Mapping Chaos to Evaluate LPI Characteristics of Radar Systems

Traditionally utilized radar systems may achieve high range and doppler resolution but are vulnerable to detection and interference because they stand out in the presence of noise and can be quickly assessed. The type of transmitted waveform influences both the efficiency of the radar system and the ease of intercept by potential adversaries who may impose electronic countermeasures (ECM) on the radar system. Chaos, though deterministic, is unpredictable, aperiodic, and sensitive to initial conditions as it is bounded with featureless properties. They are considered to be pseudo-random waveforms that cannot be easily detected and replicated by the ECM systems. Chaotic waveforms exhibit characteristics that align with the goals of enhancing low probability of intercept/detection (LPI/LPD) capabilities, as they seamlessly blend with the existing noise in the environment. Additionally, the sensitivity of initial conditions entices features that can be used for electronic counter-countermeasures (ECCM) applications. By applying power spectrum analysis, and cyclostationary analysis, signals can be assessed for their LPI and LPD capabilities. The cyclostationary analysis helps identify man made artificial signals by detecting inherent periodicities inside them. We apply both spectral correlation and 3rd order cumulant analysis to determine the efficacy of various chaotic waveforms in LPI and LPD applications.