An Investigation of LPI Radar Waveforms Classification in RoF Channels

Abstract

Intensive research has been developed to either design or classify low probability of intercept (LPI) radar signals. These types of signals are used in different sensitive electronic warfare applications such as electronic support, electronic attack, and radar emitter identification. Linear frequency modulation, nonlinear frequency modulation, frequency shift keying, polyphase Barker, polyphase P1, P2, P3, P4 and Frank codes are examples of LPI waveforms. In this paper, we consider the modulation classification problem under the effect of transporting the captured radar signals through radio over fiber channels. Distortions and noise introduced by such channels are likely to affect the performance of LPI classification algorithms. Here, we investigate the accuracy of a recently proposed hierarchical decision-tree automatic modulation classification algorithm for additive white Gaussian noise channels and provide the necessary adjustments when the intercepted radar signals are transmitted over fiber optic channels. The investigation is conducted by simulations and experimental demonstration. The obtained results show that for an 80 km fiber link and noisy intercepted LPI signals, the average identification accuracy reaches more than 98%, at 16 dB optical signal-to-noise ratio.

Keywords

• Automatic modulation classification (AMC)
• low probability of intercept (LPI) radar waveforms
• intrapulse
• electronic support (ES)
• electronic attacks (EA)