|
|
|
| Research on Radar Detection of Drones Using Micro-Doppler Signals |
| YAN Jun1， GU Cunfeng2， KONG Deyong3， GONG Jiangkun1 |
| 1. State Key Laboratory of Information Engineering in Surveying， Mapping and Remote Sensing， Wuhan University， Wuhan 430079， Hubei， China； 2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China；
3. Hubei University of Economics， Wuhan 430205， Hubei， China |
|
|
|
|
Abstract Recently, the proliferation of drones has driven significant advancements in anti-drone radar systems. However, radar signals produced by the small radar cross-sections (RCS) and low velocities of drones is challenging to detect, especially when obscured by background clutter. This leads to high missed alarm rates and limited detection ranges when using traditional signal-to-noise ratio (SNR) detectors. In this paper, a method transforming the micro-Doppler signals from drones into jet engine modulation (JEM) Doppler signals was proposed. Then, a signal-to-clutter ratio (SCR) detector specifically designed to identify these Doppler signals was introduced. Test results from both a microwave anechoic chamber and outdoor environments demonstrate that micro-Doppler signals are captured in the radar echoes of both quad-rotor and VTOL fixed-wing drones across multiple radar bands. Besides, the SCR detector outperforms the SNR detector, exhibiting better detection stability, higher detection probabilities, and lower missed alarm rates.
|
|
Received: 10 May 2023
Published: 22 March 2025
|
|
|
|
|
|
|
|
|
2025, Vol. 8 
