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