Abstract
Drones and birds are typically small, slow targets that fly at a low altitude that surveillance radar systems cannot easily detect. Classic radar detection based on signal amplitude threshold detection. If the envelope of the receiver output exceeds a pre-established threshold, a signal is described as present from a target. The entire premise of amplitude detection is that RCS of an object is larger than the noise in a background, and the signal-to-noise ratio (SNR) is utilized to maintaining the detection probability. If the detection probability is larger than 50%, the SNR of the target is at least 13.1 dB for single pulse detection. This method sometimes fails to detect those weak signals at a long distance due to their small radar cross section (RCS) values and low velocities. Here, we propose a novel radar detection method based on detecting signal to clutter ratios (SCR) in the spectrum. The SCR is identified as the ratio between the spectral peak amplitude of the target to the mean amplitude of the entire spectrum. Although the spectral peak amplitude of the target is lower along the increasing range, the power of the background clutter decays as well. Therefore, SCR value of a target is independent of the detection range. This is useful for detecting targets with small RCS values, including birds, drones, vortex et.al. Theoretically, by using the SCR threshold, the detection range of a target can be as long as the range when the Doppler frequency is unambiguous. We present detection results of birds and drones by using a Ku-band pulsed Doppler radar. When we set the SCR detection threshold at 8 dB, we can detect radar echoes from birds and drones in different channels and range gates well, even at the range of 10km from the radar. We find that birds and multirotor drones have the similar SCR. When using SCR to detect a target, the crucial problem is the recognition of the target peaks, because the false alarm rate must be controlled.
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