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Section: Discussionmentioning

confidence: 99%

“…For phase modulated radars, different coding can ensure multiple radars could coexist within the same spectrum slot. The accuracy of the phase modulated radar is however often limited by the modulation bandwidth [9].…”

mentioning

confidence: 99%

Micrometer Accuracy Phase Modulated Radar for Distance Measurement and Monitoring

An¹,

He²,

Li³

et al. 2020

IEEE Sensors J.

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“…Correct recognition of intra-pulse modulation of radar signal can not only help to deduce the function of enemy radar, thus judging its threat level, but also improve the accuracy of parameter estimation. Due to the increasing density of radar signals in the modern electronic warfare environment and the use of large time-width pulse compression signals with complex modulation in most modern radar signals [3], [4], radar…”

Section: Introductionmentioning

confidence: 99%

Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network and Deep Q-Learning Network

Hou

et al. 2020

IEEE Access

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Intra-pulse modulation recognition of radar signals is an important part of modern electronic intelligence reconnaissance and electronic support systems. With the increasing density of radar signals, the analysis and processing of multi-component radar signals have become an urgent problem in the current radar reconnaissance system. In this paper, an intra-pulse modulation recognition approach for singlecomponent and dual-component radar signals is proposed. First, in order to adapt to the time-frequency energy distribution characteristics of various radar signals, we propose to extract the time-frequency images (TFIs) of received signals by Cohen class time-frequency distribution (CTFD) with multiple kernel functions. Besides, the image processing methods are used to suppress noise and adjust the size and amplitude of the TFIs. Second, we design and pre-train a TFI feature extraction network for radar signals based on a convolutional neural network (CNN). Finally, to improve the probability of successful recognition (PSR) of the recognition system in the pulse overlapping environment, a multi-label classification network based on a deep Q-learning network (DQN) is explored. Besides, two sub-networks take TFIs based on special kernel functions as input and re-judge the recognition results of some specific signals to further enhance the recognition effect of the recognition system. The proposed approach can identify 8 kinds of random overlapping radar signals. The simulation results show that the overall PSR of dual-component radar signals and single-component radar signals can reach 94.83% and 94.43%, respectively, when the signal-to-noise ratio (SNR) is −6 dB. INDEX TERMS Radar signal recognition, Cohen class time-frequency distribution, convolutional neural network, deep Q-learning network.

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“…The use of low-power continuous wave technology to diminish the chance of power interception is a superior low-interception method. It minimizes the peak of instantaneous power in the waveform by spreading the energy over an extended duration, thereby reducing the reconnaissance system's probability of interception [8,9]. Low-side-lobe antenna technology deliberately prevents the ES system from acquiring excess radiated energy, effectively preventing energy leakage and decreasing the interception likelihood [10].…”

Section: Introductionmentioning

confidence: 99%

LPI Sequences Optimization Method against Summation Detector Based on FFT Filter Bank

Liu,

Guo,

Xiong

et al. 2024

Remote Sensing

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Waveform design is a crucial factor in electronic surveillance (ES) systems. In this paper, we introduce an algorithm that designs a low probability of intercept (LPI) radar waveform. Our approach directly minimizes the detection probability of summation detectors based on FFT filter banks. The algorithm is derived from the general quadratic optimization framework, which inherits the monotonic properties of such methods. To expedite overall convergence, we have integrated acceleration schemes based on the squared iterative method (SQUAREM). Additionally, the proposed algorithm can be executed through fast Fourier transform (FFT) operations, enhancing computational efficiency. With some modifications, the algorithm can be adjusted to incorporate spectral constraints, increasing its flexibility. Numerical experiments indicate that our proposed algorithm outperforms existing ones in terms of both intercept properties and computational complexity.

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Design of Costas/PSK continuous wave LPI radar signal

Cited by 7 publications

References 16 publications

Micrometer Accuracy Phase Modulated Radar for Distance Measurement and Monitoring

Micrometer Accuracy Phase Modulated Radar for Distance Measurement and Monitoring

Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network and Deep Q-Learning Network

LPI Sequences Optimization Method against Summation Detector Based on FFT Filter Bank

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