In coastal surveillance, false target discrimination is about telling legitimate vessels from clutter echoes that can appear on radar due to waves, spray, seabed, birds, weather, and land features. The radar has to cope with a very cluttered environment where many echoes look “real,” so simply detecting a return isn’t enough to declare a target. Radar/clutter effects are handled by techniques that separate moving, real objects from the sea and land clutter. Moving Target Indication and Doppler processing exploit the fact that real ships produce Doppler shifts as they move relative to the radar, while much of the sea clutter sits near zero Doppler or has a broad, low-velocity distribution. By filtering or nulling the low-Doppler clutter and tracking only returns with believable velocity, the system reduces false alarms and highlights genuine targets. This is essential in coastlines where sea state can produce strong, persistent clutter. Beyond Doppler processing, confirming targets with multiple sensors adds confidence. If a radar return is supported by another sensor—such as an optical/EO system, AIS, or magnetic/ acoustic data—the likelihood that it is a real vessel increases. This cross-validation helps reject clutter that might resemble a target in one modality but not in others. Finally, proper track correlation (data association) ties detections across successive scans into coherent tracks. A real vessel follows a consistent motion pattern; clutter or random echoes are unlikely to form a plausible, continuous track. By requiring consistent position, velocity, and trajectory over time, the system further suppresses false targets and maintains accurate situational awareness in complex coastal environments.