Detection of LPI Radar Signals Based on Periodicity Analysis

One of the primary objectives of electronic warfare support (ES) systems is the accurate detection of low-probability-of-intercept (LPI) radar signals. These signals are challenging to detect due to their low transmission power but can be identified through specific patterns. Many of the intercepted LPI radar signals exhibit a pattern of periodic pulse repetition. Therefore, signal samples separated by the pulse repetition time possess a high autocorrelation. This property serves as a pivotal characteristic revealing the periodicity of the radar signal. Based on this characteristic, precise signal detection techniques can be achieved. We introduce the periodic autocorrelation function (PACF), known to be effective for periodicity analysis, and propose a method to effectively detect signals by utilizing PACF. Through simulation results, we analyze the signal detection performance of our proposed method. Furthermore, we present results comparing the detection performance of the proposed method with existing signal detection methods.