How are false alarms typically managed in CRC operations?

• A. Increasing sensor sensitivity
• B. Sensor fusion, corroboration across sensors, and threat scoring to filter out non-threats
• C. Random sampling
• D. Decreasing data update rate

Answer: (B)

Managing false alarms in CRC operations relies on bringing multiple sensor observations together and evaluating how likely a contact is a real threat. Sensor fusion combines data from different sensors to create a single, coherent picture of a contact’s position, velocity, and trajectory. Corroboration across sensors means different sensors independently confirm the same target’s existence and movement, which greatly reduces coincidental detections from clutter or noise. Threat scoring adds an assessment layer that weighs how credible the contact is based on factors like track consistency over time, maneuver patterns, sensor confidence, and estimated threat characteristics. When the score indicates a real threat, it triggers appropriate action; when it doesn’t, the contact can be filtered out, keeping operators focused on genuine hazards.

Raising sensor sensitivity tends to increase false alarms by capturing more noise and non-threat clutter. Random sampling doesn’t enhance confirmation across sensors and can miss real threats. Decreasing the data update rate slows or disrupts tracking and doesn’t address false alarms effectively.