(untitled) (International Journal of Environmental Sciences, 2024)
Reliable spectrum sensing remains a key challenge in aeronautical cognitive communications, particularly under high mobility, fluctuating noise, and adversarial interference. This paper proposes an Adaptive Multi-stage Robust Correlator (AMRC) that combines a two-stage correlation architecture with adaptive thresholding and an entropy–variance anomaly detector for enhanced spoofing and jamming resilience. The proposed framework is implemented and validated through Monte Carlo simulations in MATLAB/Simulink using ITU aeronautical channel models. Results demonstrate that AMRC achieves up to 5–7 dB SNR gain in detection probability (Pd) compared to conventional single-stage correlators, while reducing average energy consumption by nearly 50% relative to the baseline. The scheme also shows superior robustness under Doppler shifts of up to 400 Hz, with less than 5% degradation in Pd and maintains false-alarm rates (Pfa​) below 0.1 even under increased noise variance and targeted spoofing attempts. These results confirm that AMRC offers a favorable balance between detection reliability, energy efficiency, and resilience to hostile interference, making it a strong candidate for practical deployment in LDACS and related aeronautical systems.