Estimation of modulation parameters for LPI radar using Quadrature Mirror Filter Bank

Shyamsunder, Metuku; Subbarao, K.T.V; Regimanu, Bharath; Teja, Cvssd Krishna

doi:10.1109/upcon.2016.7894659

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…References [ 24 , 25 , 26 , 27 , 28 ] introduce techniques for conducting TFA and extracting modulation parameters from deterministic signals assumed LPI/LPE. However, these techniques have a drawback: the extraction process relies exclusively on visual analysis.…”

Section: Introductionmentioning

confidence: 99%

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications

Barbosa,

Pralon,

Ramos

et al. 2024

Sensors

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The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal’s ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than −10 dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems.

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Section: Introductionmentioning

confidence: 99%

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications

Barbosa,

Pralon,

Ramos

et al. 2024

Sensors

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“…A method based on modified Wigner Hough Transform (WHT) is applied to detect Frank, P1, P2, P3, P4, and LFM types LPI radar signals and detection performance compared to Generalized (WHT) [13]. QMFB analysis is used for parameter extraction in P1, P2, P3, and P4 type polyphase signals [22]. The extracted parameters from the TF image are carrier frequency, number of phases, and cycle per phase.…”

Section: Introductionmentioning

confidence: 99%

LPI Radar Signal Detection Based on Autocorrelation Function and Wigner-Ville Distribution

Ünal¹,

Pakfiliz²

2022

RCES

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Low probability of intercept (LPI) radar systems is designed "to see and not to be seen." Low peak power, low sidelobe antenna pattern, wide bandwidth, and spread spectrum waveform are their typical characteristics to prevent detection by noncooperative electronic warfare receivers. As a result, in terms of Electronic Warfare systems, the detection of an unknown LPI radar has great importance and requires special techniques. While a few studies have been done on this subject, many open points still need to be managed. This paper presents an LPI radar signal detection algorithm based on autocorrelation and time-frequency image-based moments. Detection does not require any prior information on radar signals. Detection performance for different types of LPI radar signal waveform is studied. The results showed that detection is possible under low SNR.

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Reduced complexity and near optimum detector for linear‐frequency‐modulated and phase‐modulated LPI radar signals

Dezfuli

Shokouhmand

Oveis

et al. 2019

IET Radar, Sonar & Navigation

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Estimation of modulation parameters for LPI radar using Quadrature Mirror Filter Bank

Cited by 3 publications

References 4 publications

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications

LPI Radar Signal Detection Based on Autocorrelation Function and Wigner-Ville Distribution

Reduced complexity and near optimum detector for linear‐frequency‐modulated and phase‐modulated LPI radar signals

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