Direction Finding Techniques for Over-the-Horizon Radars

Abstract

There is no ultimate intelligence-gathering discipline. Intelligence products almost always require multiple sources for further analytical processing. However, signals intelligence represents a unique gathering discipline since information is derived from both communication and noncommunication electromagnetic emissions; it operates passively and is usually highly reliable. A subdivision of signals intelligence dedicated solely to the noncommunication emission is electronic intelligence. It focuses mainly on emitters such as radars, telemetry systems and radio navigation systems. Over-the-horizon radars are part of systems for long-range detection. This paper presents a comprehensive evaluation of three distinct direction-finding methods implemented within a unified three-channel coherent system for the bearing estimation of over-the-horizon (OTH) radar transmitters. The key contribution lies in the detailed simulation-based assessment of these methods under varying signal-to-noise ratio (SNR) conditions using realistic waveform parameters derived from measured real OTH radar signals. The results quantitatively characterise the operational strengths and limitations of each method, offering a practical foundation for algorithm selection in electronic intelligence applications and enabling future integration of machine learning models to enhance direction-finding performance in a dynamic operational environment.