Doppler signals of a radar are used to filter moving objects from complicated background noises. In the case of air surveillance radar, the doppler filtering process can be relatively easy because the speed of targets is faster than background noises.
However, in the case of radars for detecting moving vehicles on the ground or drones in the air, the problem to separate doppler signals caused by driving cars from various background noises is considerably difficult – mainly because the bandwidth of doppler signals overlap the bandwidth of doppler signals by background noises. In this situation, traditional methods can lead to frequent false alarms.
Looking far into the distance
Radar pattern recognition (or radar machine learning) that recognize patterns of received signals has been researched and mastered by YOTASYS to overcome these limitations.
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