Summary: Researchers at UCLA’s Department of Electrical and Computer Engineering have developed a novel synthesizer-free phase imaging radar that generates high-resolution images with low power consumption.
Background: Imaging radars are used in various applications, from self-driving cars and aircraft navigation to medical screening. Traditional frequency-modulated continuous wave (FMCW) radar struggles with high power demands and limited resolution. While phase imaging offers superior resolution at longer wavelengths, existing systems suffer from self-interference, frequency drift, and high noise, requiring complex hardware and phase-locked loops (PLLs) for stability. There is an unmet need for a simpler, energy-efficient radar capable of producing high-resolution images without the drawbacks of conventional systems.
Innovation: UCLA researchers led by Professor Aydin Babakhani have developed a low-power phase imaging radar that eliminates the need for a synthesizer while maintaining high resolution. The device uses a free-running oscillator to achieve locked-in frequencies, reducing hardware complexity. Further, it operates efficiently at low and high frequencies making it suitable for on-chip and off-chip applications in obtaining precise distance, amplitude, and wave sensing data. By avoiding self-interference, the system minimizes power consumption, making it an ideal solution for phase imaging radar. The proposed solution enhances state-of-the-art radar systems with high-resolution imaging and improved energy efficiency by eliminating the need for a synthesizer.
Potential Applications: ● Evanescent field sensing ● On-chip and off-chip antenna/resonators ● Automotive radar ● Imaging systems ● Biosensing ● Defense and military applications ● Security systems
Advantages: ● No self-interference ● High resolution imaging ● Insensitive to noise ● Simplified design with free-running oscillator
State of Development: The device has been successfully developed and demonstrated, outperforming existing models with higher resolution, lower power consumption, and the ability to operate with a free-running oscillator.
Related Papers: [1] Zheng, K., Qian, K., Woodford, T., & Zhang, X. (2023). NeuroRadar: A Neuromorphic Radar Sensor for Low-Power IoT Systems. [2] Juan, P. H., Chen, K. H., & Wang, F. K. (2020). Frequency-offset self-injection-locked radar with digital frequency demodulation for SNR improvement, elimination of EMI issue, and DC offset calibration. IEEE Transactions on Microwave Theory and Techniques, 69(1), 1149-1160.
Reference: UCLA Case No. 2024-190
Lead Inventor: Aydin Babakhani