Enhanced Perimeter Intrusion Detection System (PIDS) - Resilient to Environmental Variations for Military Applications

Perimeter intrusion detection systems (PIDS) often face challenges in accurately detecting breaches while minimizing false alarms triggered by environmental factors. This paper presents a reliable PIDS approach integrating fiber optic sensing with several environmental transducers and a sophisticated control algorithm. The technical framework uses a distributed network of fiber optic cables installed along the perimeter as sensors to detect vibrations and disturbances. These high-sensitivity fiber optic sensors provide input data to the control system. Environmental transducers like rain gauges, anemometers, and temperature sensors are incorporated to detect weather conditions near the perimeter.The core innovation is a two-part control algorithm that analyzes this multi-modal sensor data to classify events and make intelligent decisions. The first segment uses historical data to establish adaptive baselines tuned to different conditions. Machine learning models extract informative features to distinguish between various types of events. The second segment employs anomaly detection to identify disturbances in real-time sensor data. A Gaussian Mixture Model algorithm models normal behavior and detects outliers.Rigorous testing under diverse simulated scenarios will validate the system's ability to detect intrusions reliably while minimizing false alarms caused by changing environmental contexts. Key advantages over existing methods include higher precision, addressing cold start problems, real-time low latency performance, cost-effectiveness, and resilience to unforeseen events. The proposed system promises substantial military payoffs by enhancing perimeter security and response efficacy.