研究目的
To mitigate the leakage phase noise in heterodyne FMCW radars for small drone detection, which raises the noise floor and limits sensitivity, by proposing a stationary point concentration (SPC) technique that concentrates the noise on a stationary point using digital signal processing without additional hardware.
研究成果
The SPC technique effectively mitigates the dominant leakage phase noise in heterodyne FMCW radars, significantly lowering the noise floor and increasing SNR for small drone detection. It provides accurate distance information and can be implemented using DSP without additional hardware, offering a novel approach compared to existing methods. Future work could address minor leakages and optimize for complex environments.
研究不足
The technique assumes a dominant leakage signal; minor leakages from other paths may not be fully mitigated, especially at near distances. The accuracy depends on FFT resolution, and computational load increases with larger NFFT values. The method requires strategic frequency planning and oversampling, which may not be optimal for all radar designs. Real-time implementation might be challenging due to processing time constraints.
1：Experimental Design and Method Selection:
The study employs a heterodyne FMCW radar system to detect small drones. The SPC technique is designed to mitigate leakage phase noise by concentrating it on a stationary point through digital signal processing (DSP) without extra hardware. Theoretical models include equations for signal processing and phase noise analysis.
2：Sample Selection and Data Sources:
The experiments use no targets for noise floor measurement and small drones (DJI Inspire I and DJI Spark) for target detection. Data is collected from radar signals in a quasi-monostatic configuration with antennas 25 cm apart, installed on a rooftop.
3：List of Experimental Equipment and Materials:
A Ku-band heterodyne FMCW radar system comprising baseband and IF stages, a block up converter, a low-noise block, corrugated conical horn antennas, Analog Devices AD9854 direct digital synthesizer, Ettus USRP N210 software-defined radio, and a mini-PC with MATLAB R2017a for DSP.
4：Experimental Procedures and Operational Workflow:
For Experiment A, measure the noise floor with only leakage present. For Experiment B, place drones at askew directions and measure signals. Oversample IF beat signals using USRP N210, apply FFT with zero-padding to extract frequency and phase of leakage, generate a digital NCO, perform last down-conversion, and use digital LPF and decimation.
5：Data Analysis Methods:
Analyze power spectra using MATLAB, compute SNR improvements, and compare results with simulations. Statistical techniques include averaging over multiple chirps for noise floor reduction analysis.
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