@inproceedings{dbb35dbcf5d04f4fafe14f65a0f2ee86,
title = "Blind detection of radar pulse trains via self-convolution",
abstract = "This paper studies the blind detection of radar pulse trains using self-convolution. The self-convolution of a horizontally polarized pulse train with a constant pulse repetition frequency (PRF) is the same as its autocorrelation, only shifted in time, provided that the pulses are symmetric. This makes the waveform amenable to blind detection even in the presence of a constant Doppler shift. Once detected, we estimate the carrier, demodulate, and estimate the PRF of the baseband train using a logarithmic frequency domain matched filter. We derive a Neyman-Pearson self-convolution detection threshold for additive white Gaussian noise (AWGN) and conduct numerical experiments to compare the Signal-to-Noise Ratio (SNR) performance against standard matched filtering. We also illustrate the logarithmic frequency matched filter's PRF estimation accuracy.",
keywords = "Blind-detection, Electronic-intelligence, Prf-estimation, Pulse-trains, Radar, Self-convolution",
author = "Alex Byrley and Adly Fam",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Autonomous Systems, ICAS 2021 ; Conference date: 11-08-2021 Through 13-08-2021",
year = "2021",
month = aug,
day = "11",
doi = "10.1109/ICAS49788.2021.9551181",
language = "English",
series = "ICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings",
address = "United States",
}